Jae-Woo Choi, Youngjin Yu, Hyeonsang Eom, H. Yeom, Dongin Shin
{"title":"SAN Optimization for High Performance Storage with RDMA Data Transfer","authors":"Jae-Woo Choi, Youngjin Yu, Hyeonsang Eom, H. Yeom, Dongin Shin","doi":"10.1109/SC.Companion.2012.15","DOIUrl":null,"url":null,"abstract":"Today's server environments consist of many machines constructing clusters for distributed computing system or storage area networks (SAN) for effectively processing or saving enormous data. In these kinds of server environments, backend-storages are usually the bottleneck of the overall system. But it is not enough to simply replace the devices with better ones to exploit their performance benefits. In other words, proper optimizations are needed to fully utilize their performance gains. In this work, we first applied a high performance device as a backend-storage to the existing SAN solution, and found that it could not utilize the low latency and high bandwidth of the device, especially in case of small sized random I/O pattern even though a high speed network was used. To address this problem, we propose a new design that contains three optimizations: 1) removing software overheads to lower I/O latency; 2) parallelism to utilize the high bandwidth of the device; 3) temporal merge mechanism to reduce network overhead. We implemented them as a prototype and found that our solution makes substantial performance improvements in terms of both the latency and bandwidth.","PeriodicalId":6346,"journal":{"name":"2012 SC Companion: High Performance Computing, Networking Storage and Analysis","volume":"14 1","pages":"24-29"},"PeriodicalIF":0.0000,"publicationDate":"2012-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 SC Companion: High Performance Computing, Networking Storage and Analysis","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SC.Companion.2012.15","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Today's server environments consist of many machines constructing clusters for distributed computing system or storage area networks (SAN) for effectively processing or saving enormous data. In these kinds of server environments, backend-storages are usually the bottleneck of the overall system. But it is not enough to simply replace the devices with better ones to exploit their performance benefits. In other words, proper optimizations are needed to fully utilize their performance gains. In this work, we first applied a high performance device as a backend-storage to the existing SAN solution, and found that it could not utilize the low latency and high bandwidth of the device, especially in case of small sized random I/O pattern even though a high speed network was used. To address this problem, we propose a new design that contains three optimizations: 1) removing software overheads to lower I/O latency; 2) parallelism to utilize the high bandwidth of the device; 3) temporal merge mechanism to reduce network overhead. We implemented them as a prototype and found that our solution makes substantial performance improvements in terms of both the latency and bandwidth.