Autor(s):

Maria Pashinska-Gadzheva, Institute of Mathematics and Informatics, Bulgarian Academy of Sciences, Sofia, Bulgaria, mariqpashinska@math.bas.bg

Iliya Bouyukliev, Institute of Mathematics and Informatics, Bulgarian Academy of Sciences, Sofia, Bulgaria, iliyab@math.bas.bg

https://doi.org/10.55630/STEM.2024.0628

Abstract:

    A large number of algorithms solving Coding Theory problems involve operations on vectors over finite fields. The use of extended CPU registers and instructions is suitable for the optimization of these algorithms. Current work presents the Neon instruction set for the ARM architectures used in Apple's M series of processors. A method for their application in algorithms for finding weight characteristics is considered. Some basic similarities and differences with extended vector instructions available in other architectures are presented. Their performance is compared with non-vectorized methods.

Keywords:

Vectorization; NEON Instruction Set;

Received:

15-08-2024

Accepted:

20-12-2024

Published:

26-12-2024

Cite (APA style):

Pashinska-Gadzheva, M., Bouyukliev, I. (2024). NEON Instruction Set Efficiency and their Use in Coding Theory Problems, Science Series "Innovative STEM Education", volume 06, ISSN: 2683-1333, Institute of Mathematics and Informatics – Bulgarian Academy of Sciences, pp. 250-254, DOI: https://doi.org/10.55630/STEM.2024.0628

PDF file address:

http://www.math.bas.bg/vt/stemedu/books/06/STEM.2024.0628.pdf