CrystalGPU: Transparent and Efficient Utilization of GPU Power

Abdullah Gharaibeh, Samer Al-Kiswany, Matei Ripeanu
Electrical and Computer Engineering Department, The University of British Columbia
arXiv:1005.1695v1 [cs.OH] (11 May 2010)


   title={CrystalGPU: Transparent and Efficient Utilization of GPU Power},

   author={Gharaibeh, A. and Al-Kiswany, S. and Ripeanu, M.},

   journal={Arxiv preprint arXiv:1005.1695},



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General-purpose computing on graphics processing units (GPGPU) has recently gained considerable attention in various domains such as bioinformatics, databases and distributed computing. GPGPU is based on using the GPU as a co-processor accelerator to offload computationally-intensive tasks from the CPU. This study starts from the observation that a number of GPU features (such as overlapping communication and computation, short lived buffer reuse, and harnessing multi-GPU systems) can be abstracted and reused across different GPGPU applications. This paper describes CrystalGPU, a modular framework that transparently enables applications to exploit a number of GPU optimizations. Our evaluation shows that CrystalGPU enables up to 16x speedup gains on synthetic benchmarks, while introducing negligible latency overhead.
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