Presentation 2010-09-16
Hardware Lossless-Compressors of Floating-Point Data Streams to Enhance Memory Bandwidth
Kentaro SANO, Kazuya KATAHIRA, Satoru YAMAMOTO,
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Abstract(in English) This paper presents an FPGA-based lossless compressor that directly compresses floating-point data streams to enhance the effective memory bandwidth of a lattice Boltzmann method (LBM) accelerator. We show that the compression algorithms based on the 1D polynomial prediction are suitable for high-throughput hardware design. Moreover we show that integer operations provide comparable prediction performance to a floating-point predictor, while an integer predictor is expected to have smaller circuits than a floating-point one. We evaluate the compression ratio, the operating frequency and the resource consumption of the compressors with integer-based predictors through their prototype implementation using ALTERA Stratix III FPGA. We demonstrate that the implemented compressors dominate only 0.15 to 0.23 % of the entire logic resources and operate at 95 to 174 MHz to provide the compression ratio of up to 3.5, which means that we can enhance the memory bandwidth by a factor of 3.5 on average.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Lossless Data Compression / Floating-Point Data / Memory Bandwidth / Stream Computation
Paper # RECONF2010-24
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Conference Information
Committee RECONF
Conference Date 2010/9/9(1days)
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Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Hardware Lossless-Compressors of Floating-Point Data Streams to Enhance Memory Bandwidth
Sub Title (in English)
Keyword(1) Lossless Data Compression
Keyword(2) Floating-Point Data
Keyword(3) Memory Bandwidth
Keyword(4) Stream Computation
1st Author's Name Kentaro SANO
1st Author's Affiliation Graduate School of Information Sciences, Tohoku University()
2nd Author's Name Kazuya KATAHIRA
2nd Author's Affiliation Graduate School of Information Sciences, Tohoku University
3rd Author's Name Satoru YAMAMOTO
3rd Author's Affiliation Graduate School of Information Sciences, Tohoku University
Date 2010-09-16
Paper # RECONF2010-24
Volume (vol) vol.110
Number (no) 204
Page pp.pp.-
#Pages 6
Date of Issue