Detailed Information

Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

Improving blocked matrix-matrix multiplication routine by utilizing AVX-512 instructions on intel knights landing and xeon scalable processors

Authors
Park, YoosangKim, RaehyunNguyen, Thi My TuyenChoi, Jaeyoung
Issue Date
Oct-2023
Publisher
Springer
Keywords
AVX-512; Intel Skylake-SP; Intel Xeon Phi; Parallel BLAS; Parallel matrix-matrix multiplication; ScaLAPACK
Citation
Cluster Computing, v.26, no.5, pp.2539 - 2549
Journal Title
Cluster Computing
Volume
26
Number
5
Start Page
2539
End Page
2549
URI
https://scholarworks.bwise.kr/ssu/handle/2018.sw.ssu/41013
DOI
10.1007/s10586-021-03274-8
ISSN
1386-7857
Abstract
In high-performance computing, the general matrix-matrix multiplication (xGEMM) routine is the core of the Level 3 BLAS kernel for effective matrix-matrix multiplication operations. The performance of parallel xGEMM (PxGEMM) is significantly affected by two main factors: the flop rate that can be achieved by calculating the operations and the communication costs for broadcasting submatrices to others. In this study, an approach is proposed to improve and adjust the parallel double-precision general matrix-matrix multiplication (PDGEMM) routine for modern Intel computers such as Knights Landing (KNL) and Xeon Scalable Processors (SKL). The proposed approach consists of two methods to deal with the aforementioned factors. First, the improvement of PDGEMM for the computational part is suggested based on a blocked GEMM algorithm that provides better fits for the architectures of KNL and SKL to perform better block size computation. Second, a communication routine adjustment with the message passing interface is proposed to overcome the settings of the basic linear algebra communication subprograms to improve the time-wise cost efficiency. Consequently, it is shown that performance improvements are achieved in the case of smaller matrix multiplications on the SKL clusters. © 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
Files in This Item
Go to Link
Appears in
Collections
College of Information Technology > School of Computer Science and Engineering > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher Choi, Jaeyoung photo

Choi, Jaeyoung
College of Information Technology (School of Computer Science and Engineering)
Read more

Altmetrics

Total Views & Downloads

BROWSE