A Predictable SIMD Library for GEMM Routines - ANITI - Artificial and Natural Intelligence Toulouse Institute Accéder directement au contenu
Communication Dans Un Congrès Année : 2024

A Predictable SIMD Library for GEMM Routines

Résumé

The resource-constrained environment and the certification requirements underlying embedded safety-critical real-time systems impose an adapted development process for software applications. In this work, we propose an efficient and traceable implementation of an existing blocked general matrix multiplication (GEMM) algorithm. We target time-predictability in a COTS processor with single-instruction multiple-data (SIMD) extensions. We provide a set of rules for tuning the algorithm parameters and predict with precision its number of memory accesses and cache misses, which paves the way for a static WCET analysis. Our experiments show that time-predictability comes at the cost of a performance degradation of only 2.54% on average. Moreover, tuning the parameters allows for reducing cache misses by up to 60% in certain parts of the algorithm.
Fichier principal
Vignette du fichier
Predictable_GEMM.pdf (420.12 Ko) Télécharger le fichier
Origine Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-04660701 , version 1 (24-07-2024)

Identifiants

Citer

Iryna De Albuquerque Silva, Thomas Carle, Adrien Gauffriau, Victor Jegu, Claire Pagetti. A Predictable SIMD Library for GEMM Routines. 2024 IEEE 30th Real-Time and Embedded Technology and Applications Symposium (RTAS), May 2024, Hong Kong, Hong Kong SAR China. pp.55-67, ⟨10.1109/RTAS61025.2024.00013⟩. ⟨hal-04660701⟩
0 Consultations
0 Téléchargements

Altmetric

Partager

Gmail Mastodon Facebook X LinkedIn More