Flexibility and performance of parallel file systems
ACM SIGOPS Operating Systems Review
ENWRICH: a compute-processor write caching scheme for parallel file systems
Proceedings of the fourth workshop on I/O in parallel and distributed systems: part of the federated computing research conference
Performance of the gallery parallel file system
Proceedings of the fourth workshop on I/O in parallel and distributed systems: part of the federated computing research conference
The galley parallel file system
ICS '96 Proceedings of the 10th international conference on Supercomputing
Integrated Performance Models for SPMD Applications and MIMD Architectures
IEEE Transactions on Parallel and Distributed Systems
Integrated Performance Models for SPMD Applications and MIMD Architectures
IEEE Transactions on Parallel and Distributed Systems
I/O Requirements of Scientific Applications: An Evolutionary View
HPDC '96 Proceedings of the 5th IEEE International Symposium on High Performance Distributed Computing
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Phenomenal improvements in the computational performance of multiprocessors have not been matched by comparable gains in I/O system performance. This imbalance has resulted in I/O becoming a significant bottleneck for many scientific applications. One key to overcoming this bottleneck is improving the performance of parallel file systems. The design of a high-performance parallel file system requires a comprehensive understanding of the expected workload. Unfortunately, until recently, no general workload studies of parallel file systems have been conducted. The goal of the CHARISMA project was to remedy this problem by characterizing the behavior of several production workloads, on different machines, at the level of individual reads and writes. The first set of results from the CHARISMA project describe the workloads observed on an Intel iPSC/860 and a Thinking Machines CM-5. This paper is intended to compare and contrast these two workloads for an understanding of their essential similarities and differences, isolating common trends and platform-dependent variances. Using this comparison, we are able to gain more insight into the general principles that should guide parallel file-system design.