B. Nouanesengsy, J. Patchett, J. Ahrens, A. Bauer, Aashish Chaudhary, Ross G. Miller, Berk Geveci, G. Shipman, Dean N. Williams
{"title":"一个使用时空并行性优化文件访问模式的模型","authors":"B. Nouanesengsy, J. Patchett, J. Ahrens, A. Bauer, Aashish Chaudhary, Ross G. Miller, Berk Geveci, G. Shipman, Dean N. Williams","doi":"10.1145/2535571.2535593","DOIUrl":null,"url":null,"abstract":"For many years now, I/O read time has been recognized as the primary bottleneck for parallel visualization and analysis of large-scale data. In this paper, we introduce a model that can estimate the read time for a file stored in a parallel filesystem when given the file access pattern. Read times ultimately depend on how the file is stored and the access pattern used to read the file. The file access pattern will be dictated by the type of parallel decomposition used. We employ spatio-temporal parallelism, which combines both spatial and temporal parallelism, to provide greater flexibility to possible file access patterns. Using our model, we were able to configure the spatio-temporal parallelism to design optimized read access patterns that resulted in a speedup factor of approximately 400 over traditional file access patterns.","PeriodicalId":262085,"journal":{"name":"Proceedings of the 8th International Workshop on Ultrascale Visualization","volume":"4613 3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A model for optimizing file access patterns using spatio-temporal parallelism\",\"authors\":\"B. Nouanesengsy, J. Patchett, J. Ahrens, A. Bauer, Aashish Chaudhary, Ross G. Miller, Berk Geveci, G. Shipman, Dean N. Williams\",\"doi\":\"10.1145/2535571.2535593\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"For many years now, I/O read time has been recognized as the primary bottleneck for parallel visualization and analysis of large-scale data. In this paper, we introduce a model that can estimate the read time for a file stored in a parallel filesystem when given the file access pattern. Read times ultimately depend on how the file is stored and the access pattern used to read the file. The file access pattern will be dictated by the type of parallel decomposition used. We employ spatio-temporal parallelism, which combines both spatial and temporal parallelism, to provide greater flexibility to possible file access patterns. Using our model, we were able to configure the spatio-temporal parallelism to design optimized read access patterns that resulted in a speedup factor of approximately 400 over traditional file access patterns.\",\"PeriodicalId\":262085,\"journal\":{\"name\":\"Proceedings of the 8th International Workshop on Ultrascale Visualization\",\"volume\":\"4613 3 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-11-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 8th International Workshop on Ultrascale Visualization\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2535571.2535593\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 8th International Workshop on Ultrascale Visualization","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2535571.2535593","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A model for optimizing file access patterns using spatio-temporal parallelism
For many years now, I/O read time has been recognized as the primary bottleneck for parallel visualization and analysis of large-scale data. In this paper, we introduce a model that can estimate the read time for a file stored in a parallel filesystem when given the file access pattern. Read times ultimately depend on how the file is stored and the access pattern used to read the file. The file access pattern will be dictated by the type of parallel decomposition used. We employ spatio-temporal parallelism, which combines both spatial and temporal parallelism, to provide greater flexibility to possible file access patterns. Using our model, we were able to configure the spatio-temporal parallelism to design optimized read access patterns that resulted in a speedup factor of approximately 400 over traditional file access patterns.