https://github.com/intelpython/optimizations_bench

Collection of performance benchmarks used to present optimizations implemented for Intel(R) Distribution for Python*
https://github.com/intelpython/optimizations_bench

benchmark mkl-umath numpy python

Last synced: about 1 month ago
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Collection of performance benchmarks used to present optimizations implemented for Intel(R) Distribution for Python*

• Host: GitHub
• URL: https://github.com/intelpython/optimizations_bench
• Owner: IntelPython
• License: mit
• Created: 2017-04-14T22:26:09.000Z (over 7 years ago)
• Default Branch: master
• Last Pushed: 2024-08-16T18:34:22.000Z (4 months ago)
• Last Synced: 2024-08-16T19:38:11.786Z (4 months ago)
• Topics: benchmark, mkl-umath, numpy, python
• Language: C++
• Size: 76.2 KB
• Stars: 3
• Watchers: 6
• Forks: 8
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE
  • Security: SECURITY.md

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# Optimization Benchmarks

Collection of performance benchmarks used to present optimizations implemented for Intel(R) Distribution for Python*

## Environment Setup

To install Python environments from Intel channel along with pip-installed packages

- `conda env create -f environments/intel.yaml`

- `conda activate intel_env`

## Run tests

- `python numpy/umath/umath_mem_bench.py -v --size 10 --goal-time 0.01 --repeats 1`

## Run benchmarks

### umath

- To run python benchmarks: `python numpy/umath/umath_mem_bench.py`

- To compile and run native benchmarks (requires `icx`): `make -C numpy/umath`

### Random number generation

- To run python benchmarks: `python numpy/random/rng.py`

- To compile and run native benchmarks (requires `icx`): `make -C numpy/random`

## See also

"[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