A case for redundant arrays of inexpensive disks (RAID)
SIGMOD '88 Proceedings of the 1988 ACM SIGMOD international conference on Management of data
Swift/RAID: a distributed RAID system
Computing Systems
Parallel file systems for the IBM SP computers
IBM Systems Journal
The HP AutoRAID hierarchical storage system
ACM Transactions on Computer Systems (TOCS) - Special issue on operating system principles
Orthogonal Striping and Mirroring in Distributed RAID for I/O-Centric Cluster Computing
IEEE Transactions on Parallel and Distributed Systems
GPFS: A Shared-Disk File System for Large Computing Clusters
FAST '02 Proceedings of the Conference on File and Storage Technologies
Distributed RAID - A New Multiple Copy Algorithm
Proceedings of the Sixth International Conference on Data Engineering
Beowulf Cluster Computing with Linux
Beowulf Cluster Computing with Linux
SNAPI '03 Proceedings of the international workshop on Storage network architecture and parallel I/Os
Scalability in the XFS file system
ATEC '96 Proceedings of the 1996 annual conference on USENIX Annual Technical Conference
Modularized redundant parallel virtual file system
ACSAC'05 Proceedings of the 10th Asia-Pacific conference on Advances in Computer Systems Architecture
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Using parity information to protect data from loss in a parallel file system is a straightforward and cost-effective method. However, the “small-write” phenomenon can lead to poor write performance. This is still true in the distributed paradigm even when file system cache is used. The local file system knows nothing about a stripe and thus can not benefit from the related blocks of a stripe. We propose a distributed parity cache table (DPCT) which knows the related blocks of a stripe and can use them to improve the performance of parity calculation and parity updating. This high level cache can benefit from previous reads and can aggregate small writes to improve the overall performance. We implement this mechanism in our reliable parallel file system (RPFS). The experimental results show that both read and write performance can be improved with DPCT support. The improvement comes from the fact that we can reduce the number of disk accesses by DPCT. This matches our quantitative analysis which shows that the number of disk accesses can be reduced from N to N(1–H), where N is the number of I/O nodes and H is the DPCT hit ratio.