Input/output characteristics of scalable parallel applications
Supercomputing '95 Proceedings of the 1995 ACM/IEEE conference on Supercomputing
Profile-guided I/O partitioning
ICS '03 Proceedings of the 17th annual international conference on Supercomputing
Noncontiguous I/O Accesses Through MPI-IO
CCGRID '03 Proceedings of the 3st International Symposium on Cluster Computing and the Grid
Data Sieving and Collective I/O in ROMIO
FRONTIERS '99 Proceedings of the The 7th Symposium on the Frontiers of Massively Parallel Computation
Operating Systems Design and Implementation (3rd Edition)
Operating Systems Design and Implementation (3rd Edition)
Parallel I/O prefetching using MPI file caching and I/O signatures
Proceedings of the 2008 ACM/IEEE conference on Supercomputing
Bridging the Gap Between Parallel File Systems and Local File Systems: A Case Study with PVFS
ICPP '08 Proceedings of the 2008 37th International Conference on Parallel Processing
BORG: block-reORGanization for self-optimizing storage systems
FAST '09 Proccedings of the 7th conference on File and storage technologies
PLFS: a checkpoint filesystem for parallel applications
Proceedings of the Conference on High Performance Computing Networking, Storage and Analysis
IOrchestrator: Improving the Performance of Multi-node I/O Systems via Inter-Server Coordination
Proceedings of the 2010 ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis
I/O acceleration with pattern detection
Proceedings of the 22nd international symposium on High-performance parallel and distributed computing
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Scientific computing is becoming more data-intensive; however I/O throughput is not growing at the same rate. MPI-IO and parallel file systems are expected to help bridge the gap by increasing data access parallelism. Compared to traditional I/O systems, some factors are more important in parallel I/O system in order to achieve better performance, such as the number of requests and contiguousness of accesses. The variation of these factors can lead to significant differences in performance. Programmers usually arrange data in a logical fashion for ease of programming and data manipulation; however, this may not be ideal for parallel I/O systems. Without taking into account the organization of file and behavior of the I/O system, the performance may be badly degraded. In this paper, a novel method of reorganizing files in I/O middleware level is proposed, which takes into account the access patterns. By placing data in a way favoring the parallel I/O system, gains of up to two orders of magnitudes in reading and up to one order of magnitude in writing were observed with spinning disks and solid-state disks.