W. Liao, Kenin Coloma, A. Choudhary, L. Ward, E. Russell, Sonja Tideman
{"title":"集体缓存:应用程序感知的客户端文件缓存","authors":"W. Liao, Kenin Coloma, A. Choudhary, L. Ward, E. Russell, Sonja Tideman","doi":"10.1109/HPDC.2005.1520940","DOIUrl":null,"url":null,"abstract":"Parallel file subsystems in today's high-performance computers adopt many I/O optimization strategies that were designed for distributed systems. These strategies, for instance client-side file caching, treat each I/O request process independently, due to the consideration that clients are unlikely related with each other in a distributed environment. However, it is inadequate to apply such strategies directly in the high-performance computers where most of the I/O requests come from the processes that work on the same parallel applications. We believe that client-side caching could perform more effectively if the caching subsystem is aware of the process scope of an application and regards all the application processes as a single client. In this paper, we propose the idea of \"collective caching\" which coordinates the application processes to manage cache data and achieve cache coherence without involving the I/O servers. To demonstrate this idea, we implemented a collective caching subsystem at user space as a library, which can be incorporated into any message passing interface implementation to increase its portability. The performance evaluation is presented with three I/O benchmarks on an IBM SP using its native parallel file system, GPFS. Our results show significant performance enhancement obtained by collective caching over the traditional approaches.","PeriodicalId":120564,"journal":{"name":"HPDC-14. Proceedings. 14th IEEE International Symposium on High Performance Distributed Computing, 2005.","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"68","resultStr":"{\"title\":\"Collective caching: application-aware client-side file caching\",\"authors\":\"W. Liao, Kenin Coloma, A. Choudhary, L. Ward, E. Russell, Sonja Tideman\",\"doi\":\"10.1109/HPDC.2005.1520940\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Parallel file subsystems in today's high-performance computers adopt many I/O optimization strategies that were designed for distributed systems. These strategies, for instance client-side file caching, treat each I/O request process independently, due to the consideration that clients are unlikely related with each other in a distributed environment. However, it is inadequate to apply such strategies directly in the high-performance computers where most of the I/O requests come from the processes that work on the same parallel applications. We believe that client-side caching could perform more effectively if the caching subsystem is aware of the process scope of an application and regards all the application processes as a single client. In this paper, we propose the idea of \\\"collective caching\\\" which coordinates the application processes to manage cache data and achieve cache coherence without involving the I/O servers. To demonstrate this idea, we implemented a collective caching subsystem at user space as a library, which can be incorporated into any message passing interface implementation to increase its portability. The performance evaluation is presented with three I/O benchmarks on an IBM SP using its native parallel file system, GPFS. Our results show significant performance enhancement obtained by collective caching over the traditional approaches.\",\"PeriodicalId\":120564,\"journal\":{\"name\":\"HPDC-14. Proceedings. 14th IEEE International Symposium on High Performance Distributed Computing, 2005.\",\"volume\":\"27 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2005-07-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"68\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"HPDC-14. Proceedings. 14th IEEE International Symposium on High Performance Distributed Computing, 2005.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HPDC.2005.1520940\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"HPDC-14. Proceedings. 14th IEEE International Symposium on High Performance Distributed Computing, 2005.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HPDC.2005.1520940","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Parallel file subsystems in today's high-performance computers adopt many I/O optimization strategies that were designed for distributed systems. These strategies, for instance client-side file caching, treat each I/O request process independently, due to the consideration that clients are unlikely related with each other in a distributed environment. However, it is inadequate to apply such strategies directly in the high-performance computers where most of the I/O requests come from the processes that work on the same parallel applications. We believe that client-side caching could perform more effectively if the caching subsystem is aware of the process scope of an application and regards all the application processes as a single client. In this paper, we propose the idea of "collective caching" which coordinates the application processes to manage cache data and achieve cache coherence without involving the I/O servers. To demonstrate this idea, we implemented a collective caching subsystem at user space as a library, which can be incorporated into any message passing interface implementation to increase its portability. The performance evaluation is presented with three I/O benchmarks on an IBM SP using its native parallel file system, GPFS. Our results show significant performance enhancement obtained by collective caching over the traditional approaches.