Title :

Massively parallel CMA-ES with increasing population

Author(s) :

Redon, David [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Optimisation de grande taille et calcul large échelle [BONUS]
Fortin, Pierre [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Optimisation de grande taille et calcul large échelle [BONUS]
Derbel, Bilel [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Optimisation de grande taille et calcul large échelle [BONUS]
Tsuji, Miwako [Auteur]
RIKEN Center for Computational Science [Kobe] [RIKEN CCS]
Sato, Mitsuhisa [Auteur]
RIKEN Center for Computational Science [Kobe] [RIKEN CCS]

Publication date :

2024-09-16

English keyword(s) :

Parallel Optimization Blackbox Optimization Local Optimization Large-Scale Parallelism BLAS
Parallel Optimization
Blackbox Optimization
Local Optimization
Large-Scale Parallelism
BLAS

HAL domain(s) :

Informatique [cs]/Calcul parallèle, distribué et partagé [cs.DC]

English abstract : [en]

<div><p>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 ...
Show more ><div><p>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.</p></div>Show less >

Language :

Anglais

Collections :

• Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189

Source :

Harvested from HAL

Submission date :

2024-09-19T02:03:07Z