DOI: 10.1080/17445760.2021.1941010
Study and Evaluation of Improved Automatic GPU Offloading Method
DOI:
https://doi.org/10.51094/jxiv.1027Keywords:
Environment Adaptive Software, GPGPU, Automatic Offloadin, Performance, Evolutionary ComputationAbstract
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.
Y. Yamato, "Study and Evaluation of Improved Automatic GPU Offloading Method," International Journal of Parallel, Emergent and Distributed Systems, Taylor & Francis, Jun. 2021.
Conflicts of Interest Disclosure
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Submitted: 2025-01-05 04:52:29 UTC
Published: 2025-01-09 01:42:22 UTC
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Yoji Yamato
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