Converts a subset of python generator functions into synthesizable sequential SystemVerilog
Project description
python2verilog
- This tool facilitates the conversion of select Python functions (including generators!) into synthesizable sequential SystemVerilog
- Ideal for quickly translating higher-level "CPU code" into hardware descriptions for use on FPGAs, without needing to interface with or including a CPU in the design
- Testbenches can be automatically generated if the user uses the function within their Python code or provides explicit test cases
from python2verilog import verilogify
@verilogify
def hrange(base, limit, step):
i = base
while i < limit:
yield i
i += step
print(list(hrange(0, 10, 3)))
A live transpile demo can be found here.
Specifications
Some constrains on Python functions include:
- Supports only signed integral input/output and operations
- Must be a pure function
Unsupported Python paradigms include but are not limited to the following:
- Global (nonlocal) variables, instead declare them within the function with minimal overhead
- Keyword parameters and default arguments, instead use explicit positional arguments
Usage and Installation
Try it in Google Collab or check out examples/
!
python3 -m pip install --upgrade pip
python3 -m pip install python2verilog
Tested Generations
You may find the output of the integration testing as a Github Artifact available for download.
For Developers
To setup pre-commit, run pre-commit install
.
Github Issues are used for tracking.
Sphinx is used for the docs. Follow the sphinx workflow to generate a local copy.
Development
Setup
For most up-to-date information, refer to the pytest workflow or the packaging workflow.
A Ubuntu environment (WSL2 works too, make sure to have the repo on the Ubuntu partition, as os.mkfifo
is used to avoid writing to disk)
Steps
source ./build.sh venv
./build.sh all
pre-commit install
For automatic Verilog simulation and testing, install Icarus Verilog and its dependencies with
sudo apt install expect
# This adds `iverilog` to PATH
git submodule update --init
./extern/iverilog_setup.sh
The online simulator EDA Playground can be used as a subsitute if you manually copy-paste the module and testbench files to it.
Running Tests
Run Python tests with pytest
.
Run rust tests with cargo test
.
CLI arguments for test configuration can be found in tests/conftest.py.
Use ./clean.sh
to remove gitignored and generated files.
Troubleshooting
cargo test
Errors
- error: linker `cc` not found
- On Ubuntu run
sudo apt install build-essential
- On Ubuntu run
- /usr/bin/ld: cannot find -lpython3.10: No such file or directory
- On Ubuntu 22.04 run
sudo apt install libpython3.10-dev
- On Ubuntu 22.04 run
Flamegraph
cargo install flamegraph
sudo apt install linux-tools-common linux-tools-generic linux-tools-`uname -r`
sudo sysctl kernel.perf_event_paranoid=0
CARGO_PROFILE_RELEASE_DEBUG=true cargo flamegraph --unit-test tohdl-tests -- verilog::module::test::odd_fib
CARGO_PROFILE_RELEASE_DEBUG=true cargo flamegraph --test loops
Will need to set PERF env var for flamegraph
if running in WSL from this stackoverflow answer.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
File details
Details for the file python2verilog-0.5.0.tar.gz
.
File metadata
- Download URL: python2verilog-0.5.0.tar.gz
- Upload date:
- Size: 59.1 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.0.0 CPython/3.9.19
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | c1b68fe2d3d49cb3b2be9a2e2cfb2f1be2aba01ac35a01bab41512a04bc7fa59 |
|
MD5 | aad06bcda4f1ebf0e7f13f996248d1a8 |
|
BLAKE2b-256 | 2302c05ac947a18b9a2f9126d7e7bef830b7a781e975bf13fc45471c1ecf4bda |
File details
Details for the file python2verilog-0.5.0-py3-none-any.whl
.
File metadata
- Download URL: python2verilog-0.5.0-py3-none-any.whl
- Upload date:
- Size: 69.8 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.0.0 CPython/3.9.19
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | d8bcfa0ed8766398a1c4e55dbfb4bb6c48b06b3924e620905eadc3566173fad9 |
|
MD5 | 0a157f271a3ae42689452d567b58ce4f |
|
BLAKE2b-256 | 7d42a8ad78efabce848b267a16a032835d4db6452a7c3c2cc863b7909319687f |