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Harnessing the power of idle GPUs for acceleration of biological sequence alignment

Fumihiko Ino, Yuki Kotani, Yuma Munekawa, Kenichi Hagihara
Graduate School of Information Science and Technology, Osaka University, 1-5 Yamada-oka, Suita, 565-0871 Osaka, Japan
IEEE International Symposium on Parallel & Distributed Processing, 2009. IPDPS 2009

@article{ino2009harnessing,

   title={Harnessing the power of idle GPUs for acceleration of biological sequence alignment},

   author={Ino, F. and Kotani, Y. and Hagihara, K.},

   year={2009},

   publisher={IEEE}

}

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This paper presents a parallel system capable of accelerating biological sequence alignment on the graphics processing unit (GPU) grid. The GPU grid in this paper is a desktop grid system that utilizes idle GPUs and CPUs in the office and home. Our parallel implementation employs a master-worker paradigm to accelerate Liu’s OpenGL-based algorithm that runs on a single GPU. We integrate this implementation into a screensaver-based grid system that detects idle resources on which the alignment code can run. We also show some experimental results comparing our implementation with three different implementations running on a single GPU, a single CPU, or multiple CPUs. As a result, we find that a single non-dedicated GPU can provide us almost the same throughput as two dedicated CPUs in our laboratory environment, where GPU-equipped machines are ordinarily used to develop GPU applications.
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