Resource Placement with Multiple Adjacency Constraints in k-ary n-Cubes
IEEE Transactions on Parallel and Distributed Systems
An online video placement policy based on bandwidth to space ratio (BSR)
SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
PPFS: a high performance portable parallel file system
ICS '95 Proceedings of the 9th international conference on Supercomputing
Resource Allocation in Cube Network Systems Based on the Covering Radius
IEEE Transactions on Parallel and Distributed Systems
Exploiting local data in parallel array I/O on a practical network of workstations
Proceedings of the fifth workshop on I/O in parallel and distributed systems
Resource Placement in Torus-Based Networks
IEEE Transactions on Computers
Galley: a new parallel file system for scientific applications
Galley: a new parallel file system for scientific applications
VIP-FS: a VIrtual, Parallel File System for high performance parallel and distributed computing
IPPS '95 Proceedings of the 9th International Symposium on Parallel Processing
A Software Architecture for Massively Parallel Input-Output
PARA '96 Proceedings of the Third International Workshop on Applied Parallel Computing, Industrial Computation and Optimization
Load management in distributed video servers
ICDCS '97 Proceedings of the 17th International Conference on Distributed Computing Systems (ICDCS '97)
PVFS: a parallel file system for linux clusters
ALS'00 Proceedings of the 4th annual Linux Showcase & Conference - Volume 4
MMPacking: a load and storage balancing algorithm for distributed multimedia servers
IEEE Transactions on Circuits and Systems for Video Technology
Optimizing server placement for parallel I/O in switch-based clusters
Journal of Parallel and Distributed Computing
Optimizing server placement in distributed systems in the presence of competition
Journal of Parallel and Distributed Computing
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In this paper, we study I/O server placement for optimizing parallel I/O performance on switch-based clusters, which typically adopt irregular network topologies to allow construction of scalable systems with incremental expansion capability. Finding optimal solution to this problem is computationally intractable. We quantified the number of messages travelling through each network link by a workload function, and developed three heuristic algorithms to find good solutions based on the values of the workload function. The maximum-workload-based heuristic chooses the locations for I/O nodes in order to minimize the maximum value of the workload function. The distance-based heuristic aims to minimize the average distance between the compute nodes and I/O nodes, which is equivalent to minimizing average workload on the network links. The load-balance-based heuristic balances the workload on the links based on a recursive traversal of the routing tree for the network.Our simulation results demonstrate performance advantage of our algorithms over a number of algorithms commonly used in existing parallel systems. In particular, the load-balance-based algorithm is superior to the other algorithms in most cases, with improvement ratio of 10 to 95% in terms of parallel I/O throughput.