EASEA: specification and execution of evolutionary algorithms on GPGPU
Soft Computing, 2012•Springer
EASEA is a framework designed to help non-expert programmers to optimize their problems
by evolutionary computation. It allows to generate code targeted for standard CPU
architectures, GPGPU-equipped machines as well as distributed memory clusters. In this
paper, EASEA is presented by its underlying algorithms and by some example problems.
Achievable speedups are also shown onto different NVIDIA GPGPUs cards for different
optimization algorithm families.
by evolutionary computation. It allows to generate code targeted for standard CPU
architectures, GPGPU-equipped machines as well as distributed memory clusters. In this
paper, EASEA is presented by its underlying algorithms and by some example problems.
Achievable speedups are also shown onto different NVIDIA GPGPUs cards for different
optimization algorithm families.
Abstract
EASEA is a framework designed to help non-expert programmers to optimize their problems by evolutionary computation. It allows to generate code targeted for standard CPU architectures, GPGPU-equipped machines as well as distributed memory clusters. In this paper, EASEA is presented by its underlying algorithms and by some example problems. Achievable speedups are also shown onto different NVIDIA GPGPUs cards for different optimization algorithm families.
Springer