{"title":"A Scalable Multi-engine Xpress9 Compressor with Asynchronous Data Transfer","authors":"Joo-Young Kim, S. Hauck, D. Burger","doi":"10.1109/FCCM.2014.49","DOIUrl":null,"url":null,"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.","PeriodicalId":246162,"journal":{"name":"2014 IEEE 22nd Annual International Symposium on Field-Programmable Custom Computing Machines","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE 22nd Annual International Symposium on Field-Programmable Custom Computing Machines","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FCCM.2014.49","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 12
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.
在大型存储服务器中,数据压缩对于节省存储和网络带宽至关重要,但其计算成本较高。在这项工作中,我们提出了一个基于FPGA的高吞吐量压缩器作为PCIe加速器,以实现CPU资源的节省和高功耗效率。该压缩器与以往的硬件压缩器有以下特点:1)针对Xpress9算法,其压缩质量可与最好的Gzip实现(9级)相媲美;2)具有不同IP块的可扩展多引擎架构,以处理算法复杂性并实现高吞吐量;3)支持重度多线程服务器环境,在主机和加速器之间提供异步数据传输接口。在Altera Stratix V GS上实现的Xpress9压缩器在不同的压缩基准下,在7个引擎上执行1.6-2.4Gbps的吞吐量,支持多达128个线程上下文。