Added a mini type system for Dfg using DfgDataType to replace Dfg's use
of AstNodeDType. This is much more restricted and represents only the
types Dfg can handle in a canonical form. This will be needed when
adding more support for unpacked arrays and maybe unpacked structs one
day.
Also added an internal type checker for DfgGraphs which encodes all the
assumptions the code makes about type relationships in the graph. Run
this in a few places with --debug-check. Fix resulting fallout.
Reduce set of synthesized logic to be more in-line with what Dfg used to
handle before + drivers of circular variables. This was always the
intention but the previous algorithm was both a bit too eager, and also
missed some circular variables. We can add back more heuristics based on
performance measurements for non-circular logic later.
Parts of this algorithm were distributed over many files some
masquerading as re-usable APIs, they were not. Move everything into one
file and avoid unnecessary virtual functions.
- Remove _ENUM_END, so -Wswitch does not demand it's covered. Use the
new NUM_TYPES constexpr member instead.
- Remove 'at' prefix. This seems historical and is not particularly useful.
- Fix some cppcheck warts while at it
Add DfgUserMap as a handle around the one pointer worth of algorithm
specific 'user' storage in each DfgVertex. This reduces verbosity,
improves type safety and correctness. Also enables us to remove one
pointer from DfgVertex to reduce memory use. No functional change.
Large scale refactoring to simplify some of the more obtuse internals of
DFG. Remove multiple redundant internal APIs, simplify representation of
variables, fix potential unsoundness in circular decomposition. No
functional change intended.
This patch adds DfgLogic, which is a vertex that represents a whole,
arbitrarily complex combinational AstAlways or AstAssignW in the
DfgGraph.
Implementing this requires computing the variables live at entry to the
AstAlways (variables read by the block), so there is a new
ControlFlowGraph data structure and a classical data-flow analysis based
live variable analysis to do that at the variable level (as opposed to
bit/element level).
The actual CFG construction and live variable analysis is best effort,
and might fail for currently unhandled constructs or data types. This
can be extended later.
V3DfgAstToDfg is changed to convert the Ast into an initial DfgGraph
containing only DfgLogic, DfgVertexSplice and DfgVertexVar vertices.
The DfgLogic are then subsequently synthesized into primitive operations
by the new V3DfgSynthesize pass, which is a combination of the old
V3DfgAstToDfg conversion and new code to handle AstAlways blocks with
complex flow control.
V3DfgSynthesize by default will synthesize roughly the same constructs
as V3DfgAstToDfg used to handle before, plus any logic that is part of a
combinational cycle within the DfgGraph. This enables breaking up these
cycles, for which there are extensions to V3DfgBreakCycles in this patch
as well. V3DfgSynthesize will then delete all non synthesized or non
synthesizable DfgLogic vertices and the rest of the Dfg pipeline is
identical, with minor changes to adjust for the changed representation.
Because with this change we can now eliminate many more UNOPTFLAT, DFG
has been disabled in all the tests that specifically target testing the
scheduling and reporting of circular combinational logic.
After making a cyclic DFG component acyclic, merge that component back
into the acyclic sub-graph of the input graph. This enables optimizing
through the components that were made acyclic in their larger context.
Store all flags in a DfgVertexVar relating to the underlying
AstVar/AstVarScope stored via AstNode::user1(). user2/user3/user4 are
then usable by DFG algorithms as needed.
SystemC variables are fairly special (they can only be assigned to/from,
but not otherwise participate in expressions), which complicates some
DFG code. These variables only ever appear as port on the top level
wrapper, so excluding them from DFG does not make us loose any
optimizations, but simplifies internals.
Previously DFG was limited to having a Sel, or an ArraySel potentially
under a Concat on the LHS of combinational assignments. Other forms or
combinations were not representable in the graph.
This adds support for arbitrary combinations of the above by
combining DfgSplicePacked and DfgSpliceArray vertices introduced in
#6176. In particular, Sel(ArraySel(VarRef,_),_) enables a lot more code
to be represented in DFG.
This is mostly a refactoring, but also enables handling some more
UNOPTFLAT, when the variable is only partially assigned in the cycle.
Previously the way partial assignments to variables were handled were
through the DfgVerexVar types themselves, which kept track of all
drivers. This has been replaced by DfgVertexSplice (which always drives
a DfgVeretexVar), and all DfgVertexVar now only have a single source,
either a DfgVertexSplice, if partially assigned, or an arbitrary
DfgVertex when updated as a whole.
Added an algorithm that can break some combinational cycles in DFG, by
attempting to trace driver logic until we escape the cycle. This can
eliminate a decent portion of UNOPTFLAT warnings. E.g. due to this code:
```systemverilog
assign a[0] = .....;
assign a[1] = ~a[0];
```
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.
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
Vertices representing variables (DfgVertexVar) and constants (DfgConst)
are very common (40-50% of all vertices created in some large designs),
and we also need to, or can treat them specially in algorithms. Keep
these as separate lists in DfgGraph for direct access to them. This
improve verilation speed.
Cyclic components are now extracted separately, so there is no
functional reason to have to do a topological sort (previously we used it
to detect cyclic graphs). Removing it to gain some speed.
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'.
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.
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.
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.
Geza Lore
Wilson Snyder
github action
Mariusz Glebocki