Massively parallel CMA-ES with increasing population - CRIStAL - Calcul Formel et Haute Performance
Pré-Publication, Document De Travail Année : 2024

Massively parallel CMA-ES with increasing population

Résumé

The Increasing Population Covariance Matrix Adaptation Evolution Strategy (IPOP-CMA-ES) algorithm is a reference stochastic optimizer dedicated to blackbox optimization, where no prior knowledge about the underlying problem structure is available. This paper aims at accelerating IPOP-CMA-ES thanks to high performance computing and parallelism when solving large optimization problems. We first show how BLAS and LAPACK routines can be introduced in linear algebra operations, and we then propose two strategies for deploying IPOP-CMA-ES efficiently on large-scale parallel architectures with thousands of CPU cores. The first parallel strategy processes the multiple searches in the same ordering as the sequential IPOP-CMA-ES, while the second one processes concurrently these multiple searches. These strategies are implemented in MPI+OpenMP and compared on 6144 cores of the supercomputer Fugaku. We manage to obtain substantial speedups (up to several thousand) and even super-linear ones, and we provide an in-depth analysis of our results to understand precisely the superior performance of our second strategy.

Fichier principal
Vignette du fichier
main-HAL.pdf (609.73 Ko) Télécharger le fichier
Origine Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-04698736 , version 1 (16-09-2024)

Identifiants

Citer

David Redon, Pierre Fortin, Bilel Derbel, Miwako Tsuji, Mitsuhisa Sato. Massively parallel CMA-ES with increasing population. 2024. ⟨hal-04698736⟩
0 Consultations
0 Téléchargements

Altmetric

Partager

More