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• W2118906989 abstract "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." @default.
• W2118906989 created "2016-06-24" @default.
• W2118906989 creator A5055794856 @default.
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• W2118906989 date "2011-01-01" @default.
• W2118906989 modified "2023-09-26" @default.
• W2118906989 title "Floating-point data compression at 75 Gb/s on a GPU" @default.
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• W2118906989 doi "https://doi.org/10.1145/1964179.1964189" @default.
• W2118906989 hasPublicationYear "2011" @default.
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