Improved parallel I/O via a two-phase run-time access strategy
ACM SIGARCH Computer Architecture News - Special issue on input/output in parallel computer systems
Lessons from characterizating the input/output behavior of parallel scientific applications
Performance Evaluation - Special issue on tools for performance evaluation
On implementing MPI-IO portably and with high performance
Proceedings of the sixth workshop on I/O in parallel and distributed systems
Optimizing noncontiguous accesses in MPI – IO
Parallel Computing
GPFS: A Shared-Disk File System for Large Computing Clusters
FAST '02 Proceedings of the Conference on File and Storage Technologies
The parallel I/O architecture of the high-performance storage system (HPSS)
MSS '95 Proceedings of the 14th IEEE Symposium on Mass Storage Systems
Improving MPI-IO Output Performance with Active Buffering Plus Threads
IPDPS '03 Proceedings of the 17th International Symposium on Parallel and Distributed Processing
Grid Datafarm Architecture for Petascale Data Intensive Computing
CCGRID '02 Proceedings of the 2nd IEEE/ACM International Symposium on Cluster Computing and the Grid
PVFS: a parallel file system for linux clusters
ALS'00 Proceedings of the 4th annual Linux Showcase & Conference - Volume 4
Using MPI file caching to improve parallel write performance for large-scale scientific applications
Proceedings of the 2007 ACM/IEEE conference on Supercomputing
Measurement and analysis of TCP throughput collapse in cluster-based storage systems
FAST'08 Proceedings of the 6th USENIX Conference on File and Storage Technologies
View-Based Collective I/O for MPI-IO
CCGRID '08 Proceedings of the 2008 Eighth IEEE International Symposium on Cluster Computing and the Grid
Hi-index | 0.00 |
In a cluster of multiple processors or cpu-cores, many processes may run on each compute node. Each process tends to issue contiguous I/O requests for snapshot, checkpointing or so, however, if large number of processes enter the I/O phase at the same time, the requests from the same process may be interrupted by the requests of other processes. Then, the I/O nodes receive these requests as non-contiguous way. This interleaved access pattern causes performance degradation in parallel file systems. In order to overcome the problem, we have designed the Gather-Arrange-Scatter (GAS) I/O architecture, for optimizing the parallel write performance. The GAS is an architecture for capturing write operations, buffering them in the memory, and scheduling them to reduce I/O cost at I/O nodes. The scheduling is done per compute node, and the requests are sent to the remote disks in parallel. In this paper, after introducing the GAS architecture in detail, its efficiency and scalability are evaluated using the NAS Parallel Benchmark BTIO. GAS is 5.2%faster than ROMIO collective I/O on PVFS2 in BTIO with 16 nodes/64 processes, and 34.9% faster than MPI noncollective I/O in the same configuration.