PACUE: Processor allocator considering user experience

Abstract

GPU accelerated applications including GPGPU ones are commonly seen in modern PCs. If many applications compete on the same GPU, the performance will decrease significantly. Some applications have a large impact on user experience. Therefore, for such applications, we have to limit GPU utilization by the other applications. It might be straightforward to modify applications to switch compute device dynamically for intelligent resources allocation. Unfortunately, we cannot do so due to software distribution policy or the other reasons. In this paper, we propose PACUE, which allows the end system to allocate compute devices arbitrary to applications. In addition, PACUE guesses optimal compute device for each application according to user preference. We implemented the dynamic compute device redirector of PACUE including OpenCL API hooking and device camouflaging features. We also implemented the frame of the resource manager of PACUE. We demonstrate PACUE achieves dynamic compute device redirecting on one out of two real applications and on all of 20 sample codes. © 2012 Springer-Verlag Berlin Heidelberg.