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Inter-Block GPU Communication via Fast Barrier Synchronization

Shucai Xiao, Wu-chun Feng
Department of Electrical and Computer Engineering, Virginia Tech, Blacksburg, Virginia 24061
IEEE International Symposium on Parallel & Distributed Processing (IPDPS), 2010

@conference{xiao2010inter,

   title={Inter-block GPU communication via fast barrier synchronization},

   author={Xiao, S. and Feng, W.},

   booktitle={Parallel & Distributed Processing (IPDPS), 2010 IEEE International Symposium on},

   pages={1–12},

   issn={1530-2075},

   year={2010},

   organization={IEEE}

}

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While GPGPU stands for general-purpose computation on graphics processing units, the lack of explicit support for inter-block communication on the GPU arguably hampers its broader adoption as a general-purpose computing device. Interblock communication on the GPU occurs via global memory and then requires barrier synchronization across the blocks, i.e., inter-block GPU communication via barrier synchronization. Currently, such synchronization is only available via the CPU, which in turn, can incur significant overhead. We propose two approaches for inter-block GPU communication via barrier synchronization: GPU lock-based synchronization and GPU lock-free synchronization. We then evaluate the efficacy of each approach via a micro-benchmark as well as three well-known algorithms – Fast Fourier Transform (FFT), dynamic programming, and bitonic sort. For the micro-benchmark, the experimental results show that our GPU lock-free synchronization performs 8.4 times faster than CPU explicit synchronization and 4.0 times faster than CPU implicit synchronization. When integrated with the FFT, dynamic programming, and bitonic sort algorithms, our GPU lock-free synchronization further improves performance by 10%, 26%, and 40%, respectively, and ultimately delivers an overall speed-up of 70x, 13x, and 24x, respectively.
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