Evaluation of GPU Logic Reconfiguration after Service Start

Abstract

In order to make full use of heterogeneous hardware, it is necessary to have a technical skill of hardware such as CUDA, and the current situation is that the barrier is high. Based on this background, I have proposed environment-adaptive software that enables high-performance operation by automatically converting application code written for normal CPUs by engineers according to the deployed environment and setting appropriate amount of resources. Until now, I only considered conversions and settings before operation. In this paper, I verify that the logic is reconfigured according to the usage characteristics during operation. I confirm that the application running on the GPU is reconfigured into other loops or applications offloading according to the usage trends.