DocumentCode :
188159
Title :
A Scalable Multi-engine Xpress9 Compressor with Asynchronous Data Transfer
Author :
Joo-Young Kim ; Hauck, Scott ; Burger, Doug
Author_Institution :
Microsoft Res., Redmond, WA, USA
fYear :
2014
fDate :
11-13 May 2014
Firstpage :
161
Lastpage :
164
Abstract :
Data compression is crucial in large-scale storage servers to save both storage and network bandwidth, but it suffers from high computational cost. In this work, we present a high throughput FPGA based compressor as a PCIe accelerator to achieve CPU resource saving and high power efficiency. The proposed compressor is differentiated from previous hardware compressors by the following features: 1) targeting Xpress9 algorithm, whose compression quality is comparable to the best Gzip implementation (level 9); 2) a scalable multi-engine architecture with various IP blocks to handle algorithmic complexity as well as to achieve high throughput; 3) supporting a heavily multi-threaded server environment with an asynchronous data transfer interface between the host and the accelerator. The implemented Xpress9 compressor on Altera Stratix V GS performs 1.6-2.4Gbps throughput with 7 engines on various compression benchmarks, supporting up to 128 thread contexts.
Keywords :
field programmable gate arrays; microprocessor chips; multi-threading; peripheral interfaces; Altera Stratix V GS; CPU resource saving; FPGA based compressor; Gzip implementation; IP blocks; PCIe accelerator; Xpress9 compressor; algorithmic complexity; asynchronous data transfer; asynchronous data transfer interface; data compression; hardware compressors; large-scale storage servers; multithreaded server environment; network bandwidth; scalable multiengine Xpress9 compressor; scalable multiengine architecture; storage bandwidth; Data transfer; Encoding; Engines; Field programmable gate arrays; Hardware; Random access memory; Throughput; FPGA; Huffman encoding; LZ77; Xpress; data compression; hardware accelerator; high throughput;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Field-Programmable Custom Computing Machines (FCCM), 2014 IEEE 22nd Annual International Symposium on
Conference_Location :
Boston, MA
Print_ISBN :
978-1-4799-5110-9
Type :
conf
DOI :
10.1109/FCCM.2014.49
Filename :
6861611
Link To Document :
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