Balancing workload distribution in multicore computing

Abstract

As multicore computing becomes ubiquitous in modern computing systems, efficiently balancing workload distribution across multiple cores remains a critical challenge. This article reviews the key strategies for workload distribution in multicore environments, examines the associated challenges, and discusses future directions for research and development. The focus is on dynamic and static load balancing techniques, the impact of hardware and software heterogeneity, and the role of machine learning in optimizing workload distribution.