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verilator/src/V3Dfg.cpp

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Introduce DFG based combinational logic optimizer (#3527) Added a new data-flow graph (DFG) based combinational logic optimizer. The capabilities of this covers a combination of V3Const and V3Gate, but is also more capable of transforming combinational logic into simplified forms and more. This entail adding a new internal representation, `DfgGraph`, and appropriate `astToDfg` and `dfgToAst` conversion functions. The graph represents some of the combinational equations (~continuous assignments) in a module, and for the duration of the DFG passes, it takes over the role of AstModule. A bulk of the Dfg vertices represent expressions. These vertex classes, and the corresponding conversions to/from AST are mostly auto-generated by astgen, together with a DfgVVisitor that can be used for dynamic dispatch based on vertex (operation) types. The resulting combinational logic graph (a `DfgGraph`) is then optimized in various ways. Currently we perform common sub-expression elimination, variable inlining, and some specific peephole optimizations, but there is scope for more optimizations in the future using the same representation. The optimizer is run directly before and after inlining. The pre inline pass can operate on smaller graphs and hence converges faster, but still has a chance of substantially reducing the size of the logic on some designs, making inlining both faster and less memory intensive. The post inline pass can then optimize across the inlined module boundaries. No optimization is performed across a module boundary. For debugging purposes, each peephole optimization can be disabled individually via the -fno-dfg-peepnole-<OPT> option, where <OPT> is one of the optimizations listed in V3DfgPeephole.h, for example -fno-dfg-peephole-remove-not-not. The peephole patterns currently implemented were mostly picked based on the design that inspired this work, and on that design the optimizations yields ~30% single threaded speedup, and ~50% speedup on 4 threads. As you can imagine not having to haul around redundant combinational networks in the rest of the compilation pipeline also helps with memory consumption, and up to 30% peak memory usage of Verilator was observed on the same design. Gains on other arbitrary designs are smaller (and can be improved by analyzing those designs). For example OpenTitan gains between 1-15% speedup depending on build type.
2022-09-23 17:46:22 +02:00
// -*- mode: C++; c-file-style: "cc-mode" -*-
//*************************************************************************
// DESCRIPTION: Verilator: Data flow graph (DFG) representation of logic
//
// Code available from: https://verilator.org
//
//*************************************************************************
//
Copyright year update.
2025-01-01 14:30:25 +01:00
// Copyright 2003-2025 by Wilson Snyder. This program is free software; you
Introduce DFG based combinational logic optimizer (#3527) Added a new data-flow graph (DFG) based combinational logic optimizer. The capabilities of this covers a combination of V3Const and V3Gate, but is also more capable of transforming combinational logic into simplified forms and more. This entail adding a new internal representation, `DfgGraph`, and appropriate `astToDfg` and `dfgToAst` conversion functions. The graph represents some of the combinational equations (~continuous assignments) in a module, and for the duration of the DFG passes, it takes over the role of AstModule. A bulk of the Dfg vertices represent expressions. These vertex classes, and the corresponding conversions to/from AST are mostly auto-generated by astgen, together with a DfgVVisitor that can be used for dynamic dispatch based on vertex (operation) types. The resulting combinational logic graph (a `DfgGraph`) is then optimized in various ways. Currently we perform common sub-expression elimination, variable inlining, and some specific peephole optimizations, but there is scope for more optimizations in the future using the same representation. The optimizer is run directly before and after inlining. The pre inline pass can operate on smaller graphs and hence converges faster, but still has a chance of substantially reducing the size of the logic on some designs, making inlining both faster and less memory intensive. The post inline pass can then optimize across the inlined module boundaries. No optimization is performed across a module boundary. For debugging purposes, each peephole optimization can be disabled individually via the -fno-dfg-peepnole-<OPT> option, where <OPT> is one of the optimizations listed in V3DfgPeephole.h, for example -fno-dfg-peephole-remove-not-not. The peephole patterns currently implemented were mostly picked based on the design that inspired this work, and on that design the optimizations yields ~30% single threaded speedup, and ~50% speedup on 4 threads. As you can imagine not having to haul around redundant combinational networks in the rest of the compilation pipeline also helps with memory consumption, and up to 30% peak memory usage of Verilator was observed on the same design. Gains on other arbitrary designs are smaller (and can be improved by analyzing those designs). For example OpenTitan gains between 1-15% speedup depending on build type.
2022-09-23 17:46:22 +02:00
// can redistribute it and/or modify it under the terms of either the GNU
// Lesser General Public License Version 3 or the Perl Artistic License
// Version 2.0.
// SPDX-License-Identifier: LGPL-3.0-only OR Artistic-2.0
//
//*************************************************************************
Fix header order botched by clang-format in recent commit.
2023-10-18 12:37:46 +02:00
#include "V3PchAstNoMT.h" // VL_MT_DISABLED_CODE_UNIT
Introduce DFG based combinational logic optimizer (#3527) Added a new data-flow graph (DFG) based combinational logic optimizer. The capabilities of this covers a combination of V3Const and V3Gate, but is also more capable of transforming combinational logic into simplified forms and more. This entail adding a new internal representation, `DfgGraph`, and appropriate `astToDfg` and `dfgToAst` conversion functions. The graph represents some of the combinational equations (~continuous assignments) in a module, and for the duration of the DFG passes, it takes over the role of AstModule. A bulk of the Dfg vertices represent expressions. These vertex classes, and the corresponding conversions to/from AST are mostly auto-generated by astgen, together with a DfgVVisitor that can be used for dynamic dispatch based on vertex (operation) types. The resulting combinational logic graph (a `DfgGraph`) is then optimized in various ways. Currently we perform common sub-expression elimination, variable inlining, and some specific peephole optimizations, but there is scope for more optimizations in the future using the same representation. The optimizer is run directly before and after inlining. The pre inline pass can operate on smaller graphs and hence converges faster, but still has a chance of substantially reducing the size of the logic on some designs, making inlining both faster and less memory intensive. The post inline pass can then optimize across the inlined module boundaries. No optimization is performed across a module boundary. For debugging purposes, each peephole optimization can be disabled individually via the -fno-dfg-peepnole-<OPT> option, where <OPT> is one of the optimizations listed in V3DfgPeephole.h, for example -fno-dfg-peephole-remove-not-not. The peephole patterns currently implemented were mostly picked based on the design that inspired this work, and on that design the optimizations yields ~30% single threaded speedup, and ~50% speedup on 4 threads. As you can imagine not having to haul around redundant combinational networks in the rest of the compilation pipeline also helps with memory consumption, and up to 30% peak memory usage of Verilator was observed on the same design. Gains on other arbitrary designs are smaller (and can be improved by analyzing those designs). For example OpenTitan gains between 1-15% speedup depending on build type.
2022-09-23 17:46:22 +02:00
#include "V3Dfg.h"
#include "V3File.h"
DFG: Extract cyclic components separately A lot of optimizations in DFG assume a DAG, but the more things are representable, the more likely it is that a small cyclic sub-graph is present in an otherwise very large graph that is mostly acyclic. In order to avoid loosing optimization opportunities, we explicitly extract the cyclic sub-graphs (which are the strongly connected components + anything feeing them, up to variable boundaries) and treat them separately. This enables optimization of the remaining input.
2022-09-28 15:42:18 +02:00
VL_DEFINE_DEBUG_FUNCTIONS;
Introduce DFG based combinational logic optimizer (#3527) Added a new data-flow graph (DFG) based combinational logic optimizer. The capabilities of this covers a combination of V3Const and V3Gate, but is also more capable of transforming combinational logic into simplified forms and more. This entail adding a new internal representation, `DfgGraph`, and appropriate `astToDfg` and `dfgToAst` conversion functions. The graph represents some of the combinational equations (~continuous assignments) in a module, and for the duration of the DFG passes, it takes over the role of AstModule. A bulk of the Dfg vertices represent expressions. These vertex classes, and the corresponding conversions to/from AST are mostly auto-generated by astgen, together with a DfgVVisitor that can be used for dynamic dispatch based on vertex (operation) types. The resulting combinational logic graph (a `DfgGraph`) is then optimized in various ways. Currently we perform common sub-expression elimination, variable inlining, and some specific peephole optimizations, but there is scope for more optimizations in the future using the same representation. The optimizer is run directly before and after inlining. The pre inline pass can operate on smaller graphs and hence converges faster, but still has a chance of substantially reducing the size of the logic on some designs, making inlining both faster and less memory intensive. The post inline pass can then optimize across the inlined module boundaries. No optimization is performed across a module boundary. For debugging purposes, each peephole optimization can be disabled individually via the -fno-dfg-peepnole-<OPT> option, where <OPT> is one of the optimizations listed in V3DfgPeephole.h, for example -fno-dfg-peephole-remove-not-not. The peephole patterns currently implemented were mostly picked based on the design that inspired this work, and on that design the optimizations yields ~30% single threaded speedup, and ~50% speedup on 4 threads. As you can imagine not having to haul around redundant combinational networks in the rest of the compilation pipeline also helps with memory consumption, and up to 30% peak memory usage of Verilator was observed on the same design. Gains on other arbitrary designs are smaller (and can be improved by analyzing those designs). For example OpenTitan gains between 1-15% speedup depending on build type.
2022-09-23 17:46:22 +02:00
//------------------------------------------------------------------------------
// DfgGraph
//------------------------------------------------------------------------------
DfgGraph::DfgGraph(AstModule& module, const string& name)
: m_modulep{&module}
, m_name{name} {}
DfgGraph::~DfgGraph() {
forEachVertex([](DfgVertex& vtxp) { delete &vtxp; });
}
void DfgGraph::addGraph(DfgGraph& other) {
Speed up DfgGraph::addGraph Append whole lists in one go, rather than going item by item.
2022-10-08 13:05:30 +02:00
m_size += other.m_size;
other.m_size = 0;
Improve V3List user interface (#4996)
2024-03-26 00:06:25 +01:00
for (DfgVertexVar& vtx : other.m_varVertices) {
vtx.m_userCnt = 0;
vtx.m_graphp = this;
}
m_varVertices.splice(m_varVertices.end(), other.m_varVertices);
for (DfgConst& vtx : other.m_constVertices) {
vtx.m_userCnt = 0;
vtx.m_graphp = this;
}
m_constVertices.splice(m_constVertices.end(), other.m_constVertices);
for (DfgVertex& vtx : other.m_opVertices) {
vtx.m_userCnt = 0;
vtx.m_graphp = this;
}
m_opVertices.splice(m_opVertices.end(), other.m_opVertices);
Introduce DFG based combinational logic optimizer (#3527) Added a new data-flow graph (DFG) based combinational logic optimizer. The capabilities of this covers a combination of V3Const and V3Gate, but is also more capable of transforming combinational logic into simplified forms and more. This entail adding a new internal representation, `DfgGraph`, and appropriate `astToDfg` and `dfgToAst` conversion functions. The graph represents some of the combinational equations (~continuous assignments) in a module, and for the duration of the DFG passes, it takes over the role of AstModule. A bulk of the Dfg vertices represent expressions. These vertex classes, and the corresponding conversions to/from AST are mostly auto-generated by astgen, together with a DfgVVisitor that can be used for dynamic dispatch based on vertex (operation) types. The resulting combinational logic graph (a `DfgGraph`) is then optimized in various ways. Currently we perform common sub-expression elimination, variable inlining, and some specific peephole optimizations, but there is scope for more optimizations in the future using the same representation. The optimizer is run directly before and after inlining. The pre inline pass can operate on smaller graphs and hence converges faster, but still has a chance of substantially reducing the size of the logic on some designs, making inlining both faster and less memory intensive. The post inline pass can then optimize across the inlined module boundaries. No optimization is performed across a module boundary. For debugging purposes, each peephole optimization can be disabled individually via the -fno-dfg-peepnole-<OPT> option, where <OPT> is one of the optimizations listed in V3DfgPeephole.h, for example -fno-dfg-peephole-remove-not-not. The peephole patterns currently implemented were mostly picked based on the design that inspired this work, and on that design the optimizations yields ~30% single threaded speedup, and ~50% speedup on 4 threads. As you can imagine not having to haul around redundant combinational networks in the rest of the compilation pipeline also helps with memory consumption, and up to 30% peak memory usage of Verilator was observed on the same design. Gains on other arbitrary designs are smaller (and can be improved by analyzing those designs). For example OpenTitan gains between 1-15% speedup depending on build type.
2022-09-23 17:46:22 +02:00
}
static const string toDotId(const DfgVertex& vtx) { return '"' + cvtToHex(&vtx) + '"'; }
// Dump one DfgVertex in Graphviz format
static void dumpDotVertex(std::ostream& os, const DfgVertex& vtx) {
DFG: Partial support for unpacked arrays Representation and Ast / Dfg conversions available, for element-wise access only. Not much optimization yet (only CSE).
2022-09-27 01:06:50 +02:00
if (const DfgVarPacked* const varVtxp = vtx.cast<DfgVarPacked>()) {
Introduce DFG based combinational logic optimizer (#3527) Added a new data-flow graph (DFG) based combinational logic optimizer. The capabilities of this covers a combination of V3Const and V3Gate, but is also more capable of transforming combinational logic into simplified forms and more. This entail adding a new internal representation, `DfgGraph`, and appropriate `astToDfg` and `dfgToAst` conversion functions. The graph represents some of the combinational equations (~continuous assignments) in a module, and for the duration of the DFG passes, it takes over the role of AstModule. A bulk of the Dfg vertices represent expressions. These vertex classes, and the corresponding conversions to/from AST are mostly auto-generated by astgen, together with a DfgVVisitor that can be used for dynamic dispatch based on vertex (operation) types. The resulting combinational logic graph (a `DfgGraph`) is then optimized in various ways. Currently we perform common sub-expression elimination, variable inlining, and some specific peephole optimizations, but there is scope for more optimizations in the future using the same representation. The optimizer is run directly before and after inlining. The pre inline pass can operate on smaller graphs and hence converges faster, but still has a chance of substantially reducing the size of the logic on some designs, making inlining both faster and less memory intensive. The post inline pass can then optimize across the inlined module boundaries. No optimization is performed across a module boundary. For debugging purposes, each peephole optimization can be disabled individually via the -fno-dfg-peepnole-<OPT> option, where <OPT> is one of the optimizations listed in V3DfgPeephole.h, for example -fno-dfg-peephole-remove-not-not. The peephole patterns currently implemented were mostly picked based on the design that inspired this work, and on that design the optimizations yields ~30% single threaded speedup, and ~50% speedup on 4 threads. As you can imagine not having to haul around redundant combinational networks in the rest of the compilation pipeline also helps with memory consumption, and up to 30% peak memory usage of Verilator was observed on the same design. Gains on other arbitrary designs are smaller (and can be improved by analyzing those designs). For example OpenTitan gains between 1-15% speedup depending on build type.
2022-09-23 17:46:22 +02:00
AstVar* const varp = varVtxp->varp();
DFG: Improve .dot dumps slightly
2022-09-30 17:19:21 +02:00
os << toDotId(vtx);
Introduce DFG based combinational logic optimizer (#3527) Added a new data-flow graph (DFG) based combinational logic optimizer. The capabilities of this covers a combination of V3Const and V3Gate, but is also more capable of transforming combinational logic into simplified forms and more. This entail adding a new internal representation, `DfgGraph`, and appropriate `astToDfg` and `dfgToAst` conversion functions. The graph represents some of the combinational equations (~continuous assignments) in a module, and for the duration of the DFG passes, it takes over the role of AstModule. A bulk of the Dfg vertices represent expressions. These vertex classes, and the corresponding conversions to/from AST are mostly auto-generated by astgen, together with a DfgVVisitor that can be used for dynamic dispatch based on vertex (operation) types. The resulting combinational logic graph (a `DfgGraph`) is then optimized in various ways. Currently we perform common sub-expression elimination, variable inlining, and some specific peephole optimizations, but there is scope for more optimizations in the future using the same representation. The optimizer is run directly before and after inlining. The pre inline pass can operate on smaller graphs and hence converges faster, but still has a chance of substantially reducing the size of the logic on some designs, making inlining both faster and less memory intensive. The post inline pass can then optimize across the inlined module boundaries. No optimization is performed across a module boundary. For debugging purposes, each peephole optimization can be disabled individually via the -fno-dfg-peepnole-<OPT> option, where <OPT> is one of the optimizations listed in V3DfgPeephole.h, for example -fno-dfg-peephole-remove-not-not. The peephole patterns currently implemented were mostly picked based on the design that inspired this work, and on that design the optimizations yields ~30% single threaded speedup, and ~50% speedup on 4 threads. As you can imagine not having to haul around redundant combinational networks in the rest of the compilation pipeline also helps with memory consumption, and up to 30% peak memory usage of Verilator was observed on the same design. Gains on other arbitrary designs are smaller (and can be improved by analyzing those designs). For example OpenTitan gains between 1-15% speedup depending on build type.
2022-09-23 17:46:22 +02:00
os << " [label=\"" << varp->name() << "\nW" << varVtxp->width() << " / F"
<< varVtxp->fanout() << '"';
DFG: Partial support for unpacked arrays Representation and Ast / Dfg conversions available, for element-wise access only. Not much optimization yet (only CSE).
2022-09-27 01:06:50 +02:00
if (varp->direction() == VDirection::INPUT) {
os << ", shape=box, style=filled, fillcolor=chartreuse2"; // Green
} else if (varp->direction() == VDirection::OUTPUT) {
os << ", shape=box, style=filled, fillcolor=cyan2"; // Cyan
} else if (varp->direction() == VDirection::INOUT) {
os << ", shape=box, style=filled, fillcolor=darkorchid2"; // Purple
Introduce DFG based combinational logic optimizer (#3527) Added a new data-flow graph (DFG) based combinational logic optimizer. The capabilities of this covers a combination of V3Const and V3Gate, but is also more capable of transforming combinational logic into simplified forms and more. This entail adding a new internal representation, `DfgGraph`, and appropriate `astToDfg` and `dfgToAst` conversion functions. The graph represents some of the combinational equations (~continuous assignments) in a module, and for the duration of the DFG passes, it takes over the role of AstModule. A bulk of the Dfg vertices represent expressions. These vertex classes, and the corresponding conversions to/from AST are mostly auto-generated by astgen, together with a DfgVVisitor that can be used for dynamic dispatch based on vertex (operation) types. The resulting combinational logic graph (a `DfgGraph`) is then optimized in various ways. Currently we perform common sub-expression elimination, variable inlining, and some specific peephole optimizations, but there is scope for more optimizations in the future using the same representation. The optimizer is run directly before and after inlining. The pre inline pass can operate on smaller graphs and hence converges faster, but still has a chance of substantially reducing the size of the logic on some designs, making inlining both faster and less memory intensive. The post inline pass can then optimize across the inlined module boundaries. No optimization is performed across a module boundary. For debugging purposes, each peephole optimization can be disabled individually via the -fno-dfg-peepnole-<OPT> option, where <OPT> is one of the optimizations listed in V3DfgPeephole.h, for example -fno-dfg-peephole-remove-not-not. The peephole patterns currently implemented were mostly picked based on the design that inspired this work, and on that design the optimizations yields ~30% single threaded speedup, and ~50% speedup on 4 threads. As you can imagine not having to haul around redundant combinational networks in the rest of the compilation pipeline also helps with memory consumption, and up to 30% peak memory usage of Verilator was observed on the same design. Gains on other arbitrary designs are smaller (and can be improved by analyzing those designs). For example OpenTitan gains between 1-15% speedup depending on build type.
2022-09-23 17:46:22 +02:00
} else if (varVtxp->hasExtRefs()) {
DFG: Partial support for unpacked arrays Representation and Ast / Dfg conversions available, for element-wise access only. Not much optimization yet (only CSE).
2022-09-27 01:06:50 +02:00
os << ", shape=box, style=filled, fillcolor=firebrick2"; // Red
Introduce DFG based combinational logic optimizer (#3527) Added a new data-flow graph (DFG) based combinational logic optimizer. The capabilities of this covers a combination of V3Const and V3Gate, but is also more capable of transforming combinational logic into simplified forms and more. This entail adding a new internal representation, `DfgGraph`, and appropriate `astToDfg` and `dfgToAst` conversion functions. The graph represents some of the combinational equations (~continuous assignments) in a module, and for the duration of the DFG passes, it takes over the role of AstModule. A bulk of the Dfg vertices represent expressions. These vertex classes, and the corresponding conversions to/from AST are mostly auto-generated by astgen, together with a DfgVVisitor that can be used for dynamic dispatch based on vertex (operation) types. The resulting combinational logic graph (a `DfgGraph`) is then optimized in various ways. Currently we perform common sub-expression elimination, variable inlining, and some specific peephole optimizations, but there is scope for more optimizations in the future using the same representation. The optimizer is run directly before and after inlining. The pre inline pass can operate on smaller graphs and hence converges faster, but still has a chance of substantially reducing the size of the logic on some designs, making inlining both faster and less memory intensive. The post inline pass can then optimize across the inlined module boundaries. No optimization is performed across a module boundary. For debugging purposes, each peephole optimization can be disabled individually via the -fno-dfg-peepnole-<OPT> option, where <OPT> is one of the optimizations listed in V3DfgPeephole.h, for example -fno-dfg-peephole-remove-not-not. The peephole patterns currently implemented were mostly picked based on the design that inspired this work, and on that design the optimizations yields ~30% single threaded speedup, and ~50% speedup on 4 threads. As you can imagine not having to haul around redundant combinational networks in the rest of the compilation pipeline also helps with memory consumption, and up to 30% peak memory usage of Verilator was observed on the same design. Gains on other arbitrary designs are smaller (and can be improved by analyzing those designs). For example OpenTitan gains between 1-15% speedup depending on build type.
2022-09-23 17:46:22 +02:00
} else if (varVtxp->hasModRefs()) {
Add DFG 'regularize' pass, and improve variable removal (#4937) This functionality used to be distributed in the removeVars pass and the final dfgToAst conversion. Instead added a new 'regularize' pass to convert DFGs into forms that can be trivially converted back to Ast, and a new 'eliminateVars' pass to remove/repalce redundant variables. This simplifies dfgToAst significantly and makes the code a bit easier to follow. The new 'regularize' pass will ensure that every sub-expression with multiple uses is assigned to a temporary (unless it's a trivial memory reference or constant), and will also eliminate or replace redundant variables. Overall it is a performance neutral change but it does enable some later improvements which required the graph to be in this form, and this also happens to be the form required for the dfgToAst conversion.
2024-03-02 20:49:29 +01:00
os << ", shape=box, style=filled, fillcolor=darkorange1"; // Orange
} else if (varVtxp->hasDfgRefs()) {
DFG: Partial support for unpacked arrays Representation and Ast / Dfg conversions available, for element-wise access only. Not much optimization yet (only CSE).
2022-09-27 01:06:50 +02:00
os << ", shape=box, style=filled, fillcolor=gold2"; // Yellow
} else if (varVtxp->keep()) {
os << ", shape=box, style=filled, fillcolor=grey";
Introduce DFG based combinational logic optimizer (#3527) Added a new data-flow graph (DFG) based combinational logic optimizer. The capabilities of this covers a combination of V3Const and V3Gate, but is also more capable of transforming combinational logic into simplified forms and more. This entail adding a new internal representation, `DfgGraph`, and appropriate `astToDfg` and `dfgToAst` conversion functions. The graph represents some of the combinational equations (~continuous assignments) in a module, and for the duration of the DFG passes, it takes over the role of AstModule. A bulk of the Dfg vertices represent expressions. These vertex classes, and the corresponding conversions to/from AST are mostly auto-generated by astgen, together with a DfgVVisitor that can be used for dynamic dispatch based on vertex (operation) types. The resulting combinational logic graph (a `DfgGraph`) is then optimized in various ways. Currently we perform common sub-expression elimination, variable inlining, and some specific peephole optimizations, but there is scope for more optimizations in the future using the same representation. The optimizer is run directly before and after inlining. The pre inline pass can operate on smaller graphs and hence converges faster, but still has a chance of substantially reducing the size of the logic on some designs, making inlining both faster and less memory intensive. The post inline pass can then optimize across the inlined module boundaries. No optimization is performed across a module boundary. For debugging purposes, each peephole optimization can be disabled individually via the -fno-dfg-peepnole-<OPT> option, where <OPT> is one of the optimizations listed in V3DfgPeephole.h, for example -fno-dfg-peephole-remove-not-not. The peephole patterns currently implemented were mostly picked based on the design that inspired this work, and on that design the optimizations yields ~30% single threaded speedup, and ~50% speedup on 4 threads. As you can imagine not having to haul around redundant combinational networks in the rest of the compilation pipeline also helps with memory consumption, and up to 30% peak memory usage of Verilator was observed on the same design. Gains on other arbitrary designs are smaller (and can be improved by analyzing those designs). For example OpenTitan gains between 1-15% speedup depending on build type.
2022-09-23 17:46:22 +02:00
} else {
os << ", shape=box";
}
Use newline instead of endl, for fewer stream flushes
2023-11-24 17:45:52 +01:00
os << "]\n";
DFG: Partial support for unpacked arrays Representation and Ast / Dfg conversions available, for element-wise access only. Not much optimization yet (only CSE).
2022-09-27 01:06:50 +02:00
return;
}
if (const DfgVarArray* const arrVtxp = vtx.cast<DfgVarArray>()) {
AstVar* const varp = arrVtxp->varp();
DFG: Improve .dot dumps slightly
2022-09-30 17:19:21 +02:00
const int elements = VN_AS(arrVtxp->dtypep(), UnpackArrayDType)->elementsConst();
os << toDotId(vtx);
os << " [label=\"" << varp->name() << "[" << elements << "]\"";
DFG: Partial support for unpacked arrays Representation and Ast / Dfg conversions available, for element-wise access only. Not much optimization yet (only CSE).
2022-09-27 01:06:50 +02:00
if (varp->direction() == VDirection::INPUT) {
os << ", shape=box3d, style=filled, fillcolor=chartreuse2"; // Green
} else if (varp->direction() == VDirection::OUTPUT) {
os << ", shape=box3d, style=filled, fillcolor=cyan2"; // Cyan
} else if (varp->direction() == VDirection::INOUT) {
os << ", shape=box3d, style=filled, fillcolor=darkorchid2"; // Purple
} else if (arrVtxp->hasExtRefs()) {
os << ", shape=box3d, style=filled, fillcolor=firebrick2"; // Red
} else if (arrVtxp->hasModRefs()) {
Add DFG 'regularize' pass, and improve variable removal (#4937) This functionality used to be distributed in the removeVars pass and the final dfgToAst conversion. Instead added a new 'regularize' pass to convert DFGs into forms that can be trivially converted back to Ast, and a new 'eliminateVars' pass to remove/repalce redundant variables. This simplifies dfgToAst significantly and makes the code a bit easier to follow. The new 'regularize' pass will ensure that every sub-expression with multiple uses is assigned to a temporary (unless it's a trivial memory reference or constant), and will also eliminate or replace redundant variables. Overall it is a performance neutral change but it does enable some later improvements which required the graph to be in this form, and this also happens to be the form required for the dfgToAst conversion.
2024-03-02 20:49:29 +01:00
os << ", shape=box3d, style=filled, fillcolor=darkorange1"; // Orange
} else if (arrVtxp->hasDfgRefs()) {
DFG: Partial support for unpacked arrays Representation and Ast / Dfg conversions available, for element-wise access only. Not much optimization yet (only CSE).
2022-09-27 01:06:50 +02:00
os << ", shape=box3d, style=filled, fillcolor=gold2"; // Yellow
} else if (arrVtxp->keep()) {
os << ", shape=box3d, style=filled, fillcolor=grey";
} else {
os << ", shape=box3d";
}
Use newline instead of endl, for fewer stream flushes
2023-11-24 17:45:52 +01:00
os << "]\n";
DFG: Partial support for unpacked arrays Representation and Ast / Dfg conversions available, for element-wise access only. Not much optimization yet (only CSE).
2022-09-27 01:06:50 +02:00
return;
}
if (const DfgConst* const constVtxp = vtx.cast<DfgConst>()) {
Make DfgConst hold V3Number directly Remove intermediary AstConst. No functional change intended.
2022-10-07 16:44:14 +02:00
const V3Number& num = constVtxp->num();
DFG: Improve .dot dumps slightly
2022-09-30 17:19:21 +02:00
os << toDotId(vtx);
Introduce DFG based combinational logic optimizer (#3527) Added a new data-flow graph (DFG) based combinational logic optimizer. The capabilities of this covers a combination of V3Const and V3Gate, but is also more capable of transforming combinational logic into simplified forms and more. This entail adding a new internal representation, `DfgGraph`, and appropriate `astToDfg` and `dfgToAst` conversion functions. The graph represents some of the combinational equations (~continuous assignments) in a module, and for the duration of the DFG passes, it takes over the role of AstModule. A bulk of the Dfg vertices represent expressions. These vertex classes, and the corresponding conversions to/from AST are mostly auto-generated by astgen, together with a DfgVVisitor that can be used for dynamic dispatch based on vertex (operation) types. The resulting combinational logic graph (a `DfgGraph`) is then optimized in various ways. Currently we perform common sub-expression elimination, variable inlining, and some specific peephole optimizations, but there is scope for more optimizations in the future using the same representation. The optimizer is run directly before and after inlining. The pre inline pass can operate on smaller graphs and hence converges faster, but still has a chance of substantially reducing the size of the logic on some designs, making inlining both faster and less memory intensive. The post inline pass can then optimize across the inlined module boundaries. No optimization is performed across a module boundary. For debugging purposes, each peephole optimization can be disabled individually via the -fno-dfg-peepnole-<OPT> option, where <OPT> is one of the optimizations listed in V3DfgPeephole.h, for example -fno-dfg-peephole-remove-not-not. The peephole patterns currently implemented were mostly picked based on the design that inspired this work, and on that design the optimizations yields ~30% single threaded speedup, and ~50% speedup on 4 threads. As you can imagine not having to haul around redundant combinational networks in the rest of the compilation pipeline also helps with memory consumption, and up to 30% peak memory usage of Verilator was observed on the same design. Gains on other arbitrary designs are smaller (and can be improved by analyzing those designs). For example OpenTitan gains between 1-15% speedup depending on build type.
2022-09-23 17:46:22 +02:00
os << " [label=\"";
if (num.width() <= 32 && !num.isSigned()) {
DFG: Improve .dot dumps slightly
2022-09-30 17:19:21 +02:00
os << constVtxp->width() << "'d" << num.toUInt() << "\n";
os << constVtxp->width() << "'h" << std::hex << num.toUInt() << std::dec;
Introduce DFG based combinational logic optimizer (#3527) Added a new data-flow graph (DFG) based combinational logic optimizer. The capabilities of this covers a combination of V3Const and V3Gate, but is also more capable of transforming combinational logic into simplified forms and more. This entail adding a new internal representation, `DfgGraph`, and appropriate `astToDfg` and `dfgToAst` conversion functions. The graph represents some of the combinational equations (~continuous assignments) in a module, and for the duration of the DFG passes, it takes over the role of AstModule. A bulk of the Dfg vertices represent expressions. These vertex classes, and the corresponding conversions to/from AST are mostly auto-generated by astgen, together with a DfgVVisitor that can be used for dynamic dispatch based on vertex (operation) types. The resulting combinational logic graph (a `DfgGraph`) is then optimized in various ways. Currently we perform common sub-expression elimination, variable inlining, and some specific peephole optimizations, but there is scope for more optimizations in the future using the same representation. The optimizer is run directly before and after inlining. The pre inline pass can operate on smaller graphs and hence converges faster, but still has a chance of substantially reducing the size of the logic on some designs, making inlining both faster and less memory intensive. The post inline pass can then optimize across the inlined module boundaries. No optimization is performed across a module boundary. For debugging purposes, each peephole optimization can be disabled individually via the -fno-dfg-peepnole-<OPT> option, where <OPT> is one of the optimizations listed in V3DfgPeephole.h, for example -fno-dfg-peephole-remove-not-not. The peephole patterns currently implemented were mostly picked based on the design that inspired this work, and on that design the optimizations yields ~30% single threaded speedup, and ~50% speedup on 4 threads. As you can imagine not having to haul around redundant combinational networks in the rest of the compilation pipeline also helps with memory consumption, and up to 30% peak memory usage of Verilator was observed on the same design. Gains on other arbitrary designs are smaller (and can be improved by analyzing those designs). For example OpenTitan gains between 1-15% speedup depending on build type.
2022-09-23 17:46:22 +02:00
} else {
os << num.ascii();
}
os << '"';
os << ", shape=plain";
Use newline instead of endl, for fewer stream flushes
2023-11-24 17:45:52 +01:00
os << "]\n";
DFG: Partial support for unpacked arrays Representation and Ast / Dfg conversions available, for element-wise access only. Not much optimization yet (only CSE).
2022-09-27 01:06:50 +02:00
return;
}
DFG: Improve .dot dumps slightly
2022-09-30 17:19:21 +02:00
if (const DfgSel* const selVtxp = vtx.cast<DfgSel>()) {
DFG: Special case representation of AstSel AstSel is a ternary node, but the 'widthp' is always constant and is hence redundant, and 'lsbp' is very often constant. As AstSel is fairly common, we special case as a DfgSel for the constant 'lsbp', and as 'DfgMux` for the non-constant 'lsbp'.
2022-10-06 19:34:18 +02:00
const uint32_t lsb = selVtxp->lsb();
const uint32_t msb = lsb + selVtxp->width() - 1;
os << toDotId(vtx);
os << " [label=\"SEL\n_[" << msb << ":" << lsb << "]\nW" << vtx.width() << " / F"
<< vtx.fanout() << '"';
if (vtx.hasMultipleSinks()) {
os << ", shape=doublecircle";
} else {
os << ", shape=circle";
DFG: Improve .dot dumps slightly
2022-09-30 17:19:21 +02:00
}
Use newline instead of endl, for fewer stream flushes
2023-11-24 17:45:52 +01:00
os << "]\n";
DFG: Special case representation of AstSel AstSel is a ternary node, but the 'widthp' is always constant and is hence redundant, and 'lsbp' is very often constant. As AstSel is fairly common, we special case as a DfgSel for the constant 'lsbp', and as 'DfgMux` for the non-constant 'lsbp'.
2022-10-06 19:34:18 +02:00
return;
DFG: Improve .dot dumps slightly
2022-09-30 17:19:21 +02:00
}
os << toDotId(vtx);
DFG: Partial support for unpacked arrays Representation and Ast / Dfg conversions available, for element-wise access only. Not much optimization yet (only CSE).
2022-09-27 01:06:50 +02:00
os << " [label=\"" << vtx.typeName() << "\nW" << vtx.width() << " / F" << vtx.fanout() << '"';
if (vtx.hasMultipleSinks()) {
os << ", shape=doublecircle";
Introduce DFG based combinational logic optimizer (#3527) Added a new data-flow graph (DFG) based combinational logic optimizer. The capabilities of this covers a combination of V3Const and V3Gate, but is also more capable of transforming combinational logic into simplified forms and more. This entail adding a new internal representation, `DfgGraph`, and appropriate `astToDfg` and `dfgToAst` conversion functions. The graph represents some of the combinational equations (~continuous assignments) in a module, and for the duration of the DFG passes, it takes over the role of AstModule. A bulk of the Dfg vertices represent expressions. These vertex classes, and the corresponding conversions to/from AST are mostly auto-generated by astgen, together with a DfgVVisitor that can be used for dynamic dispatch based on vertex (operation) types. The resulting combinational logic graph (a `DfgGraph`) is then optimized in various ways. Currently we perform common sub-expression elimination, variable inlining, and some specific peephole optimizations, but there is scope for more optimizations in the future using the same representation. The optimizer is run directly before and after inlining. The pre inline pass can operate on smaller graphs and hence converges faster, but still has a chance of substantially reducing the size of the logic on some designs, making inlining both faster and less memory intensive. The post inline pass can then optimize across the inlined module boundaries. No optimization is performed across a module boundary. For debugging purposes, each peephole optimization can be disabled individually via the -fno-dfg-peepnole-<OPT> option, where <OPT> is one of the optimizations listed in V3DfgPeephole.h, for example -fno-dfg-peephole-remove-not-not. The peephole patterns currently implemented were mostly picked based on the design that inspired this work, and on that design the optimizations yields ~30% single threaded speedup, and ~50% speedup on 4 threads. As you can imagine not having to haul around redundant combinational networks in the rest of the compilation pipeline also helps with memory consumption, and up to 30% peak memory usage of Verilator was observed on the same design. Gains on other arbitrary designs are smaller (and can be improved by analyzing those designs). For example OpenTitan gains between 1-15% speedup depending on build type.
2022-09-23 17:46:22 +02:00
} else {
DFG: Partial support for unpacked arrays Representation and Ast / Dfg conversions available, for element-wise access only. Not much optimization yet (only CSE).
2022-09-27 01:06:50 +02:00
os << ", shape=circle";
Introduce DFG based combinational logic optimizer (#3527) Added a new data-flow graph (DFG) based combinational logic optimizer. The capabilities of this covers a combination of V3Const and V3Gate, but is also more capable of transforming combinational logic into simplified forms and more. This entail adding a new internal representation, `DfgGraph`, and appropriate `astToDfg` and `dfgToAst` conversion functions. The graph represents some of the combinational equations (~continuous assignments) in a module, and for the duration of the DFG passes, it takes over the role of AstModule. A bulk of the Dfg vertices represent expressions. These vertex classes, and the corresponding conversions to/from AST are mostly auto-generated by astgen, together with a DfgVVisitor that can be used for dynamic dispatch based on vertex (operation) types. The resulting combinational logic graph (a `DfgGraph`) is then optimized in various ways. Currently we perform common sub-expression elimination, variable inlining, and some specific peephole optimizations, but there is scope for more optimizations in the future using the same representation. The optimizer is run directly before and after inlining. The pre inline pass can operate on smaller graphs and hence converges faster, but still has a chance of substantially reducing the size of the logic on some designs, making inlining both faster and less memory intensive. The post inline pass can then optimize across the inlined module boundaries. No optimization is performed across a module boundary. For debugging purposes, each peephole optimization can be disabled individually via the -fno-dfg-peepnole-<OPT> option, where <OPT> is one of the optimizations listed in V3DfgPeephole.h, for example -fno-dfg-peephole-remove-not-not. The peephole patterns currently implemented were mostly picked based on the design that inspired this work, and on that design the optimizations yields ~30% single threaded speedup, and ~50% speedup on 4 threads. As you can imagine not having to haul around redundant combinational networks in the rest of the compilation pipeline also helps with memory consumption, and up to 30% peak memory usage of Verilator was observed on the same design. Gains on other arbitrary designs are smaller (and can be improved by analyzing those designs). For example OpenTitan gains between 1-15% speedup depending on build type.
2022-09-23 17:46:22 +02:00
}
Use newline instead of endl, for fewer stream flushes
2023-11-24 17:45:52 +01:00
os << "]\n";
Introduce DFG based combinational logic optimizer (#3527) Added a new data-flow graph (DFG) based combinational logic optimizer. The capabilities of this covers a combination of V3Const and V3Gate, but is also more capable of transforming combinational logic into simplified forms and more. This entail adding a new internal representation, `DfgGraph`, and appropriate `astToDfg` and `dfgToAst` conversion functions. The graph represents some of the combinational equations (~continuous assignments) in a module, and for the duration of the DFG passes, it takes over the role of AstModule. A bulk of the Dfg vertices represent expressions. These vertex classes, and the corresponding conversions to/from AST are mostly auto-generated by astgen, together with a DfgVVisitor that can be used for dynamic dispatch based on vertex (operation) types. The resulting combinational logic graph (a `DfgGraph`) is then optimized in various ways. Currently we perform common sub-expression elimination, variable inlining, and some specific peephole optimizations, but there is scope for more optimizations in the future using the same representation. The optimizer is run directly before and after inlining. The pre inline pass can operate on smaller graphs and hence converges faster, but still has a chance of substantially reducing the size of the logic on some designs, making inlining both faster and less memory intensive. The post inline pass can then optimize across the inlined module boundaries. No optimization is performed across a module boundary. For debugging purposes, each peephole optimization can be disabled individually via the -fno-dfg-peepnole-<OPT> option, where <OPT> is one of the optimizations listed in V3DfgPeephole.h, for example -fno-dfg-peephole-remove-not-not. The peephole patterns currently implemented were mostly picked based on the design that inspired this work, and on that design the optimizations yields ~30% single threaded speedup, and ~50% speedup on 4 threads. As you can imagine not having to haul around redundant combinational networks in the rest of the compilation pipeline also helps with memory consumption, and up to 30% peak memory usage of Verilator was observed on the same design. Gains on other arbitrary designs are smaller (and can be improved by analyzing those designs). For example OpenTitan gains between 1-15% speedup depending on build type.
2022-09-23 17:46:22 +02:00
}
// Dump one DfgEdge in Graphviz format
static void dumpDotEdge(std::ostream& os, const DfgEdge& edge, const string& headlabel) {
os << toDotId(*edge.sourcep()) << " -> " << toDotId(*edge.sinkp());
if (!headlabel.empty()) os << " [headlabel=\"" << headlabel << "\"]";
Use newline instead of endl, for fewer stream flushes
2023-11-24 17:45:52 +01:00
os << "\n";
Introduce DFG based combinational logic optimizer (#3527) Added a new data-flow graph (DFG) based combinational logic optimizer. The capabilities of this covers a combination of V3Const and V3Gate, but is also more capable of transforming combinational logic into simplified forms and more. This entail adding a new internal representation, `DfgGraph`, and appropriate `astToDfg` and `dfgToAst` conversion functions. The graph represents some of the combinational equations (~continuous assignments) in a module, and for the duration of the DFG passes, it takes over the role of AstModule. A bulk of the Dfg vertices represent expressions. These vertex classes, and the corresponding conversions to/from AST are mostly auto-generated by astgen, together with a DfgVVisitor that can be used for dynamic dispatch based on vertex (operation) types. The resulting combinational logic graph (a `DfgGraph`) is then optimized in various ways. Currently we perform common sub-expression elimination, variable inlining, and some specific peephole optimizations, but there is scope for more optimizations in the future using the same representation. The optimizer is run directly before and after inlining. The pre inline pass can operate on smaller graphs and hence converges faster, but still has a chance of substantially reducing the size of the logic on some designs, making inlining both faster and less memory intensive. The post inline pass can then optimize across the inlined module boundaries. No optimization is performed across a module boundary. For debugging purposes, each peephole optimization can be disabled individually via the -fno-dfg-peepnole-<OPT> option, where <OPT> is one of the optimizations listed in V3DfgPeephole.h, for example -fno-dfg-peephole-remove-not-not. The peephole patterns currently implemented were mostly picked based on the design that inspired this work, and on that design the optimizations yields ~30% single threaded speedup, and ~50% speedup on 4 threads. As you can imagine not having to haul around redundant combinational networks in the rest of the compilation pipeline also helps with memory consumption, and up to 30% peak memory usage of Verilator was observed on the same design. Gains on other arbitrary designs are smaller (and can be improved by analyzing those designs). For example OpenTitan gains between 1-15% speedup depending on build type.
2022-09-23 17:46:22 +02:00
}
// Dump one DfgVertex and all of its source DfgEdges in Graphviz format
static void dumpDotVertexAndSourceEdges(std::ostream& os, const DfgVertex& vtx) {
dumpDotVertex(os, vtx);
vtx.forEachSourceEdge([&](const DfgEdge& edge, size_t idx) { //
if (edge.sourcep()) {
string headLabel;
DFG: Make implementation more similar to AST Use the same style, and reuse the bulk of astgen to generate DfgVertex related code. In particular allow for easier definition of custom DfgVertex sub-types that do not directly correspond to an AstNode sub-type. Also introduces specific names for the fixed arity vertices. No functional change intended.
2022-10-04 12:03:41 +02:00
if (vtx.arity() > 1 || vtx.is<DfgVertexVar>()) headLabel = vtx.srcName(idx);
Introduce DFG based combinational logic optimizer (#3527) Added a new data-flow graph (DFG) based combinational logic optimizer. The capabilities of this covers a combination of V3Const and V3Gate, but is also more capable of transforming combinational logic into simplified forms and more. This entail adding a new internal representation, `DfgGraph`, and appropriate `astToDfg` and `dfgToAst` conversion functions. The graph represents some of the combinational equations (~continuous assignments) in a module, and for the duration of the DFG passes, it takes over the role of AstModule. A bulk of the Dfg vertices represent expressions. These vertex classes, and the corresponding conversions to/from AST are mostly auto-generated by astgen, together with a DfgVVisitor that can be used for dynamic dispatch based on vertex (operation) types. The resulting combinational logic graph (a `DfgGraph`) is then optimized in various ways. Currently we perform common sub-expression elimination, variable inlining, and some specific peephole optimizations, but there is scope for more optimizations in the future using the same representation. The optimizer is run directly before and after inlining. The pre inline pass can operate on smaller graphs and hence converges faster, but still has a chance of substantially reducing the size of the logic on some designs, making inlining both faster and less memory intensive. The post inline pass can then optimize across the inlined module boundaries. No optimization is performed across a module boundary. For debugging purposes, each peephole optimization can be disabled individually via the -fno-dfg-peepnole-<OPT> option, where <OPT> is one of the optimizations listed in V3DfgPeephole.h, for example -fno-dfg-peephole-remove-not-not. The peephole patterns currently implemented were mostly picked based on the design that inspired this work, and on that design the optimizations yields ~30% single threaded speedup, and ~50% speedup on 4 threads. As you can imagine not having to haul around redundant combinational networks in the rest of the compilation pipeline also helps with memory consumption, and up to 30% peak memory usage of Verilator was observed on the same design. Gains on other arbitrary designs are smaller (and can be improved by analyzing those designs). For example OpenTitan gains between 1-15% speedup depending on build type.
2022-09-23 17:46:22 +02:00
dumpDotEdge(os, edge, headLabel);
}
});
}
void DfgGraph::dumpDot(std::ostream& os, const string& label) const {
// Header
Use newline instead of endl, for fewer stream flushes
2023-11-24 17:45:52 +01:00
os << "digraph dfg {\n";
Introduce DFG based combinational logic optimizer (#3527) Added a new data-flow graph (DFG) based combinational logic optimizer. The capabilities of this covers a combination of V3Const and V3Gate, but is also more capable of transforming combinational logic into simplified forms and more. This entail adding a new internal representation, `DfgGraph`, and appropriate `astToDfg` and `dfgToAst` conversion functions. The graph represents some of the combinational equations (~continuous assignments) in a module, and for the duration of the DFG passes, it takes over the role of AstModule. A bulk of the Dfg vertices represent expressions. These vertex classes, and the corresponding conversions to/from AST are mostly auto-generated by astgen, together with a DfgVVisitor that can be used for dynamic dispatch based on vertex (operation) types. The resulting combinational logic graph (a `DfgGraph`) is then optimized in various ways. Currently we perform common sub-expression elimination, variable inlining, and some specific peephole optimizations, but there is scope for more optimizations in the future using the same representation. The optimizer is run directly before and after inlining. The pre inline pass can operate on smaller graphs and hence converges faster, but still has a chance of substantially reducing the size of the logic on some designs, making inlining both faster and less memory intensive. The post inline pass can then optimize across the inlined module boundaries. No optimization is performed across a module boundary. For debugging purposes, each peephole optimization can be disabled individually via the -fno-dfg-peepnole-<OPT> option, where <OPT> is one of the optimizations listed in V3DfgPeephole.h, for example -fno-dfg-peephole-remove-not-not. The peephole patterns currently implemented were mostly picked based on the design that inspired this work, and on that design the optimizations yields ~30% single threaded speedup, and ~50% speedup on 4 threads. As you can imagine not having to haul around redundant combinational networks in the rest of the compilation pipeline also helps with memory consumption, and up to 30% peak memory usage of Verilator was observed on the same design. Gains on other arbitrary designs are smaller (and can be improved by analyzing those designs). For example OpenTitan gains between 1-15% speedup depending on build type.
2022-09-23 17:46:22 +02:00
os << "graph [label=\"" << name();
if (!label.empty()) os << "-" << label;
Use newline instead of endl, for fewer stream flushes
2023-11-24 17:45:52 +01:00
os << "\", labelloc=t, labeljust=l]\n";
os << "graph [rankdir=LR]\n";
Introduce DFG based combinational logic optimizer (#3527) Added a new data-flow graph (DFG) based combinational logic optimizer. The capabilities of this covers a combination of V3Const and V3Gate, but is also more capable of transforming combinational logic into simplified forms and more. This entail adding a new internal representation, `DfgGraph`, and appropriate `astToDfg` and `dfgToAst` conversion functions. The graph represents some of the combinational equations (~continuous assignments) in a module, and for the duration of the DFG passes, it takes over the role of AstModule. A bulk of the Dfg vertices represent expressions. These vertex classes, and the corresponding conversions to/from AST are mostly auto-generated by astgen, together with a DfgVVisitor that can be used for dynamic dispatch based on vertex (operation) types. The resulting combinational logic graph (a `DfgGraph`) is then optimized in various ways. Currently we perform common sub-expression elimination, variable inlining, and some specific peephole optimizations, but there is scope for more optimizations in the future using the same representation. The optimizer is run directly before and after inlining. The pre inline pass can operate on smaller graphs and hence converges faster, but still has a chance of substantially reducing the size of the logic on some designs, making inlining both faster and less memory intensive. The post inline pass can then optimize across the inlined module boundaries. No optimization is performed across a module boundary. For debugging purposes, each peephole optimization can be disabled individually via the -fno-dfg-peepnole-<OPT> option, where <OPT> is one of the optimizations listed in V3DfgPeephole.h, for example -fno-dfg-peephole-remove-not-not. The peephole patterns currently implemented were mostly picked based on the design that inspired this work, and on that design the optimizations yields ~30% single threaded speedup, and ~50% speedup on 4 threads. As you can imagine not having to haul around redundant combinational networks in the rest of the compilation pipeline also helps with memory consumption, and up to 30% peak memory usage of Verilator was observed on the same design. Gains on other arbitrary designs are smaller (and can be improved by analyzing those designs). For example OpenTitan gains between 1-15% speedup depending on build type.
2022-09-23 17:46:22 +02:00
// Emit all vertices
forEachVertex([&](const DfgVertex& vtx) { dumpDotVertexAndSourceEdges(os, vtx); });
// Footer
Use newline instead of endl, for fewer stream flushes
2023-11-24 17:45:52 +01:00
os << "}\n";
Introduce DFG based combinational logic optimizer (#3527) Added a new data-flow graph (DFG) based combinational logic optimizer. The capabilities of this covers a combination of V3Const and V3Gate, but is also more capable of transforming combinational logic into simplified forms and more. This entail adding a new internal representation, `DfgGraph`, and appropriate `astToDfg` and `dfgToAst` conversion functions. The graph represents some of the combinational equations (~continuous assignments) in a module, and for the duration of the DFG passes, it takes over the role of AstModule. A bulk of the Dfg vertices represent expressions. These vertex classes, and the corresponding conversions to/from AST are mostly auto-generated by astgen, together with a DfgVVisitor that can be used for dynamic dispatch based on vertex (operation) types. The resulting combinational logic graph (a `DfgGraph`) is then optimized in various ways. Currently we perform common sub-expression elimination, variable inlining, and some specific peephole optimizations, but there is scope for more optimizations in the future using the same representation. The optimizer is run directly before and after inlining. The pre inline pass can operate on smaller graphs and hence converges faster, but still has a chance of substantially reducing the size of the logic on some designs, making inlining both faster and less memory intensive. The post inline pass can then optimize across the inlined module boundaries. No optimization is performed across a module boundary. For debugging purposes, each peephole optimization can be disabled individually via the -fno-dfg-peepnole-<OPT> option, where <OPT> is one of the optimizations listed in V3DfgPeephole.h, for example -fno-dfg-peephole-remove-not-not. The peephole patterns currently implemented were mostly picked based on the design that inspired this work, and on that design the optimizations yields ~30% single threaded speedup, and ~50% speedup on 4 threads. As you can imagine not having to haul around redundant combinational networks in the rest of the compilation pipeline also helps with memory consumption, and up to 30% peak memory usage of Verilator was observed on the same design. Gains on other arbitrary designs are smaller (and can be improved by analyzing those designs). For example OpenTitan gains between 1-15% speedup depending on build type.
2022-09-23 17:46:22 +02:00
}
Internals: Rename some filename functions. No functional change.
2024-07-14 15:34:54 +02:00
void DfgGraph::dumpDotFile(const string& filename, const string& label) const {
Introduce DFG based combinational logic optimizer (#3527) Added a new data-flow graph (DFG) based combinational logic optimizer. The capabilities of this covers a combination of V3Const and V3Gate, but is also more capable of transforming combinational logic into simplified forms and more. This entail adding a new internal representation, `DfgGraph`, and appropriate `astToDfg` and `dfgToAst` conversion functions. The graph represents some of the combinational equations (~continuous assignments) in a module, and for the duration of the DFG passes, it takes over the role of AstModule. A bulk of the Dfg vertices represent expressions. These vertex classes, and the corresponding conversions to/from AST are mostly auto-generated by astgen, together with a DfgVVisitor that can be used for dynamic dispatch based on vertex (operation) types. The resulting combinational logic graph (a `DfgGraph`) is then optimized in various ways. Currently we perform common sub-expression elimination, variable inlining, and some specific peephole optimizations, but there is scope for more optimizations in the future using the same representation. The optimizer is run directly before and after inlining. The pre inline pass can operate on smaller graphs and hence converges faster, but still has a chance of substantially reducing the size of the logic on some designs, making inlining both faster and less memory intensive. The post inline pass can then optimize across the inlined module boundaries. No optimization is performed across a module boundary. For debugging purposes, each peephole optimization can be disabled individually via the -fno-dfg-peepnole-<OPT> option, where <OPT> is one of the optimizations listed in V3DfgPeephole.h, for example -fno-dfg-peephole-remove-not-not. The peephole patterns currently implemented were mostly picked based on the design that inspired this work, and on that design the optimizations yields ~30% single threaded speedup, and ~50% speedup on 4 threads. As you can imagine not having to haul around redundant combinational networks in the rest of the compilation pipeline also helps with memory consumption, and up to 30% peak memory usage of Verilator was observed on the same design. Gains on other arbitrary designs are smaller (and can be improved by analyzing those designs). For example OpenTitan gains between 1-15% speedup depending on build type.
2022-09-23 17:46:22 +02:00
// This generates a file used by graphviz, https://www.graphviz.org
// "hardcoded" parameters:
Internals: Rename some filename functions. No functional change.
2024-07-14 15:34:54 +02:00
const std::unique_ptr<std::ofstream> os{V3File::new_ofstream(filename)};
if (os->fail()) v3fatal("Cannot write to file: " << filename);
Introduce DFG based combinational logic optimizer (#3527) Added a new data-flow graph (DFG) based combinational logic optimizer. The capabilities of this covers a combination of V3Const and V3Gate, but is also more capable of transforming combinational logic into simplified forms and more. This entail adding a new internal representation, `DfgGraph`, and appropriate `astToDfg` and `dfgToAst` conversion functions. The graph represents some of the combinational equations (~continuous assignments) in a module, and for the duration of the DFG passes, it takes over the role of AstModule. A bulk of the Dfg vertices represent expressions. These vertex classes, and the corresponding conversions to/from AST are mostly auto-generated by astgen, together with a DfgVVisitor that can be used for dynamic dispatch based on vertex (operation) types. The resulting combinational logic graph (a `DfgGraph`) is then optimized in various ways. Currently we perform common sub-expression elimination, variable inlining, and some specific peephole optimizations, but there is scope for more optimizations in the future using the same representation. The optimizer is run directly before and after inlining. The pre inline pass can operate on smaller graphs and hence converges faster, but still has a chance of substantially reducing the size of the logic on some designs, making inlining both faster and less memory intensive. The post inline pass can then optimize across the inlined module boundaries. No optimization is performed across a module boundary. For debugging purposes, each peephole optimization can be disabled individually via the -fno-dfg-peepnole-<OPT> option, where <OPT> is one of the optimizations listed in V3DfgPeephole.h, for example -fno-dfg-peephole-remove-not-not. The peephole patterns currently implemented were mostly picked based on the design that inspired this work, and on that design the optimizations yields ~30% single threaded speedup, and ~50% speedup on 4 threads. As you can imagine not having to haul around redundant combinational networks in the rest of the compilation pipeline also helps with memory consumption, and up to 30% peak memory usage of Verilator was observed on the same design. Gains on other arbitrary designs are smaller (and can be improved by analyzing those designs). For example OpenTitan gains between 1-15% speedup depending on build type.
2022-09-23 17:46:22 +02:00
dumpDot(*os.get(), label);
os->close();
}
void DfgGraph::dumpDotFilePrefixed(const string& label) const {
Internals: Rename some filename functions. No functional change.
2024-07-14 15:34:54 +02:00
string filename = name();
if (!label.empty()) filename += "-" + label;
dumpDotFile(v3Global.debugFilename(filename) + ".dot", label);
Introduce DFG based combinational logic optimizer (#3527) Added a new data-flow graph (DFG) based combinational logic optimizer. The capabilities of this covers a combination of V3Const and V3Gate, but is also more capable of transforming combinational logic into simplified forms and more. This entail adding a new internal representation, `DfgGraph`, and appropriate `astToDfg` and `dfgToAst` conversion functions. The graph represents some of the combinational equations (~continuous assignments) in a module, and for the duration of the DFG passes, it takes over the role of AstModule. A bulk of the Dfg vertices represent expressions. These vertex classes, and the corresponding conversions to/from AST are mostly auto-generated by astgen, together with a DfgVVisitor that can be used for dynamic dispatch based on vertex (operation) types. The resulting combinational logic graph (a `DfgGraph`) is then optimized in various ways. Currently we perform common sub-expression elimination, variable inlining, and some specific peephole optimizations, but there is scope for more optimizations in the future using the same representation. The optimizer is run directly before and after inlining. The pre inline pass can operate on smaller graphs and hence converges faster, but still has a chance of substantially reducing the size of the logic on some designs, making inlining both faster and less memory intensive. The post inline pass can then optimize across the inlined module boundaries. No optimization is performed across a module boundary. For debugging purposes, each peephole optimization can be disabled individually via the -fno-dfg-peepnole-<OPT> option, where <OPT> is one of the optimizations listed in V3DfgPeephole.h, for example -fno-dfg-peephole-remove-not-not. The peephole patterns currently implemented were mostly picked based on the design that inspired this work, and on that design the optimizations yields ~30% single threaded speedup, and ~50% speedup on 4 threads. As you can imagine not having to haul around redundant combinational networks in the rest of the compilation pipeline also helps with memory consumption, and up to 30% peak memory usage of Verilator was observed on the same design. Gains on other arbitrary designs are smaller (and can be improved by analyzing those designs). For example OpenTitan gains between 1-15% speedup depending on build type.
2022-09-23 17:46:22 +02:00
}
// Dump upstream logic cone starting from given vertex
static void dumpDotUpstreamConeFromVertex(std::ostream& os, const DfgVertex& vtx) {
// Work queue for depth first traversal starting from this vertex
std::vector<const DfgVertex*> queue{&vtx};
// Set of already visited vertices
std::unordered_set<const DfgVertex*> visited;
// Depth first traversal
while (!queue.empty()) {
// Pop next work item
const DfgVertex* const itemp = queue.back();
queue.pop_back();
// Mark vertex as visited
const bool isFirstEncounter = visited.insert(itemp).second;
// If we have already visited this vertex during the traversal, then move on.
if (!isFirstEncounter) continue;
// Enqueue all sources of this vertex.
itemp->forEachSource([&](const DfgVertex& src) { queue.push_back(&src); });
// Emit this vertex and all of its source edges
dumpDotVertexAndSourceEdges(os, *itemp);
}
DFG: Partial support for unpacked arrays Representation and Ast / Dfg conversions available, for element-wise access only. Not much optimization yet (only CSE).
2022-09-27 01:06:50 +02:00
// Emit all DfgVarPacked vertices that have external references driven by this vertex
Introduce DFG based combinational logic optimizer (#3527) Added a new data-flow graph (DFG) based combinational logic optimizer. The capabilities of this covers a combination of V3Const and V3Gate, but is also more capable of transforming combinational logic into simplified forms and more. This entail adding a new internal representation, `DfgGraph`, and appropriate `astToDfg` and `dfgToAst` conversion functions. The graph represents some of the combinational equations (~continuous assignments) in a module, and for the duration of the DFG passes, it takes over the role of AstModule. A bulk of the Dfg vertices represent expressions. These vertex classes, and the corresponding conversions to/from AST are mostly auto-generated by astgen, together with a DfgVVisitor that can be used for dynamic dispatch based on vertex (operation) types. The resulting combinational logic graph (a `DfgGraph`) is then optimized in various ways. Currently we perform common sub-expression elimination, variable inlining, and some specific peephole optimizations, but there is scope for more optimizations in the future using the same representation. The optimizer is run directly before and after inlining. The pre inline pass can operate on smaller graphs and hence converges faster, but still has a chance of substantially reducing the size of the logic on some designs, making inlining both faster and less memory intensive. The post inline pass can then optimize across the inlined module boundaries. No optimization is performed across a module boundary. For debugging purposes, each peephole optimization can be disabled individually via the -fno-dfg-peepnole-<OPT> option, where <OPT> is one of the optimizations listed in V3DfgPeephole.h, for example -fno-dfg-peephole-remove-not-not. The peephole patterns currently implemented were mostly picked based on the design that inspired this work, and on that design the optimizations yields ~30% single threaded speedup, and ~50% speedup on 4 threads. As you can imagine not having to haul around redundant combinational networks in the rest of the compilation pipeline also helps with memory consumption, and up to 30% peak memory usage of Verilator was observed on the same design. Gains on other arbitrary designs are smaller (and can be improved by analyzing those designs). For example OpenTitan gains between 1-15% speedup depending on build type.
2022-09-23 17:46:22 +02:00
vtx.forEachSink([&](const DfgVertex& dst) {
DFG: Partial support for unpacked arrays Representation and Ast / Dfg conversions available, for element-wise access only. Not much optimization yet (only CSE).
2022-09-27 01:06:50 +02:00
if (const DfgVarPacked* const varVtxp = dst.cast<DfgVarPacked>()) {
Add DFG 'regularize' pass, and improve variable removal (#4937) This functionality used to be distributed in the removeVars pass and the final dfgToAst conversion. Instead added a new 'regularize' pass to convert DFGs into forms that can be trivially converted back to Ast, and a new 'eliminateVars' pass to remove/repalce redundant variables. This simplifies dfgToAst significantly and makes the code a bit easier to follow. The new 'regularize' pass will ensure that every sub-expression with multiple uses is assigned to a temporary (unless it's a trivial memory reference or constant), and will also eliminate or replace redundant variables. Overall it is a performance neutral change but it does enable some later improvements which required the graph to be in this form, and this also happens to be the form required for the dfgToAst conversion.
2024-03-02 20:49:29 +01:00
if (varVtxp->hasNonLocalRefs()) dumpDotVertexAndSourceEdges(os, dst);
Introduce DFG based combinational logic optimizer (#3527) Added a new data-flow graph (DFG) based combinational logic optimizer. The capabilities of this covers a combination of V3Const and V3Gate, but is also more capable of transforming combinational logic into simplified forms and more. This entail adding a new internal representation, `DfgGraph`, and appropriate `astToDfg` and `dfgToAst` conversion functions. The graph represents some of the combinational equations (~continuous assignments) in a module, and for the duration of the DFG passes, it takes over the role of AstModule. A bulk of the Dfg vertices represent expressions. These vertex classes, and the corresponding conversions to/from AST are mostly auto-generated by astgen, together with a DfgVVisitor that can be used for dynamic dispatch based on vertex (operation) types. The resulting combinational logic graph (a `DfgGraph`) is then optimized in various ways. Currently we perform common sub-expression elimination, variable inlining, and some specific peephole optimizations, but there is scope for more optimizations in the future using the same representation. The optimizer is run directly before and after inlining. The pre inline pass can operate on smaller graphs and hence converges faster, but still has a chance of substantially reducing the size of the logic on some designs, making inlining both faster and less memory intensive. The post inline pass can then optimize across the inlined module boundaries. No optimization is performed across a module boundary. For debugging purposes, each peephole optimization can be disabled individually via the -fno-dfg-peepnole-<OPT> option, where <OPT> is one of the optimizations listed in V3DfgPeephole.h, for example -fno-dfg-peephole-remove-not-not. The peephole patterns currently implemented were mostly picked based on the design that inspired this work, and on that design the optimizations yields ~30% single threaded speedup, and ~50% speedup on 4 threads. As you can imagine not having to haul around redundant combinational networks in the rest of the compilation pipeline also helps with memory consumption, and up to 30% peak memory usage of Verilator was observed on the same design. Gains on other arbitrary designs are smaller (and can be improved by analyzing those designs). For example OpenTitan gains between 1-15% speedup depending on build type.
2022-09-23 17:46:22 +02:00
}
});
}
// LCOV_EXCL_START // Debug function for developer use only
void DfgGraph::dumpDotUpstreamCone(const string& fileName, const DfgVertex& vtx,
const string& name) const {
// Open output file
const std::unique_ptr<std::ofstream> os{V3File::new_ofstream(fileName)};
if (os->fail()) v3fatal("Cannot write to file: " << fileName);
// Header
Use newline instead of endl, for fewer stream flushes
2023-11-24 17:45:52 +01:00
*os << "digraph dfg {\n";
if (!name.empty()) *os << "graph [label=\"" << name << "\", labelloc=t, labeljust=l]\n";
*os << "graph [rankdir=LR]\n";
Introduce DFG based combinational logic optimizer (#3527) Added a new data-flow graph (DFG) based combinational logic optimizer. The capabilities of this covers a combination of V3Const and V3Gate, but is also more capable of transforming combinational logic into simplified forms and more. This entail adding a new internal representation, `DfgGraph`, and appropriate `astToDfg` and `dfgToAst` conversion functions. The graph represents some of the combinational equations (~continuous assignments) in a module, and for the duration of the DFG passes, it takes over the role of AstModule. A bulk of the Dfg vertices represent expressions. These vertex classes, and the corresponding conversions to/from AST are mostly auto-generated by astgen, together with a DfgVVisitor that can be used for dynamic dispatch based on vertex (operation) types. The resulting combinational logic graph (a `DfgGraph`) is then optimized in various ways. Currently we perform common sub-expression elimination, variable inlining, and some specific peephole optimizations, but there is scope for more optimizations in the future using the same representation. The optimizer is run directly before and after inlining. The pre inline pass can operate on smaller graphs and hence converges faster, but still has a chance of substantially reducing the size of the logic on some designs, making inlining both faster and less memory intensive. The post inline pass can then optimize across the inlined module boundaries. No optimization is performed across a module boundary. For debugging purposes, each peephole optimization can be disabled individually via the -fno-dfg-peepnole-<OPT> option, where <OPT> is one of the optimizations listed in V3DfgPeephole.h, for example -fno-dfg-peephole-remove-not-not. The peephole patterns currently implemented were mostly picked based on the design that inspired this work, and on that design the optimizations yields ~30% single threaded speedup, and ~50% speedup on 4 threads. As you can imagine not having to haul around redundant combinational networks in the rest of the compilation pipeline also helps with memory consumption, and up to 30% peak memory usage of Verilator was observed on the same design. Gains on other arbitrary designs are smaller (and can be improved by analyzing those designs). For example OpenTitan gains between 1-15% speedup depending on build type.
2022-09-23 17:46:22 +02:00
// Dump the cone
dumpDotUpstreamConeFromVertex(*os, vtx);
// Footer
Use newline instead of endl, for fewer stream flushes
2023-11-24 17:45:52 +01:00
*os << "}\n";
Introduce DFG based combinational logic optimizer (#3527) Added a new data-flow graph (DFG) based combinational logic optimizer. The capabilities of this covers a combination of V3Const and V3Gate, but is also more capable of transforming combinational logic into simplified forms and more. This entail adding a new internal representation, `DfgGraph`, and appropriate `astToDfg` and `dfgToAst` conversion functions. The graph represents some of the combinational equations (~continuous assignments) in a module, and for the duration of the DFG passes, it takes over the role of AstModule. A bulk of the Dfg vertices represent expressions. These vertex classes, and the corresponding conversions to/from AST are mostly auto-generated by astgen, together with a DfgVVisitor that can be used for dynamic dispatch based on vertex (operation) types. The resulting combinational logic graph (a `DfgGraph`) is then optimized in various ways. Currently we perform common sub-expression elimination, variable inlining, and some specific peephole optimizations, but there is scope for more optimizations in the future using the same representation. The optimizer is run directly before and after inlining. The pre inline pass can operate on smaller graphs and hence converges faster, but still has a chance of substantially reducing the size of the logic on some designs, making inlining both faster and less memory intensive. The post inline pass can then optimize across the inlined module boundaries. No optimization is performed across a module boundary. For debugging purposes, each peephole optimization can be disabled individually via the -fno-dfg-peepnole-<OPT> option, where <OPT> is one of the optimizations listed in V3DfgPeephole.h, for example -fno-dfg-peephole-remove-not-not. The peephole patterns currently implemented were mostly picked based on the design that inspired this work, and on that design the optimizations yields ~30% single threaded speedup, and ~50% speedup on 4 threads. As you can imagine not having to haul around redundant combinational networks in the rest of the compilation pipeline also helps with memory consumption, and up to 30% peak memory usage of Verilator was observed on the same design. Gains on other arbitrary designs are smaller (and can be improved by analyzing those designs). For example OpenTitan gains between 1-15% speedup depending on build type.
2022-09-23 17:46:22 +02:00
// Done
os->close();
}
// LCOV_EXCL_STOP
void DfgGraph::dumpDotAllVarConesPrefixed(const string& label) const {
const string prefix = label.empty() ? name() + "-cone-" : name() + "-" + label + "-cone-";
forEachVertex([&](const DfgVertex& vtx) {
// Check if this vertex drives a variable referenced outside the DFG.
DFG: Partial support for unpacked arrays Representation and Ast / Dfg conversions available, for element-wise access only. Not much optimization yet (only CSE).
2022-09-27 01:06:50 +02:00
const DfgVarPacked* const sinkp
= vtx.findSink<DfgVarPacked>([](const DfgVarPacked& sink) { //
Add DFG 'regularize' pass, and improve variable removal (#4937) This functionality used to be distributed in the removeVars pass and the final dfgToAst conversion. Instead added a new 'regularize' pass to convert DFGs into forms that can be trivially converted back to Ast, and a new 'eliminateVars' pass to remove/repalce redundant variables. This simplifies dfgToAst significantly and makes the code a bit easier to follow. The new 'regularize' pass will ensure that every sub-expression with multiple uses is assigned to a temporary (unless it's a trivial memory reference or constant), and will also eliminate or replace redundant variables. Overall it is a performance neutral change but it does enable some later improvements which required the graph to be in this form, and this also happens to be the form required for the dfgToAst conversion.
2024-03-02 20:49:29 +01:00
return sink.hasNonLocalRefs();
DFG: Partial support for unpacked arrays Representation and Ast / Dfg conversions available, for element-wise access only. Not much optimization yet (only CSE).
2022-09-27 01:06:50 +02:00
});
Introduce DFG based combinational logic optimizer (#3527) Added a new data-flow graph (DFG) based combinational logic optimizer. The capabilities of this covers a combination of V3Const and V3Gate, but is also more capable of transforming combinational logic into simplified forms and more. This entail adding a new internal representation, `DfgGraph`, and appropriate `astToDfg` and `dfgToAst` conversion functions. The graph represents some of the combinational equations (~continuous assignments) in a module, and for the duration of the DFG passes, it takes over the role of AstModule. A bulk of the Dfg vertices represent expressions. These vertex classes, and the corresponding conversions to/from AST are mostly auto-generated by astgen, together with a DfgVVisitor that can be used for dynamic dispatch based on vertex (operation) types. The resulting combinational logic graph (a `DfgGraph`) is then optimized in various ways. Currently we perform common sub-expression elimination, variable inlining, and some specific peephole optimizations, but there is scope for more optimizations in the future using the same representation. The optimizer is run directly before and after inlining. The pre inline pass can operate on smaller graphs and hence converges faster, but still has a chance of substantially reducing the size of the logic on some designs, making inlining both faster and less memory intensive. The post inline pass can then optimize across the inlined module boundaries. No optimization is performed across a module boundary. For debugging purposes, each peephole optimization can be disabled individually via the -fno-dfg-peepnole-<OPT> option, where <OPT> is one of the optimizations listed in V3DfgPeephole.h, for example -fno-dfg-peephole-remove-not-not. The peephole patterns currently implemented were mostly picked based on the design that inspired this work, and on that design the optimizations yields ~30% single threaded speedup, and ~50% speedup on 4 threads. As you can imagine not having to haul around redundant combinational networks in the rest of the compilation pipeline also helps with memory consumption, and up to 30% peak memory usage of Verilator was observed on the same design. Gains on other arbitrary designs are smaller (and can be improved by analyzing those designs). For example OpenTitan gains between 1-15% speedup depending on build type.
2022-09-23 17:46:22 +02:00
// We only dump cones driving an externally referenced variable
if (!sinkp) return;
// Open output file
const string coneName{prefix + sinkp->varp()->name()};
const string fileName{v3Global.debugFilename(coneName) + ".dot"};
const std::unique_ptr<std::ofstream> os{V3File::new_ofstream(fileName)};
if (os->fail()) v3fatal("Cannot write to file: " << fileName);
// Header
Use newline instead of endl, for fewer stream flushes
2023-11-24 17:45:52 +01:00
*os << "digraph dfg {\n";
*os << "graph [label=\"" << coneName << "\", labelloc=t, labeljust=l]\n";
*os << "graph [rankdir=LR]\n";
Introduce DFG based combinational logic optimizer (#3527) Added a new data-flow graph (DFG) based combinational logic optimizer. The capabilities of this covers a combination of V3Const and V3Gate, but is also more capable of transforming combinational logic into simplified forms and more. This entail adding a new internal representation, `DfgGraph`, and appropriate `astToDfg` and `dfgToAst` conversion functions. The graph represents some of the combinational equations (~continuous assignments) in a module, and for the duration of the DFG passes, it takes over the role of AstModule. A bulk of the Dfg vertices represent expressions. These vertex classes, and the corresponding conversions to/from AST are mostly auto-generated by astgen, together with a DfgVVisitor that can be used for dynamic dispatch based on vertex (operation) types. The resulting combinational logic graph (a `DfgGraph`) is then optimized in various ways. Currently we perform common sub-expression elimination, variable inlining, and some specific peephole optimizations, but there is scope for more optimizations in the future using the same representation. The optimizer is run directly before and after inlining. The pre inline pass can operate on smaller graphs and hence converges faster, but still has a chance of substantially reducing the size of the logic on some designs, making inlining both faster and less memory intensive. The post inline pass can then optimize across the inlined module boundaries. No optimization is performed across a module boundary. For debugging purposes, each peephole optimization can be disabled individually via the -fno-dfg-peepnole-<OPT> option, where <OPT> is one of the optimizations listed in V3DfgPeephole.h, for example -fno-dfg-peephole-remove-not-not. The peephole patterns currently implemented were mostly picked based on the design that inspired this work, and on that design the optimizations yields ~30% single threaded speedup, and ~50% speedup on 4 threads. As you can imagine not having to haul around redundant combinational networks in the rest of the compilation pipeline also helps with memory consumption, and up to 30% peak memory usage of Verilator was observed on the same design. Gains on other arbitrary designs are smaller (and can be improved by analyzing those designs). For example OpenTitan gains between 1-15% speedup depending on build type.
2022-09-23 17:46:22 +02:00
// Dump this cone
dumpDotUpstreamConeFromVertex(*os, vtx);
// Footer
Use newline instead of endl, for fewer stream flushes
2023-11-24 17:45:52 +01:00
*os << "}\n";
Introduce DFG based combinational logic optimizer (#3527) Added a new data-flow graph (DFG) based combinational logic optimizer. The capabilities of this covers a combination of V3Const and V3Gate, but is also more capable of transforming combinational logic into simplified forms and more. This entail adding a new internal representation, `DfgGraph`, and appropriate `astToDfg` and `dfgToAst` conversion functions. The graph represents some of the combinational equations (~continuous assignments) in a module, and for the duration of the DFG passes, it takes over the role of AstModule. A bulk of the Dfg vertices represent expressions. These vertex classes, and the corresponding conversions to/from AST are mostly auto-generated by astgen, together with a DfgVVisitor that can be used for dynamic dispatch based on vertex (operation) types. The resulting combinational logic graph (a `DfgGraph`) is then optimized in various ways. Currently we perform common sub-expression elimination, variable inlining, and some specific peephole optimizations, but there is scope for more optimizations in the future using the same representation. The optimizer is run directly before and after inlining. The pre inline pass can operate on smaller graphs and hence converges faster, but still has a chance of substantially reducing the size of the logic on some designs, making inlining both faster and less memory intensive. The post inline pass can then optimize across the inlined module boundaries. No optimization is performed across a module boundary. For debugging purposes, each peephole optimization can be disabled individually via the -fno-dfg-peepnole-<OPT> option, where <OPT> is one of the optimizations listed in V3DfgPeephole.h, for example -fno-dfg-peephole-remove-not-not. The peephole patterns currently implemented were mostly picked based on the design that inspired this work, and on that design the optimizations yields ~30% single threaded speedup, and ~50% speedup on 4 threads. As you can imagine not having to haul around redundant combinational networks in the rest of the compilation pipeline also helps with memory consumption, and up to 30% peak memory usage of Verilator was observed on the same design. Gains on other arbitrary designs are smaller (and can be improved by analyzing those designs). For example OpenTitan gains between 1-15% speedup depending on build type.
2022-09-23 17:46:22 +02:00
// Done with this logic cone
os->close();
});
}
//------------------------------------------------------------------------------
// DfgEdge
//------------------------------------------------------------------------------
void DfgEdge::unlinkSource() {
if (!m_sourcep) return;
#ifdef VL_DEBUG
{
DfgEdge* sinkp = m_sourcep->m_sinksp;
while (sinkp) {
if (sinkp == this) break;
sinkp = sinkp->m_nextp;
}
UASSERT(sinkp, "'m_sourcep' does not have this edge as sink");
}
#endif
// Relink pointers of predecessor and successor
if (m_prevp) m_prevp->m_nextp = m_nextp;
if (m_nextp) m_nextp->m_prevp = m_prevp;
// If head of list in source, update source's head pointer
if (m_sourcep->m_sinksp == this) m_sourcep->m_sinksp = m_nextp;
// Mark source as unconnected
m_sourcep = nullptr;
// Clear links. This is not strictly necessary, but might catch bugs.
m_prevp = nullptr;
m_nextp = nullptr;
}
void DfgEdge::relinkSource(DfgVertex* newSourcep) {
// Unlink current source, if any
unlinkSource();
// Link new source
m_sourcep = newSourcep;
// Prepend to sink list in source
m_nextp = newSourcep->m_sinksp;
if (m_nextp) m_nextp->m_prevp = this;
newSourcep->m_sinksp = this;
}
//------------------------------------------------------------------------------
// DfgVertex
//------------------------------------------------------------------------------
DFG: Make implementation more similar to AST Use the same style, and reuse the bulk of astgen to generate DfgVertex related code. In particular allow for easier definition of custom DfgVertex sub-types that do not directly correspond to an AstNode sub-type. Also introduces specific names for the fixed arity vertices. No functional change intended.
2022-10-04 12:03:41 +02:00
DfgVertex::DfgVertex(DfgGraph& dfg, VDfgType type, FileLine* flp, AstNodeDType* dtypep)
Introduce DFG based combinational logic optimizer (#3527) Added a new data-flow graph (DFG) based combinational logic optimizer. The capabilities of this covers a combination of V3Const and V3Gate, but is also more capable of transforming combinational logic into simplified forms and more. This entail adding a new internal representation, `DfgGraph`, and appropriate `astToDfg` and `dfgToAst` conversion functions. The graph represents some of the combinational equations (~continuous assignments) in a module, and for the duration of the DFG passes, it takes over the role of AstModule. A bulk of the Dfg vertices represent expressions. These vertex classes, and the corresponding conversions to/from AST are mostly auto-generated by astgen, together with a DfgVVisitor that can be used for dynamic dispatch based on vertex (operation) types. The resulting combinational logic graph (a `DfgGraph`) is then optimized in various ways. Currently we perform common sub-expression elimination, variable inlining, and some specific peephole optimizations, but there is scope for more optimizations in the future using the same representation. The optimizer is run directly before and after inlining. The pre inline pass can operate on smaller graphs and hence converges faster, but still has a chance of substantially reducing the size of the logic on some designs, making inlining both faster and less memory intensive. The post inline pass can then optimize across the inlined module boundaries. No optimization is performed across a module boundary. For debugging purposes, each peephole optimization can be disabled individually via the -fno-dfg-peepnole-<OPT> option, where <OPT> is one of the optimizations listed in V3DfgPeephole.h, for example -fno-dfg-peephole-remove-not-not. The peephole patterns currently implemented were mostly picked based on the design that inspired this work, and on that design the optimizations yields ~30% single threaded speedup, and ~50% speedup on 4 threads. As you can imagine not having to haul around redundant combinational networks in the rest of the compilation pipeline also helps with memory consumption, and up to 30% peak memory usage of Verilator was observed on the same design. Gains on other arbitrary designs are smaller (and can be improved by analyzing those designs). For example OpenTitan gains between 1-15% speedup depending on build type.
2022-09-23 17:46:22 +02:00
: m_filelinep{flp}
, m_dtypep{dtypep}
, m_type{type} {
dfg.addVertex(*this);
}
Plug memory leaks (#5016)
2024-03-23 23:12:43 +01:00
DfgVertex::~DfgVertex() {}
DFG: Partial support for unpacked arrays Representation and Ast / Dfg conversions available, for element-wise access only. Not much optimization yet (only CSE).
2022-09-27 01:06:50 +02:00
DFG: Special case representation of AstSel AstSel is a ternary node, but the 'widthp' is always constant and is hence redundant, and 'lsbp' is very often constant. As AstSel is fairly common, we special case as a DfgSel for the constant 'lsbp', and as 'DfgMux` for the non-constant 'lsbp'.
2022-10-06 19:34:18 +02:00
bool DfgVertex::selfEquals(const DfgVertex& that) const { return true; }
Introduce DFG based combinational logic optimizer (#3527) Added a new data-flow graph (DFG) based combinational logic optimizer. The capabilities of this covers a combination of V3Const and V3Gate, but is also more capable of transforming combinational logic into simplified forms and more. This entail adding a new internal representation, `DfgGraph`, and appropriate `astToDfg` and `dfgToAst` conversion functions. The graph represents some of the combinational equations (~continuous assignments) in a module, and for the duration of the DFG passes, it takes over the role of AstModule. A bulk of the Dfg vertices represent expressions. These vertex classes, and the corresponding conversions to/from AST are mostly auto-generated by astgen, together with a DfgVVisitor that can be used for dynamic dispatch based on vertex (operation) types. The resulting combinational logic graph (a `DfgGraph`) is then optimized in various ways. Currently we perform common sub-expression elimination, variable inlining, and some specific peephole optimizations, but there is scope for more optimizations in the future using the same representation. The optimizer is run directly before and after inlining. The pre inline pass can operate on smaller graphs and hence converges faster, but still has a chance of substantially reducing the size of the logic on some designs, making inlining both faster and less memory intensive. The post inline pass can then optimize across the inlined module boundaries. No optimization is performed across a module boundary. For debugging purposes, each peephole optimization can be disabled individually via the -fno-dfg-peepnole-<OPT> option, where <OPT> is one of the optimizations listed in V3DfgPeephole.h, for example -fno-dfg-peephole-remove-not-not. The peephole patterns currently implemented were mostly picked based on the design that inspired this work, and on that design the optimizations yields ~30% single threaded speedup, and ~50% speedup on 4 threads. As you can imagine not having to haul around redundant combinational networks in the rest of the compilation pipeline also helps with memory consumption, and up to 30% peak memory usage of Verilator was observed on the same design. Gains on other arbitrary designs are smaller (and can be improved by analyzing those designs). For example OpenTitan gains between 1-15% speedup depending on build type.
2022-09-23 17:46:22 +02:00
DFG: Special case representation of AstSel AstSel is a ternary node, but the 'widthp' is always constant and is hence redundant, and 'lsbp' is very often constant. As AstSel is fairly common, we special case as a DfgSel for the constant 'lsbp', and as 'DfgMux` for the non-constant 'lsbp'.
2022-10-06 19:34:18 +02:00
V3Hash DfgVertex::selfHash() const { return V3Hash{}; }
Introduce DFG based combinational logic optimizer (#3527) Added a new data-flow graph (DFG) based combinational logic optimizer. The capabilities of this covers a combination of V3Const and V3Gate, but is also more capable of transforming combinational logic into simplified forms and more. This entail adding a new internal representation, `DfgGraph`, and appropriate `astToDfg` and `dfgToAst` conversion functions. The graph represents some of the combinational equations (~continuous assignments) in a module, and for the duration of the DFG passes, it takes over the role of AstModule. A bulk of the Dfg vertices represent expressions. These vertex classes, and the corresponding conversions to/from AST are mostly auto-generated by astgen, together with a DfgVVisitor that can be used for dynamic dispatch based on vertex (operation) types. The resulting combinational logic graph (a `DfgGraph`) is then optimized in various ways. Currently we perform common sub-expression elimination, variable inlining, and some specific peephole optimizations, but there is scope for more optimizations in the future using the same representation. The optimizer is run directly before and after inlining. The pre inline pass can operate on smaller graphs and hence converges faster, but still has a chance of substantially reducing the size of the logic on some designs, making inlining both faster and less memory intensive. The post inline pass can then optimize across the inlined module boundaries. No optimization is performed across a module boundary. For debugging purposes, each peephole optimization can be disabled individually via the -fno-dfg-peepnole-<OPT> option, where <OPT> is one of the optimizations listed in V3DfgPeephole.h, for example -fno-dfg-peephole-remove-not-not. The peephole patterns currently implemented were mostly picked based on the design that inspired this work, and on that design the optimizations yields ~30% single threaded speedup, and ~50% speedup on 4 threads. As you can imagine not having to haul around redundant combinational networks in the rest of the compilation pipeline also helps with memory consumption, and up to 30% peak memory usage of Verilator was observed on the same design. Gains on other arbitrary designs are smaller (and can be improved by analyzing those designs). For example OpenTitan gains between 1-15% speedup depending on build type.
2022-09-23 17:46:22 +02:00
bool DfgVertex::equals(const DfgVertex& that, EqualsCache& cache) const {
if (this == &that) return true;
DFG: Special case representation of AstSel AstSel is a ternary node, but the 'widthp' is always constant and is hence redundant, and 'lsbp' is very often constant. As AstSel is fairly common, we special case as a DfgSel for the constant 'lsbp', and as 'DfgMux` for the non-constant 'lsbp'.
2022-10-06 19:34:18 +02:00
if (this->type() != that.type()) return false;
if (this->dtypep() != that.dtypep()) return false;
Introduce DFG based combinational logic optimizer (#3527) Added a new data-flow graph (DFG) based combinational logic optimizer. The capabilities of this covers a combination of V3Const and V3Gate, but is also more capable of transforming combinational logic into simplified forms and more. This entail adding a new internal representation, `DfgGraph`, and appropriate `astToDfg` and `dfgToAst` conversion functions. The graph represents some of the combinational equations (~continuous assignments) in a module, and for the duration of the DFG passes, it takes over the role of AstModule. A bulk of the Dfg vertices represent expressions. These vertex classes, and the corresponding conversions to/from AST are mostly auto-generated by astgen, together with a DfgVVisitor that can be used for dynamic dispatch based on vertex (operation) types. The resulting combinational logic graph (a `DfgGraph`) is then optimized in various ways. Currently we perform common sub-expression elimination, variable inlining, and some specific peephole optimizations, but there is scope for more optimizations in the future using the same representation. The optimizer is run directly before and after inlining. The pre inline pass can operate on smaller graphs and hence converges faster, but still has a chance of substantially reducing the size of the logic on some designs, making inlining both faster and less memory intensive. The post inline pass can then optimize across the inlined module boundaries. No optimization is performed across a module boundary. For debugging purposes, each peephole optimization can be disabled individually via the -fno-dfg-peepnole-<OPT> option, where <OPT> is one of the optimizations listed in V3DfgPeephole.h, for example -fno-dfg-peephole-remove-not-not. The peephole patterns currently implemented were mostly picked based on the design that inspired this work, and on that design the optimizations yields ~30% single threaded speedup, and ~50% speedup on 4 threads. As you can imagine not having to haul around redundant combinational networks in the rest of the compilation pipeline also helps with memory consumption, and up to 30% peak memory usage of Verilator was observed on the same design. Gains on other arbitrary designs are smaller (and can be improved by analyzing those designs). For example OpenTitan gains between 1-15% speedup depending on build type.
2022-09-23 17:46:22 +02:00
if (!this->selfEquals(that)) return false;
const auto key = (this < &that) ? EqualsCache::key_type{this, &that} //
: EqualsCache::key_type{&that, this};
Internals: Remove redundant hash lookup (#5276 partial) (#5303) Minor help for #5276
2024-07-25 22:07:58 +02:00
// Note: the recursive invocation can cause a re-hash but that will not invalidate references
uint8_t& result = cache[key];
Speed up Dfg common sub-expression elimination Added a DfgVertex::user() mechanism for storing data in vertices. Similar in spirit to AstNode user data, but the generation counter is stored in the DfgGraph the vertex is held under. Use this to cache DfgVertex::hash results, and also speed up DfgVertex hashing in general. Use these and additional improvements to speed up CSE.
2022-10-06 12:26:11 +02:00
if (!result) {
result = 2; // Assume equals
Introduce DFG based combinational logic optimizer (#3527) Added a new data-flow graph (DFG) based combinational logic optimizer. The capabilities of this covers a combination of V3Const and V3Gate, but is also more capable of transforming combinational logic into simplified forms and more. This entail adding a new internal representation, `DfgGraph`, and appropriate `astToDfg` and `dfgToAst` conversion functions. The graph represents some of the combinational equations (~continuous assignments) in a module, and for the duration of the DFG passes, it takes over the role of AstModule. A bulk of the Dfg vertices represent expressions. These vertex classes, and the corresponding conversions to/from AST are mostly auto-generated by astgen, together with a DfgVVisitor that can be used for dynamic dispatch based on vertex (operation) types. The resulting combinational logic graph (a `DfgGraph`) is then optimized in various ways. Currently we perform common sub-expression elimination, variable inlining, and some specific peephole optimizations, but there is scope for more optimizations in the future using the same representation. The optimizer is run directly before and after inlining. The pre inline pass can operate on smaller graphs and hence converges faster, but still has a chance of substantially reducing the size of the logic on some designs, making inlining both faster and less memory intensive. The post inline pass can then optimize across the inlined module boundaries. No optimization is performed across a module boundary. For debugging purposes, each peephole optimization can be disabled individually via the -fno-dfg-peepnole-<OPT> option, where <OPT> is one of the optimizations listed in V3DfgPeephole.h, for example -fno-dfg-peephole-remove-not-not. The peephole patterns currently implemented were mostly picked based on the design that inspired this work, and on that design the optimizations yields ~30% single threaded speedup, and ~50% speedup on 4 threads. As you can imagine not having to haul around redundant combinational networks in the rest of the compilation pipeline also helps with memory consumption, and up to 30% peak memory usage of Verilator was observed on the same design. Gains on other arbitrary designs are smaller (and can be improved by analyzing those designs). For example OpenTitan gains between 1-15% speedup depending on build type.
2022-09-23 17:46:22 +02:00
auto thisPair = this->sourceEdges();
const DfgEdge* const thisSrcEdgesp = thisPair.first;
const size_t thisArity = thisPair.second;
auto thatPair = that.sourceEdges();
const DfgEdge* const thatSrcEdgesp = thatPair.first;
const size_t thatArity = thatPair.second;
UASSERT_OBJ(thisArity == thatArity, this, "Same type vertices must have same arity!");
for (size_t i = 0; i < thisArity; ++i) {
const DfgVertex* const thisSrcVtxp = thisSrcEdgesp[i].m_sourcep;
const DfgVertex* const thatSrcVtxp = thatSrcEdgesp[i].m_sourcep;
if (thisSrcVtxp == thatSrcVtxp) continue;
if (!thisSrcVtxp || !thatSrcVtxp || !thisSrcVtxp->equals(*thatSrcVtxp, cache)) {
Speed up Dfg common sub-expression elimination Added a DfgVertex::user() mechanism for storing data in vertices. Similar in spirit to AstNode user data, but the generation counter is stored in the DfgGraph the vertex is held under. Use this to cache DfgVertex::hash results, and also speed up DfgVertex hashing in general. Use these and additional improvements to speed up CSE.
2022-10-06 12:26:11 +02:00
result = 1; // Mark not equal
Introduce DFG based combinational logic optimizer (#3527) Added a new data-flow graph (DFG) based combinational logic optimizer. The capabilities of this covers a combination of V3Const and V3Gate, but is also more capable of transforming combinational logic into simplified forms and more. This entail adding a new internal representation, `DfgGraph`, and appropriate `astToDfg` and `dfgToAst` conversion functions. The graph represents some of the combinational equations (~continuous assignments) in a module, and for the duration of the DFG passes, it takes over the role of AstModule. A bulk of the Dfg vertices represent expressions. These vertex classes, and the corresponding conversions to/from AST are mostly auto-generated by astgen, together with a DfgVVisitor that can be used for dynamic dispatch based on vertex (operation) types. The resulting combinational logic graph (a `DfgGraph`) is then optimized in various ways. Currently we perform common sub-expression elimination, variable inlining, and some specific peephole optimizations, but there is scope for more optimizations in the future using the same representation. The optimizer is run directly before and after inlining. The pre inline pass can operate on smaller graphs and hence converges faster, but still has a chance of substantially reducing the size of the logic on some designs, making inlining both faster and less memory intensive. The post inline pass can then optimize across the inlined module boundaries. No optimization is performed across a module boundary. For debugging purposes, each peephole optimization can be disabled individually via the -fno-dfg-peepnole-<OPT> option, where <OPT> is one of the optimizations listed in V3DfgPeephole.h, for example -fno-dfg-peephole-remove-not-not. The peephole patterns currently implemented were mostly picked based on the design that inspired this work, and on that design the optimizations yields ~30% single threaded speedup, and ~50% speedup on 4 threads. As you can imagine not having to haul around redundant combinational networks in the rest of the compilation pipeline also helps with memory consumption, and up to 30% peak memory usage of Verilator was observed on the same design. Gains on other arbitrary designs are smaller (and can be improved by analyzing those designs). For example OpenTitan gains between 1-15% speedup depending on build type.
2022-09-23 17:46:22 +02:00
break;
}
}
}
Speed up Dfg common sub-expression elimination Added a DfgVertex::user() mechanism for storing data in vertices. Similar in spirit to AstNode user data, but the generation counter is stored in the DfgGraph the vertex is held under. Use this to cache DfgVertex::hash results, and also speed up DfgVertex hashing in general. Use these and additional improvements to speed up CSE.
2022-10-06 12:26:11 +02:00
return result >> 1;
Introduce DFG based combinational logic optimizer (#3527) Added a new data-flow graph (DFG) based combinational logic optimizer. The capabilities of this covers a combination of V3Const and V3Gate, but is also more capable of transforming combinational logic into simplified forms and more. This entail adding a new internal representation, `DfgGraph`, and appropriate `astToDfg` and `dfgToAst` conversion functions. The graph represents some of the combinational equations (~continuous assignments) in a module, and for the duration of the DFG passes, it takes over the role of AstModule. A bulk of the Dfg vertices represent expressions. These vertex classes, and the corresponding conversions to/from AST are mostly auto-generated by astgen, together with a DfgVVisitor that can be used for dynamic dispatch based on vertex (operation) types. The resulting combinational logic graph (a `DfgGraph`) is then optimized in various ways. Currently we perform common sub-expression elimination, variable inlining, and some specific peephole optimizations, but there is scope for more optimizations in the future using the same representation. The optimizer is run directly before and after inlining. The pre inline pass can operate on smaller graphs and hence converges faster, but still has a chance of substantially reducing the size of the logic on some designs, making inlining both faster and less memory intensive. The post inline pass can then optimize across the inlined module boundaries. No optimization is performed across a module boundary. For debugging purposes, each peephole optimization can be disabled individually via the -fno-dfg-peepnole-<OPT> option, where <OPT> is one of the optimizations listed in V3DfgPeephole.h, for example -fno-dfg-peephole-remove-not-not. The peephole patterns currently implemented were mostly picked based on the design that inspired this work, and on that design the optimizations yields ~30% single threaded speedup, and ~50% speedup on 4 threads. As you can imagine not having to haul around redundant combinational networks in the rest of the compilation pipeline also helps with memory consumption, and up to 30% peak memory usage of Verilator was observed on the same design. Gains on other arbitrary designs are smaller (and can be improved by analyzing those designs). For example OpenTitan gains between 1-15% speedup depending on build type.
2022-09-23 17:46:22 +02:00
}
Speed up Dfg common sub-expression elimination Added a DfgVertex::user() mechanism for storing data in vertices. Similar in spirit to AstNode user data, but the generation counter is stored in the DfgGraph the vertex is held under. Use this to cache DfgVertex::hash results, and also speed up DfgVertex hashing in general. Use these and additional improvements to speed up CSE.
2022-10-06 12:26:11 +02:00
V3Hash DfgVertex::hash() {
V3Hash& result = user<V3Hash>();
if (!result.value()) {
DFG: don't try to call DfgVertex::width() on arrays In DFG DfgVertex::width() is only defined for vertices representing packed values, which DfgVertex::hash() used to violate. The only non-packed values at the moment are DfgVarArray, which is a DfgVertexVar, which are handled specially anyway, so this is easy to fix. Fixes #3682
2022-10-21 11:50:02 +02:00
V3Hash hash{selfHash()};
// Variables are defined by themselves, so there is no need to hash them further
// (especially the sources). This enables sound hashing of graphs circular only through
// variables, which we rely on.
DFG: Make implementation more similar to AST Use the same style, and reuse the bulk of astgen to generate DfgVertex related code. In particular allow for easier definition of custom DfgVertex sub-types that do not directly correspond to an AstNode sub-type. Also introduces specific names for the fixed arity vertices. No functional change intended.
2022-10-04 12:03:41 +02:00
if (!is<DfgVertexVar>()) {
DFG: don't try to call DfgVertex::width() on arrays In DFG DfgVertex::width() is only defined for vertices representing packed values, which DfgVertex::hash() used to violate. The only non-packed values at the moment are DfgVarArray, which is a DfgVertexVar, which are handled specially anyway, so this is easy to fix. Fixes #3682
2022-10-21 11:50:02 +02:00
hash += m_type;
hash += width(); // Currently all non-variable vertices are packed, so this is safe
Speed up Dfg common sub-expression elimination Added a DfgVertex::user() mechanism for storing data in vertices. Similar in spirit to AstNode user data, but the generation counter is stored in the DfgGraph the vertex is held under. Use this to cache DfgVertex::hash results, and also speed up DfgVertex hashing in general. Use these and additional improvements to speed up CSE.
2022-10-06 12:26:11 +02:00
const auto pair = sourceEdges();
const DfgEdge* const edgesp = pair.first;
const size_t arity = pair.second;
// Sources must always be connected in well-formed graphs
for (size_t i = 0; i < arity; ++i) hash += edgesp[i].m_sourcep->hash();
DFG: support hashing of graphs circular through variables No functional change
2022-09-27 14:50:37 +02:00
}
Speed up Dfg common sub-expression elimination Added a DfgVertex::user() mechanism for storing data in vertices. Similar in spirit to AstNode user data, but the generation counter is stored in the DfgGraph the vertex is held under. Use this to cache DfgVertex::hash results, and also speed up DfgVertex hashing in general. Use these and additional improvements to speed up CSE.
2022-10-06 12:26:11 +02:00
result = hash;
Introduce DFG based combinational logic optimizer (#3527) Added a new data-flow graph (DFG) based combinational logic optimizer. The capabilities of this covers a combination of V3Const and V3Gate, but is also more capable of transforming combinational logic into simplified forms and more. This entail adding a new internal representation, `DfgGraph`, and appropriate `astToDfg` and `dfgToAst` conversion functions. The graph represents some of the combinational equations (~continuous assignments) in a module, and for the duration of the DFG passes, it takes over the role of AstModule. A bulk of the Dfg vertices represent expressions. These vertex classes, and the corresponding conversions to/from AST are mostly auto-generated by astgen, together with a DfgVVisitor that can be used for dynamic dispatch based on vertex (operation) types. The resulting combinational logic graph (a `DfgGraph`) is then optimized in various ways. Currently we perform common sub-expression elimination, variable inlining, and some specific peephole optimizations, but there is scope for more optimizations in the future using the same representation. The optimizer is run directly before and after inlining. The pre inline pass can operate on smaller graphs and hence converges faster, but still has a chance of substantially reducing the size of the logic on some designs, making inlining both faster and less memory intensive. The post inline pass can then optimize across the inlined module boundaries. No optimization is performed across a module boundary. For debugging purposes, each peephole optimization can be disabled individually via the -fno-dfg-peepnole-<OPT> option, where <OPT> is one of the optimizations listed in V3DfgPeephole.h, for example -fno-dfg-peephole-remove-not-not. The peephole patterns currently implemented were mostly picked based on the design that inspired this work, and on that design the optimizations yields ~30% single threaded speedup, and ~50% speedup on 4 threads. As you can imagine not having to haul around redundant combinational networks in the rest of the compilation pipeline also helps with memory consumption, and up to 30% peak memory usage of Verilator was observed on the same design. Gains on other arbitrary designs are smaller (and can be improved by analyzing those designs). For example OpenTitan gains between 1-15% speedup depending on build type.
2022-09-23 17:46:22 +02:00
}
return result;
}
uint32_t DfgVertex::fanout() const {
uint32_t result = 0;
forEachSinkEdge([&](const DfgEdge&) { ++result; });
return result;
}
void DfgVertex::unlinkDelete(DfgGraph& dfg) {
// Unlink source edges
forEachSourceEdge([](DfgEdge& edge, size_t) { edge.unlinkSource(); });
// Unlink sink edges
forEachSinkEdge([](DfgEdge& edge) { edge.unlinkSource(); });
// Remove from graph
dfg.removeVertex(*this);
// Delete
delete this;
}
void DfgVertex::replaceWith(DfgVertex* newSorucep) {
while (m_sinksp) m_sinksp->relinkSource(newSorucep);
}
//------------------------------------------------------------------------------
// Vertex classes
//------------------------------------------------------------------------------
DFG: Special case representation of AstSel AstSel is a ternary node, but the 'widthp' is always constant and is hence redundant, and 'lsbp' is very often constant. As AstSel is fairly common, we special case as a DfgSel for the constant 'lsbp', and as 'DfgMux` for the non-constant 'lsbp'.
2022-10-06 19:34:18 +02:00
// DfgConst ----------
bool DfgConst::selfEquals(const DfgVertex& that) const {
Make DfgConst hold V3Number directly Remove intermediary AstConst. No functional change intended.
2022-10-07 16:44:14 +02:00
return num().isCaseEq(that.as<DfgConst>()->num());
DFG: Special case representation of AstSel AstSel is a ternary node, but the 'widthp' is always constant and is hence redundant, and 'lsbp' is very often constant. As AstSel is fairly common, we special case as a DfgSel for the constant 'lsbp', and as 'DfgMux` for the non-constant 'lsbp'.
2022-10-06 19:34:18 +02:00
}
Make DfgConst hold V3Number directly Remove intermediary AstConst. No functional change intended.
2022-10-07 16:44:14 +02:00
V3Hash DfgConst::selfHash() const { return num().toHash(); }
DFG: Special case representation of AstSel AstSel is a ternary node, but the 'widthp' is always constant and is hence redundant, and 'lsbp' is very often constant. As AstSel is fairly common, we special case as a DfgSel for the constant 'lsbp', and as 'DfgMux` for the non-constant 'lsbp'.
2022-10-06 19:34:18 +02:00
// DfgSel ----------
bool DfgSel::selfEquals(const DfgVertex& that) const { return lsb() == that.as<DfgSel>()->lsb(); }
V3Hash DfgSel::selfHash() const { return V3Hash{lsb()}; }
Speed up Dfg common sub-expression elimination Added a DfgVertex::user() mechanism for storing data in vertices. Similar in spirit to AstNode user data, but the generation counter is stored in the DfgGraph the vertex is held under. Use this to cache DfgVertex::hash results, and also speed up DfgVertex hashing in general. Use these and additional improvements to speed up CSE.
2022-10-06 12:26:11 +02:00
// DfgVertexVar ----------
Introduce DFG based combinational logic optimizer (#3527) Added a new data-flow graph (DFG) based combinational logic optimizer. The capabilities of this covers a combination of V3Const and V3Gate, but is also more capable of transforming combinational logic into simplified forms and more. This entail adding a new internal representation, `DfgGraph`, and appropriate `astToDfg` and `dfgToAst` conversion functions. The graph represents some of the combinational equations (~continuous assignments) in a module, and for the duration of the DFG passes, it takes over the role of AstModule. A bulk of the Dfg vertices represent expressions. These vertex classes, and the corresponding conversions to/from AST are mostly auto-generated by astgen, together with a DfgVVisitor that can be used for dynamic dispatch based on vertex (operation) types. The resulting combinational logic graph (a `DfgGraph`) is then optimized in various ways. Currently we perform common sub-expression elimination, variable inlining, and some specific peephole optimizations, but there is scope for more optimizations in the future using the same representation. The optimizer is run directly before and after inlining. The pre inline pass can operate on smaller graphs and hence converges faster, but still has a chance of substantially reducing the size of the logic on some designs, making inlining both faster and less memory intensive. The post inline pass can then optimize across the inlined module boundaries. No optimization is performed across a module boundary. For debugging purposes, each peephole optimization can be disabled individually via the -fno-dfg-peepnole-<OPT> option, where <OPT> is one of the optimizations listed in V3DfgPeephole.h, for example -fno-dfg-peephole-remove-not-not. The peephole patterns currently implemented were mostly picked based on the design that inspired this work, and on that design the optimizations yields ~30% single threaded speedup, and ~50% speedup on 4 threads. As you can imagine not having to haul around redundant combinational networks in the rest of the compilation pipeline also helps with memory consumption, and up to 30% peak memory usage of Verilator was observed on the same design. Gains on other arbitrary designs are smaller (and can be improved by analyzing those designs). For example OpenTitan gains between 1-15% speedup depending on build type.
2022-09-23 17:46:22 +02:00
Speed up Dfg common sub-expression elimination Added a DfgVertex::user() mechanism for storing data in vertices. Similar in spirit to AstNode user data, but the generation counter is stored in the DfgGraph the vertex is held under. Use this to cache DfgVertex::hash results, and also speed up DfgVertex hashing in general. Use these and additional improvements to speed up CSE.
2022-10-06 12:26:11 +02:00
bool DfgVertexVar::selfEquals(const DfgVertex& that) const {
DFG: Special case representation of AstSel AstSel is a ternary node, but the 'widthp' is always constant and is hence redundant, and 'lsbp' is very often constant. As AstSel is fairly common, we special case as a DfgSel for the constant 'lsbp', and as 'DfgMux` for the non-constant 'lsbp'.
2022-10-06 19:34:18 +02:00
UASSERT_OBJ(varp() != that.as<DfgVertexVar>()->varp(), this,
Make DfgConst hold V3Number directly Remove intermediary AstConst. No functional change intended.
2022-10-07 16:44:14 +02:00
"There should only be one DfgVertexVar for a given AstVar");
Introduce DFG based combinational logic optimizer (#3527) Added a new data-flow graph (DFG) based combinational logic optimizer. The capabilities of this covers a combination of V3Const and V3Gate, but is also more capable of transforming combinational logic into simplified forms and more. This entail adding a new internal representation, `DfgGraph`, and appropriate `astToDfg` and `dfgToAst` conversion functions. The graph represents some of the combinational equations (~continuous assignments) in a module, and for the duration of the DFG passes, it takes over the role of AstModule. A bulk of the Dfg vertices represent expressions. These vertex classes, and the corresponding conversions to/from AST are mostly auto-generated by astgen, together with a DfgVVisitor that can be used for dynamic dispatch based on vertex (operation) types. The resulting combinational logic graph (a `DfgGraph`) is then optimized in various ways. Currently we perform common sub-expression elimination, variable inlining, and some specific peephole optimizations, but there is scope for more optimizations in the future using the same representation. The optimizer is run directly before and after inlining. The pre inline pass can operate on smaller graphs and hence converges faster, but still has a chance of substantially reducing the size of the logic on some designs, making inlining both faster and less memory intensive. The post inline pass can then optimize across the inlined module boundaries. No optimization is performed across a module boundary. For debugging purposes, each peephole optimization can be disabled individually via the -fno-dfg-peepnole-<OPT> option, where <OPT> is one of the optimizations listed in V3DfgPeephole.h, for example -fno-dfg-peephole-remove-not-not. The peephole patterns currently implemented were mostly picked based on the design that inspired this work, and on that design the optimizations yields ~30% single threaded speedup, and ~50% speedup on 4 threads. As you can imagine not having to haul around redundant combinational networks in the rest of the compilation pipeline also helps with memory consumption, and up to 30% peak memory usage of Verilator was observed on the same design. Gains on other arbitrary designs are smaller (and can be improved by analyzing those designs). For example OpenTitan gains between 1-15% speedup depending on build type.
2022-09-23 17:46:22 +02:00
return false;
}
Speed up Dfg common sub-expression elimination Added a DfgVertex::user() mechanism for storing data in vertices. Similar in spirit to AstNode user data, but the generation counter is stored in the DfgGraph the vertex is held under. Use this to cache DfgVertex::hash results, and also speed up DfgVertex hashing in general. Use these and additional improvements to speed up CSE.
2022-10-06 12:26:11 +02:00
V3Hash DfgVertexVar::selfHash() const {
V3Hash hash;
hash += m_varp->name();
hash += m_varp->varType();
return hash;
DFG: Partial support for unpacked arrays Representation and Ast / Dfg conversions available, for element-wise access only. Not much optimization yet (only CSE).
2022-09-27 01:06:50 +02:00
}
Introduce DFG based combinational logic optimizer (#3527) Added a new data-flow graph (DFG) based combinational logic optimizer. The capabilities of this covers a combination of V3Const and V3Gate, but is also more capable of transforming combinational logic into simplified forms and more. This entail adding a new internal representation, `DfgGraph`, and appropriate `astToDfg` and `dfgToAst` conversion functions. The graph represents some of the combinational equations (~continuous assignments) in a module, and for the duration of the DFG passes, it takes over the role of AstModule. A bulk of the Dfg vertices represent expressions. These vertex classes, and the corresponding conversions to/from AST are mostly auto-generated by astgen, together with a DfgVVisitor that can be used for dynamic dispatch based on vertex (operation) types. The resulting combinational logic graph (a `DfgGraph`) is then optimized in various ways. Currently we perform common sub-expression elimination, variable inlining, and some specific peephole optimizations, but there is scope for more optimizations in the future using the same representation. The optimizer is run directly before and after inlining. The pre inline pass can operate on smaller graphs and hence converges faster, but still has a chance of substantially reducing the size of the logic on some designs, making inlining both faster and less memory intensive. The post inline pass can then optimize across the inlined module boundaries. No optimization is performed across a module boundary. For debugging purposes, each peephole optimization can be disabled individually via the -fno-dfg-peepnole-<OPT> option, where <OPT> is one of the optimizations listed in V3DfgPeephole.h, for example -fno-dfg-peephole-remove-not-not. The peephole patterns currently implemented were mostly picked based on the design that inspired this work, and on that design the optimizations yields ~30% single threaded speedup, and ~50% speedup on 4 threads. As you can imagine not having to haul around redundant combinational networks in the rest of the compilation pipeline also helps with memory consumption, and up to 30% peak memory usage of Verilator was observed on the same design. Gains on other arbitrary designs are smaller (and can be improved by analyzing those designs). For example OpenTitan gains between 1-15% speedup depending on build type.
2022-09-23 17:46:22 +02:00
//------------------------------------------------------------------------------
// DfgVisitor
//------------------------------------------------------------------------------
DFG: Make implementation more similar to AST Use the same style, and reuse the bulk of astgen to generate DfgVertex related code. In particular allow for easier definition of custom DfgVertex sub-types that do not directly correspond to an AstNode sub-type. Also introduces specific names for the fixed arity vertices. No functional change intended.
2022-10-04 12:03:41 +02:00
#include "V3Dfg__gen_visitor_defns.h" // From ./astgen