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Deleted unused files, tweaked workflow, added badge
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.github/workflows/run_tests.yaml

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- name: Run tests in Intel environment
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run: |
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. $CONDA/etc/profile.d/conda.sh
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conda activate intel_env
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python run_tests.py
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conda activate intel_env || exit 1
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# This is toy run for GH action,
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# The arguments are really bad for real perf testing, use default arguments instead
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python numpy/umath/umath_mem_bench.py -v --size 10 --goal-time 0.01 --repeats 1 || exit 1
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- name: Run tests in stock environment
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run: |
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. $CONDA/etc/profile.d/conda.sh
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conda activate stock_env
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python run_tests.py
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conda activate stock_env || exit 1
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# This is toy run for GH action,
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# The arguments are really bad for real perf testing, use default arguments instead
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python numpy/umath/umath_mem_bench.py -v --size 10 --goal-time 0.01 --repeats 1 || exit 1

README.md

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[![Run benchmark tests](https://github.com/IntelPython/optimizations_bench/actions/workflows/run_tests.yaml/badge.svg)](https://github.com/IntelPython/optimizations_bench/actions/workflows/run_tests.yaml)
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# Optimization Benchmarks
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Collection of performance benchmarks used to present optimizations implemented for Intel(R) Distribution for Python*
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## Environment Setup
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To install Python environments from Intel channel along with pip-installed packages
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- `python3 create_python_envs.py`
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- `conda env create -f environments/intel.yaml`
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- `conda activate intel_env`
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## Run tests
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- `python3 run_tests.py`
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- `python numpy/umath/umath_mem_bench.py -v --size 10 --goal-time 0.01 --repeats 1`
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## Run benchmarks
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### umath
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- To run python benchmarks: `python numpy/umath/umath_mem_bench.py`
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- To compile and run native benchmarks (requires icc): `make -C numpy/umath`
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- To compile and run native benchmarks (requires `icx`): `make -C numpy/umath`
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### Random number generation
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- To run python benchmarks: `python numpy/random/rng.py`
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- To compile and run native benchmarks (requires icc): `make -C numpy/random`
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- To compile and run native benchmarks (requires `icx`): `make -C numpy/random`
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## See also
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"[Accelerating Scientific Python with Intel Optimizations](http://conference.scipy.org/proceedings/scipy2017/pdfs/oleksandr_pavlyk.pdf)" by Oleksandr Pavlyk, Denis Nagorny, Andres Guzman-Ballen, Anton Malakhov, Hai Liu, Ehsan Totoni, Todd A. Anderson, Sergey Maidanov. Proceedings of the 16th Python in Science Conference (SciPy 2017), July 10 - July 16, Austin, Texas

create_python_envs.py

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run_tests.py

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