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Floating-point data compression at 75 Gb/s on a GPU

Molly A. O’Neil, Martin Burtscher
Department of Computer Science, Texas State University-San Marcos
Proceedings of the Fourth Workshop on General Purpose Processing on Graphics Processing Units, GPGPU-4, 2011

@inproceedings{o2011floating,

   title={Floating-point data compression at 75 Gb/s on a GPU},

   author={O’Neil, M.A. and Burtscher, M.},

   booktitle={Proceedings of the Fourth Workshop on General Purpose Processing on Graphics Processing Units},

   pages={7},

   year={2011},

   organization={ACM}

}

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Numeric simulations often generate large amounts of data that need to be stored or sent to other compute nodes. This paper investigates whether GPUs are powerful enough to make real-time data compression and decompression possible in such environments, that is, whether they can operate at the 32- or 40-Gb/s throughput of emerging network cards. The fastest parallel CPU-based floating-point data compression algorithm operates below 20 Gb/s on eight Xeon cores, which is significantly slower than the network speed and thus insufficient for compression to be practical in high-end networks. As a remedy, we have created the highly parallel GFC compression algorithm for double-precision floating-point data. This algorithm is specifically designed for GPUs. It compresses at a minimum of 75 Gb/s, decompresses at 90 Gb/s and above, and can therefore improve internode communication throughput on current and upcoming networks by fully saturating the interconnection links with compressed data.
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