Parallel I/O systems represent the most commonly used engineering solution to mitigate the performance mismatch between CPU and disk performance; however, parallel I/O systems are application dependent and may not work well for certain data access requests. New emerging solid state drives (SSD) are able to deliver better performance but incur a high monetary cost. While SSDs cannot always replace HDDs, the hybrid SSD-HDD approach uniquely addresses common performance issues in parallel I/O systems. The performance of hybrid SSD-HDD architecture depends on the utilization of the SSD and scheduling of data placement. In this paper, we propose a cost-aware regionlevel (CARL) data placement scheme for hybrid parallel I/O systems. CARL divides large files into several small regions, calculates the region costs according to the data access patterns, and selectively places regions with high access costs onto the SSDbased file servers. We have implemented CARL under MPI-IO and the PVFS2 parallel file system environment. Experimental results of representative benchmarks show that CARL is both feasible and able to improve I/O performance significantly.
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