科技报告详细信息
Hard Disk/Solid State Drive Synergy in Support of Data-Intensive Computing
Liu,Ke1  Jiang, Song1  Davis, Kei1 
[1] Los Alamos National Laboratory
关键词: ALIGNMENT;    COMBUSTION;    DESIGN;    EFFICIENCY;    IMAGE PROCESSING;    IMPLEMENTATION;    PERFORMANCE;    SATELLITES;    SIMULATION;   
DOI  :  10.2172/1047078
RP-ID  :  LA-UR-12-23164
PID  :  OSTI ID: 1047078
Others  :  TRN: US201216%%335
美国|英语
来源: SciTech Connect
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【 摘 要 】

Data-intensive applications are becoming increasingly common in high-performance computing. Examples include combustion simulation, human genome analysis, and satellite image processing. Efficient access of data sets is critical to the performance of these applications. Because of the size of the data today's economically feasible approach is to store the data files on an array of hard disks or data servers equipped with hard disks and managed by a parallel file system such as PVFS or Lustre wherein the data is striped over a (large) number of disks for high aggregate I/O throughout. With file striping, a request for a segment of logically contiguous file space is decomposed into multiple sub-requests, each to a different server. While the data unit for this striping is usually reasonably large to benefit disk efficiency, the first and/or last sub-requests can be much smaller than the striping unit if the request does not align with the striping pattern, severely compromising hard disk efficiency and thus application performance. We propose to exploit solid state drives (SSD), whose efficiency is much less sensitive to small random accesses, to enable the alignment of requests to disk with the data striping pattern. In this scheme hard disks mainly serve large, aligned, sequential requests, with SSDs serving small or unaligned requests, thus respecting the relative cost, performance, and durability characteristics of the two media, and thereby achieving synergy in performance/cost. We will describe the design of the proposed scheme, its implementation on CCS-7's Darwin cluster, and performance results.

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