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FastMatMul

Exploring how to multiply matrices fast.

Performance overview

Algorithm GLOP/s %
C / GCC: Naive 0.33 0.13
C / GCC: Loop order optimized 9.28 3.7
Numpy 250 100
CBLAS (sGEMM) 320 100

Compilation

This project uses GNU Make to automate the compilation process. In order to use the full functionality it is required to have OpenBLAS installed in .\lib. If the library is not available only the parts of the program that do not depend on it will be compiled.

Run the program

$ make run

Run the tests

$ make test

Benchmarking

The Python file benchmark.py encapsulates building the benchmarking program and plotting the data.

$ python benchmark.py

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Exploring how to multiply matrices fast

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