NEON Instruction Set Efficiency and their Use in Coding Theory Problems

Authors: Maria Pashinska-Gadzheva, Iliya Bouyukliev

Language: English

Published/Presented on:

Magazine: Science Series “Innovative STEM Education”, Vol. 6 (2024), pp. 250–254

DOI: 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.

How to cite?

IEEE style: M. Pashinska-Gadzheva and I. Bouyukliev, “NEON Instruction Set Efficiency and their Use in Coding Theory Problems,” Science Series “Innovative STEM Education”, vol. 6, pp. 250–254, 2024, doi: 10.55630/STEM.2024.0628.

Chicago style: Pashinska-Gadzheva, Maria, and Iliya Bouyukliev. “NEON Instruction Set Efficiency and Their Use in Coding Theory Problems.” Science Series “Innovative STEM Education” 6 (2024): 250–254. https://doi.org/10.55630/STEM.2024.0628.

APA style: Pashinska-Gadzheva, M., & Bouyukliev, I. (2024). NEON instruction set efficiency and their use in coding theory problems. Science Series “Innovative STEM Education,” 6, 250–254. https://doi.org/10.55630/STEM.2024.0628