On implementing MPI-IO portably and with high performance
Proceedings of the sixth workshop on I/O in parallel and distributed systems
Parallel I/O for high performance computing
Parallel I/O for high performance computing
Software Optimization for High Performance Computers
Software Optimization for High Performance Computers
MPI-IO/GPFS, an optimized implementation of MPI-IO on top of GPFS
Proceedings of the 2001 ACM/IEEE conference on Supercomputing
Data Sieving and Collective I/O in ROMIO
FRONTIERS '99 Proceedings of the The 7th Symposium on the Frontiers of Massively Parallel Computation
Integrating collective I/O and cooperative caching into the "clusterfile" parallel file system
Proceedings of the 18th annual international conference on Supercomputing
Exploiting Lustre File Joining for Effective Collective IO
CCGRID '07 Proceedings of the Seventh IEEE International Symposium on Cluster Computing and the Grid
Self-adaptive hints for collective i/o
EuroPVM/MPI'06 Proceedings of the 13th European PVM/MPI User's Group conference on Recent advances in parallel virtual machine and message passing interface
Improving the average response time in collective I/O
EuroMPI'11 Proceedings of the 18th European MPI Users' Group conference on Recent advances in the message passing interface
Design and evaluation of nonblocking collective I/O operations
EuroMPI'11 Proceedings of the 18th European MPI Users' Group conference on Recent advances in the message passing interface
Optimized process placement for collective I/O operations
Proceedings of the 20th European MPI Users' Group Meeting
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MPI is the de-facto standard for message passing in parallel scientific applications. MPI-IO is a part of the MPI-2 specification defining file I/O operations in the MPI world. MPI-IO enables performance optimizations for collective file I/O operations as it acts as a portability layer between the application and the file system. The goal of this study is to optimize collective file I/O operations. Three different algorithms for performing collective I/O operations have been developed, implemented, and evaluated on a PVFS2 file system and over NFS. The results indicate that different algorithms promise the highest write bandwidth for different number of processors, application settings and file systems, making a one-size-fits-all solution inefficient.