An Improvement of the Matrix-Matrix Multiplication Speed using 2D-Tiling and AVX512 Intrinsics for Multi-Core Architectures

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Published: Aug 22, 2021
DOI: https://doi.org/10.55164/ajstr.v24i2.242021
Keywords:
AVX512 OpenMP 2D-tiling Multicore Processing Eigen OpenBLAS

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Nwe Zin Oo
Faculty of Engineering, Prince of Songkla University, Songkhla, 90112, Thailand
Panyayot Chaikan
Faculty of Engineering, Prince of Songkla University, Songkhla, 90112, Thailand

Abstract

Matrix-matrix multiplication is a time-consuming operation in scientific and engineering applications. When the matrix size is large, it will take a lot of computation time, resulting in slow software which is unacceptable in real-time applications. In this paper, 2D-tiling, loop unrolling, data padding, OpenMP directives, and AVX512 intrinsics are utilized to increase the speed of matrix-matrix multiplication on multi-core architectures. Our algorithm, tested on a Core i9-7900X machine, is more than two times faster than the operations offered by the OpenBLAS and Eigen libraries for single and double precision floating-point matrices. We also propose an equation for parameter tuning which allows our algorithm to be adapted to process any size of matrix on CPUs with different cache organizations.

Article Details

Issue
Vol. 24 No. 2 (2021): May - August
Section
Research Articles
Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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