Performance and energy consumption of the SIMD Gram–Schmidt process for vector orthogonalization

Title data

Jakobs, Thomas ; Naumann, Billy ; Rünger, Gudula:
Performance and energy consumption of the SIMD Gram–Schmidt process for vector orthogonalization.
In: The Journal of Supercomputing. Vol. 76 (2020) . - pp. 1999-2021.
ISSN 1573-0484
DOI: https://doi.org/10.1007/s11227-019-02839-0

Official URL:

Abstract in another language

In linear algebra and numerical computing, the orthogonalization of a set of vectors is an important submethod. Thus, the efficient implementation on recent architectures is required to provide a useful kernel for high-performance applications. In this article, we consider the process of orthogonalizing a set of vectors with the Gram–Schmidt method and develop SIMD implementations for processors providing the Advanced Vector Extensions (AVX), which is a set of instructions for SIMD execution on recent Intel and AMD CPUs. Several SIMD implementations of the Gram–Schmidt process for vector orthogonalization are built, and their behavior with respect to performance and energy is investigated. Especially, different ways to implement the SIMD programs are proposed and several optimizations have been studied. As hardware platforms, the Intel Core, Xeon and Xeon Phi processors with the AVX versions AVX, AVX2 and AVX512 have been used.

Further data

Item Type:	Article in a journal
Refereed:	Yes
Institutions of the University:	Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science > Chair Applied Computer Science II > Chair Applied Computer Science II - Univ.-Prof. Dr. Thomas Rauber Faculties Faculties > Faculty of Mathematics, Physics und Computer Science Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science > Chair Applied Computer Science II
Result of work at the UBT:	No
DDC Subjects:	000 Computer Science, information, general works > 004 Computer science
Date Deposited:	10 Aug 2021 12:07
Last Modified:	07 Apr 2022 12:06
URI:	https://eref.uni-bayreuth.de/id/eprint/66752