An efficient implementation of parallel simulated annealing algorithm in GPUs

TL;DR

This paper presents a highly optimized GPU implementation of the simulated annealing algorithm using CUDA, including sequential, asynchronous, and synchronous versions, with benchmarking on the Schwefel function and a hybrid approach for improved performance.

Contribution

The paper introduces a novel, efficient GPU-based implementation of simulated annealing with multiple parallel versions and a hybrid method, enhancing performance for large-scale optimization problems.

Findings

Synchronous GPU version outperforms asynchronous in convergence and accuracy.

Benchmark results show significant speedup over CPU implementations.

Hybrid method improves solution quality and computational efficiency.

Abstract

In this work we propose a highly optimized version of a simulated annealing (SA) algorithm adapted to the more recently developed Graphic Processor Units (GPUs). The programming has been carried out with CUDA toolkit, specially designed for Nvidia GPUs. For this purpose, efficient versions of SA have been first analyzed and adapted to GPUs. Thus, an appropriate sequential SA algorithm has been developed as a starting point. Next, a straightforward asynchronous parallel version has been implemented and then a specific and more efficient synchronous version has been developed. A wide appropriate benchmark to illustrate the performance properties of the implementation has been considered. Among all tests, a classical sample problem provided by the minimization of the normalized Schwefel function has been selected to compare the behavior of the sequential, asynchronous, and synchronous versions, the last one being more advantageous in terms of balance between convergence, accuracy, and computational cost. Also, the implementation of a hybrid method combining SA with a local minimizer method has been developed. Note that the generic feature of the SA algorithm allows its application in a wide set of real problems arising in a large variety of fields, such as biology, physics, engineering, finance, and industrial processes.