P. Nowoczynski, N. Stone, J. Yanovich, J. Sommerfield
{"title":"Zest Checkpoint storage system for large supercomputers","authors":"P. Nowoczynski, N. Stone, J. Yanovich, J. Sommerfield","doi":"10.1109/PDSW.2008.4811883","DOIUrl":null,"url":null,"abstract":"The PSC has developed a prototype distributed file system infrastructure that vastly accelerates aggregated write bandwidth on large compute platforms. Write bandwidth, more than read bandwidth, is the dominant bottleneck in HPC I/O scenarios due to writing checkpoint data, visualization data and post-processing (multi-stage) data. We have prototyped a scalable solution that will be directly applicable to future petascale compute platforms having of order 10^6 cores. Our design emphasizes high-efficiency scalability, low-cost commodity components, lightweight software layers, end-to-end parallelism, client-side caching and software parity, and a unique model of load-balancing outgoing I/O onto high-speed intermediate storage followed by asynchronous reconstruction to a 3rd-party parallel file system.","PeriodicalId":227342,"journal":{"name":"2008 3rd Petascale Data Storage Workshop","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"34","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 3rd Petascale Data Storage Workshop","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PDSW.2008.4811883","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 34
Abstract
The PSC has developed a prototype distributed file system infrastructure that vastly accelerates aggregated write bandwidth on large compute platforms. Write bandwidth, more than read bandwidth, is the dominant bottleneck in HPC I/O scenarios due to writing checkpoint data, visualization data and post-processing (multi-stage) data. We have prototyped a scalable solution that will be directly applicable to future petascale compute platforms having of order 10^6 cores. Our design emphasizes high-efficiency scalability, low-cost commodity components, lightweight software layers, end-to-end parallelism, client-side caching and software parity, and a unique model of load-balancing outgoing I/O onto high-speed intermediate storage followed by asynchronous reconstruction to a 3rd-party parallel file system.