Research and Development of Algorithms for Dispatching Tasks in Distributed Computing Systems

This article delves into heterogeneous computing systems, which employ multi-core processors (CPUs) and graphics processing units (GPUs) concurrently, facilitating efficient handling of resource-intensive tasks demanding substantial computing power. Heterogeneous systems primarily serve to judiciously allocate resources among users and computational processes. The veracity and dependability of the work's outcomes hinge upon the accurate utilization of mathematical tools, findings from experimental studies on heterogeneous SoCs, and practical validation. These systems represent a paradigm shift in computing, leveraging the strengths of both CPUs and GPUs to tackle diverse workloads effectively. By harnessing the parallel processing capabilities of GPUs alongside the general-purpose computing prowess of CPUs, heterogeneous systems optimize performance and throughput, catering to the burgeoning demands of modern computing applications. Through meticulous resource allocation and rigorous validation methodologies, these systems ensure the delivery of reliable and consistent results across a spectrum of tasks. The symbiotic integration of diverse processing units within heterogeneous architectures heralds a new era in computing, empowering users with unparalleled computational capabilities for addressing an array of challenges across various domains.