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 | |
| 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 | United States |
| City | San Diego |
| Period | 19/4/28 → 19/5/1 |
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All Science Journal Classification (ASJC) codes
- Computer Science Applications
- Hardware and Architecture
Cite this
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A Fine-grained parallel snappy decompressor for FPGAS using a relaxed execution model. / Fang, Jian; Chen, Jianyu; Lee, Jinho; Al-Ars, Zaid; Hofstee, H. Peter.
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
TY - GEN
T1 - A Fine-grained parallel snappy decompressor for FPGAS using a relaxed execution model
AU - Fang, Jian
AU - Chen, Jianyu
AU - Lee, Jinho
AU - Al-Ars, Zaid
AU - Hofstee, H. Peter
PY - 2019/4
Y1 - 2019/4
N2 - 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.
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.
UR - http://www.scopus.com/inward/record.url?scp=85068308520&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85068308520&partnerID=8YFLogxK
U2 - 10.1109/FCCM.2019.00076
DO - 10.1109/FCCM.2019.00076
M3 - Conference contribution
AN - SCOPUS:85068308520
T3 - Proceedings - 27th IEEE International Symposium on Field-Programmable Custom Computing Machines, FCCM 2019
BT - Proceedings - 27th IEEE International Symposium on Field-Programmable Custom Computing Machines, FCCM 2019
PB - Institute of Electrical and Electronics Engineers Inc.
ER -