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KyuPy - Processing VLSI Circuits With Ease
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==========================================
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KyuPy is a python package for high-performance processing and analysis of
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non-hierarchical VLSI designs. Its purpose is to provide a rapid prototyping
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platform to aid and accelerate research in the fields of VLSI test, diagnosis
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and reliability. KyuPy is freely available under the MIT license.
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Main Features
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-------------
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* Partial [lark](https://github.com/lark-parser/lark) parsers for common files used with synthesized designs:
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bench, gate-level verilog, standard delay format (SDF), standard test interface language (STIL)
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* Bit-parallel gate-level 2-, 4-, and 8-valued logic simulation
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* GPU-accelerated high-throughput gate-level timing simulation
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* High-performance through the use of [numpy](https://numpy.org) and [numba](https://numba.pydata.org)
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Getting Started
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---------------
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KyuPy requires Python 3.6 or newer.
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Install the latest release by running:
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```commandline
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pip3 install --user kyupy
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```
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For best performance, ensure you have [numba](https://pypi.org/project/numba) installed:
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```commandline
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pip3 install --user numba
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```
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GPU/CUDA support may [require some additional setup](https://numba.pydata.org/numba-doc/latest/cuda/index.html).
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If CUDA or numba is not available, KyuPy will automatically fall back to slow, pure python execution.
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The Jupyter Notebook [UsageExamples.ipynb](https://github.com/s-holst/kyupy/blob/main/UsageExamples.ipynb) on GitHub
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contains some useful examples to get familiar with the API.
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Development
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-----------
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To contribute to KyuPy or simply explore the source code, clone the KyuPy [repository](https://github.com/s-holst/kyupy) on GitHub.
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Within your local checkout, run:
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```commandline
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pip3 install --user -e .
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```
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to make the kyupy package available in your python environment.
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The source code comes with tests that can be run with:
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```
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pytest
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```
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KyuPy depends on the following packages:
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* [lark-parser](https://pypi.org/project/lark-parser)
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* [numpy](https://pypi.org/project/numpy)
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* [numba](https://pypi.org/project/numba) (optional, required only for GPU/CUDA support)
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