Study and evaluation of improved automatic GPU offloading method. Issue 6 (2nd November 2021)

• Record Type: Journal Article
• Authors: Yamato, Yoji
• Is Part Of: International journal of parallel, emergent and distributed systems. Volume 36:Issue 6(2021)
• Page Start: 594
• Page End: 608
• Publication Date: 2021-11-02
• Subjects: Environment adaptive software -- GPGPU -- automatic offloading -- Performance -- evolutionary computation; Parallel computers -- Periodicals; Electronic data processing -- Distributed processing -- Periodicals; Computer algorithms -- Periodicals; 004.35
• DOI: 10.1080/17445760.2021.1941010
• Languages: English
• ISSNs: 1744-5760

Abstract

Abstract : With the slowing down of Moore's law, the use of hardware other than CPUs, such as graphics processing units (GPUs) or field-Programmable gate arrays (FPGAs), is increasing. However, when using heterogeneous hardware other than CPUs, barriers to technical skills, such for compute unified device architecture (CUDA) and open computing language (OpenCL), are high. Therefore, I previously proposed environment adaptive software that enables automatic conversion, configuration, and high-performance operation of once written code according to the hardware to be placed. As part of environment adaptive software, I also proposed a method to offload loop statements of applications to GPUs automatically. In this paper, I improved upon this automatic GPU offloading method to expand its applicability to more applications and enhance offloading performance. I implemented the improved method to evaluate its effectiveness for multiple applications. GRAPHICAL ABSTRACT: UF0001