Benchmark computing Black Scholes formula using different technologies
icc
, if compiling native benchmarks. Intel Distribution for Python* 2019 Gold benchmarks used icc 17.0.1.mkl
, if compiling native benchmarks with MKL.
- Run
. activate-conda.sh
to install miniconda on Linux and Mac - Run
make
to build and run native benchmarks- Run
make mkl
to build and run MKL version - Run
make nomkl
to build and run non-MKL version - Run
make black_scholes_mkl
to only build MKL version - Run
make black_scholes
to only build non-MKL version
- Run
- Download & install Miniconda3 and MSYS2
- Run bash from MSYS2 and activate miniconda environment
- Run
./install-conda-envs.sh
to install Python environments
- Non-MKL version: Run the compiled binary
./black_scholes
. - MKL version: Run the compiled binary
./black_scholes_mkl
.
usage: {bs_erf_*.py|run.sh} [-h]
[--steps STEPS] [--step STEP] [--chunk CHUNK]
[--size SIZE] [--repeat REPEAT] [--dask DASK]
[--text TEXT]
optional arguments:
-h, --help show this help message and exit
--steps STEPS Number of steps
--step STEP Factor for each step
--chunk CHUNK Chunk size for Dask
--size SIZE Initial data size
--repeat REPEAT Iterations inside measured region
--dask DASK Dask scheduler: sq, mt, mp
--text TEXT Print with each result
"Accelerating Scientific Python with Intel Optimizations" 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