OpenRAM/docs/source/basic_usage.md

Go Back

Basic Usage

This page of the documentation explains the basic usage of OpenRAM.

Table of Contents

1. Environment Variable Setup
2. Script Usage (with library)
3. Command Line Usage (with library)
4. Command Line Usage (without library)
5. Configuration Files
6. Common Configuration File Options
7. Output Files
8. Data Sheets

Environment Variable Setup (assuming bash)

Note: This is optional if you have the OpenRAM library. See basic setup for details.

• OPENRAM_HOME defines where the compiler directory is
  • export OPENRAM_HOME="$HOME/openram/compiler"
• OPENRAM_TECH defines list of paths where the technologies exist
  • export OPENRAM_TECH="$HOME/openram/technology"
  • Colon separated list so you can have private technology directories
• Must also have any PDK related variables set up
• Add compiler to PYTHONPATH
  • export PYTHONPATH="$PYTHONPATH:$OPENRAM_HOME"

Script Usage (with library)

If you have the library installed, you can use OpenRAM in any Python script. You can import "openram" as follows:

import openram
openram.init_openram("myconfig.py") # Config files are explained on this page
# Now you can use modules from openram
from openram import tech
...

Note that you need to initalize OpenRAM so that the modules are imported properly. You can also look at sram_compiler.py as an example on how to use "openram."

If you want to pass custom configuration when generating an SRAM, you can use the sram_config class.

import openram
openram.init_openram("myconfig.py")

from openram import sram_config
c = sram_config(...)

from openram import sram
s = sram(sram_config=c,
         name="custom_name")

s.save()

openram.end_openram()

Command Line Usage (with library)

You can run OpenRAM from the command line using the sram_compiler.py script that is included in the library's installation. You can find the package directory on a path like:

/home/mrg/.local/lib/python3.8/site-packages/openram

Alternatively, you can run the following command to find that path:

echo -e "import os\nimport openram\nprint(os.path.dirname(openram.__file__))" | python3 -

You can continue with following section for more details.

Command Line Usage (without library)

Once you have defined the environment, you can run OpenRAM from the command line using a single configuration file written in Python.

For example, create a file called myconfig.py specifying the following parameters for your memory:

# Data word size
word_size = 2
# Number of words in the memory
num_words = 16

# Technology to use in $OPENRAM_TECH
tech_name = "scn4m_subm"

# You can use the technology nominal corner only
nominal_corner_only = True
# Or you can specify particular corners
# Process corners to characterize
# process_corners = ["SS", "TT", "FF"]
# Voltage corners to characterize
# supply_voltages = [ 3.0, 3.3, 3.5 ]
# Temperature corners to characterize
# temperatures = [ 0, 25 100]

# Output directory for the results
output_path = "temp"
# Output file base name
output_name = "sram_{0}_{1}_{2}".format(word_size,num_words,tech_name)

# Disable analytical models for full characterization (WARNING: slow!)
# analytical_delay = False

You can then run OpenRAM by executing:

python3 $OPENRAM_HOME/../sram_compiler.py myconfig

You can see all of the options for the configuration file in $OPENRAM_HOME/options.py

To run designs in Docker, it is suggested to use, for example:

cd OpenRAM/macros
make example_config_scn4m_subm

• Common arguments:
  • -t specify technology (scn4m_subm or scmos or freepdk45)
  • -v increase verbosity of output
  • -n don't run DRC/LVS
  • -c perform simulation-based characterization
  • -d don't purge /tmp directory contents

Configuration Files

• Memories are created using a Python configuration file to replicate results
  • No YAML, JSON, etc.
• Complete configuration options are in $OPENRAM_HOME/options.py
• Some options can be specified on the command line as well
  • Not recommended for replicating results
• Example configuration file:

  # Data word size
  word_size = 2
  # Number of words in the memory
  num_words = 16
  
  # Technology to use in $OPENRAM_TECH
  tech_name = "scn4m_subm"
  # Process corners to characterize
  process_corners = [ "TT" ]
  # Voltage corners to characterize
  supply_voltages = [ 3.3 ]
  # Temperature corners to characterize
  temperatures = [ 25 ]
  
  # Output directory for the results
  output_path = "temp"
  # Output file base name
  output_name = "sram_16x2"
  
  # Disable analytical models for full characterization (WARNING: slow!)
  # analytical_delay = False
  
  # To force this to use magic and netgen for DRC/LVS/PEX
  # Could be calibre for FreePDK45
  drc_name = "magic"
  lvs_name = "netgen"
  pex_name = "magic"  
  

Common Configuration File Options

• Characterization corners
  • supply_voltages = [1.7, 1.8, 1.9]
  • temperatures = [25, 50, 100]
  • process_corners = ["SS", "TT", "FF"]
• Do not generate layout
  • netlist_only = True
• Multi-port options
  • num_rw_ports = 1
  • num_r_ports = 1
  • num_w_ports = 0
• Customized module or bit cell
  • bitcell = "bitcell_1rw_1r"
  • replica_bitcell = "replica_bitcell_1rw_1r"
• Enable simulation characterization

  Warning: Slow!

  • analytical_delay = False
• Output name and location
  • output_path = "temp"
  • output_name = "sram_32x256"
• Force tool selection (should match the PDK!)
  • drc_name = "magic"
  • lvs_name = "netgen"
  • pex_name = "magic"
• Include shared configuration options using Python imports
  • from corners_freepdk45 import *

Output Files

The output files are placed in the output_dir defined in the configuration file.

The base name is specified by output_name and suffixes are added.

The final results files are:

• GDS (.gds)
• SPICE (.sp)
• Verilog (.v)
• P&R Abstract (.lef)
• Liberty (multiple corners .lib)
• Datasheet (.html)
• Log (.log)
• Configuration (.py) for replication of creation

Data Sheets