A Fine-grained parallel snappy decompressor for FPGAS using a relaxed execution model

Jian Fang; Jianyu Chen; Jinho Lee; Zaid Al-Ars; H. Peter Hofstee

doi:10.1109/FCCM.2019.00076

A Fine-grained parallel snappy decompressor for FPGAS using a relaxed execution model

Jian Fang, Jianyu Chen, Jinho Lee, Zaid Al-Ars, H. Peter Hofstee

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

4 Citations (Scopus)

Abstract

Snappy is a widely used (de) compression algorithm in many big data applications. Such a data compression technique has been proven to be successful to save storage space and to reduce the amount of data transmission from/to storage devices. In this paper, we present a fine-grained parallel Snappy decompressor on FPGAs running under a relaxed execution model that addresses the following main challenges in existing solutions. First, existing designs either can only process one token per cycle or can process multiple tokens per cycle with low area efficiency and/or low clock frequency. Second, the high read-After-write data dependency during decompression introduces stalls which pull down the throughput.

Original language	English
Title of host publication	Proceedings - 27th IEEE International Symposium on Field-Programmable Custom Computing Machines, FCCM 2019
Publisher	Institute of Electrical and Electronics Engineers Inc.
Number of pages	1
ISBN (Electronic)	9781728111315
DOIs	https://doi.org/10.1109/FCCM.2019.00076
Publication status	Published - 2019 Apr
Event	27th Annual IEEE International Symposium on Field-Programmable Custom Computing Machines, FCCM 2019 - San Diego, United States Duration: 2019 Apr 28 → 2019 May 1

Publication series

Name	Proceedings - 27th IEEE International Symposium on Field-Programmable Custom Computing Machines, FCCM 2019

Conference

Conference	27th Annual IEEE International Symposium on Field-Programmable Custom Computing Machines, FCCM 2019
Country/Territory	United States
City	San Diego
Period	19/4/28 → 19/5/1

All Science Journal Classification (ASJC) codes

Computer Science Applications
Hardware and Architecture

Access to Document

10.1109/FCCM.2019.00076

Cite this

Fang, J., Chen, J., Lee, J., Al-Ars, Z., & Hofstee, H. P. (2019). A Fine-grained parallel snappy decompressor for FPGAS using a relaxed execution model. In Proceedings - 27th IEEE International Symposium on Field-Programmable Custom Computing Machines, FCCM 2019 [8735518] (Proceedings - 27th IEEE International Symposium on Field-Programmable Custom Computing Machines, FCCM 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/FCCM.2019.00076

Fang, Jian ; Chen, Jianyu ; Lee, Jinho et al. / A Fine-grained parallel snappy decompressor for FPGAS using a relaxed execution model. Proceedings - 27th IEEE International Symposium on Field-Programmable Custom Computing Machines, FCCM 2019. Institute of Electrical and Electronics Engineers Inc., 2019. (Proceedings - 27th IEEE International Symposium on Field-Programmable Custom Computing Machines, FCCM 2019).

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title = "A Fine-grained parallel snappy decompressor for FPGAS using a relaxed execution model",

abstract = "Snappy is a widely used (de) compression algorithm in many big data applications. Such a data compression technique has been proven to be successful to save storage space and to reduce the amount of data transmission from/to storage devices. In this paper, we present a fine-grained parallel Snappy decompressor on FPGAs running under a relaxed execution model that addresses the following main challenges in existing solutions. First, existing designs either can only process one token per cycle or can process multiple tokens per cycle with low area efficiency and/or low clock frequency. Second, the high read-After-write data dependency during decompression introduces stalls which pull down the throughput.",

author = "Jian Fang and Jianyu Chen and Jinho Lee and Zaid Al-Ars and Hofstee, {H. Peter}",

year = "2019",

month = apr,

doi = "10.1109/FCCM.2019.00076",

language = "English",

series = "Proceedings - 27th IEEE International Symposium on Field-Programmable Custom Computing Machines, FCCM 2019",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "Proceedings - 27th IEEE International Symposium on Field-Programmable Custom Computing Machines, FCCM 2019",

address = "United States",

note = "27th Annual IEEE International Symposium on Field-Programmable Custom Computing Machines, FCCM 2019 ; Conference date: 28-04-2019 Through 01-05-2019",

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Fang, J, Chen, J, Lee, J, Al-Ars, Z & Hofstee, HP 2019, A Fine-grained parallel snappy decompressor for FPGAS using a relaxed execution model. in Proceedings - 27th IEEE International Symposium on Field-Programmable Custom Computing Machines, FCCM 2019., 8735518, Proceedings - 27th IEEE International Symposium on Field-Programmable Custom Computing Machines, FCCM 2019, Institute of Electrical and Electronics Engineers Inc., 27th Annual IEEE International Symposium on Field-Programmable Custom Computing Machines, FCCM 2019, San Diego, United States, 19/4/28. https://doi.org/10.1109/FCCM.2019.00076

A Fine-grained parallel snappy decompressor for FPGAS using a relaxed execution model. / Fang, Jian; Chen, Jianyu; Lee, Jinho et al.

Proceedings - 27th IEEE International Symposium on Field-Programmable Custom Computing Machines, FCCM 2019. Institute of Electrical and Electronics Engineers Inc., 2019. 8735518 (Proceedings - 27th IEEE International Symposium on Field-Programmable Custom Computing Machines, FCCM 2019).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AB - Snappy is a widely used (de) compression algorithm in many big data applications. Such a data compression technique has been proven to be successful to save storage space and to reduce the amount of data transmission from/to storage devices. In this paper, we present a fine-grained parallel Snappy decompressor on FPGAs running under a relaxed execution model that addresses the following main challenges in existing solutions. First, existing designs either can only process one token per cycle or can process multiple tokens per cycle with low area efficiency and/or low clock frequency. Second, the high read-After-write data dependency during decompression introduces stalls which pull down the throughput.

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M3 - Conference contribution

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Fang J, Chen J, Lee J, Al-Ars Z, Hofstee HP. A Fine-grained parallel snappy decompressor for FPGAS using a relaxed execution model. In Proceedings - 27th IEEE International Symposium on Field-Programmable Custom Computing Machines, FCCM 2019. Institute of Electrical and Electronics Engineers Inc. 2019. 8735518. (Proceedings - 27th IEEE International Symposium on Field-Programmable Custom Computing Machines, FCCM 2019). doi: 10.1109/FCCM.2019.00076

A Fine-grained parallel snappy decompressor for FPGAS using a relaxed execution model

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