A Partitioning Strategy for Nonuniform Problems on Multiprocessors
IEEE Transactions on Computers
Using idle workstations in a shared computing environment
SOSP '87 Proceedings of the eleventh ACM Symposium on Operating systems principles
Dynamic Remapping of Parallel Computations with Varying Resource Demands
IEEE Transactions on Computers
Finding Idle Machines in a Workstation-Based Distributed System
IEEE Transactions on Software Engineering
The available capacity of a privately owned workstation environment
Performance Evaluation
Supercomputing out of recycled garbage: preliminary experience with Piranha
ICS '92 Proceedings of the 6th international conference on Supercomputing
Array decompositions for nonuniform computational environments
Journal of Parallel and Distributed Computing
Stardust: an environment for parallel programming on networks of heterogeneous workstations
Journal of Parallel and Distributed Computing - Special issue on workstation clusters and network-based computing
The utility of exploiting idle workstations for parallel computation
SIGMETRICS '97 Proceedings of the 1997 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Journal of Parallel and Distributed Computing
Non-uniform and dynamic domain decompositions for hypercomputing
Parallel Computing
Availability and utility of idle memory in workstation clusters
SIGMETRICS '99 Proceedings of the 1999 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Predicting the cost and benefit of adapting data parallel applications in clusters
Journal of Parallel and Distributed Computing
Dense linear algebra kernels on heterogeneous platforms: redistribution issues
Parallel Computing - Parallel matrix algorithms and applications
A Case for NOW (Networks of Workstations)
IEEE Micro
Non-uniform 2-D grid partitioning for heterogeneous parallel architectures
IPPS '95 Proceedings of the 9th International Symposium on Parallel Processing
Data parallel programming in an adaptive environment
IPPS '95 Proceedings of the 9th International Symposium on Parallel Processing
Binary Dissection: Variants & Applications
Binary Dissection: Variants & Applications
Time and space adaptation for computational grids with the ATOP-Grid middleware
Future Generation Computer Systems
On/off-line prediction applied to job scheduling on non-dedicated NOWs
Journal of Computer Science and Technology - Special issue on natural language processing
A self-adaptive computing framework for parallel maximum likelihood evaluation
The Journal of Supercomputing
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Many important parallel applications are data parallel, and may be efficiently implemented on a workstation cluster by allocating each workstation a contiguous partition of the data domain. Implementation on non-dedicated clusters, however, is complicated by the possibility of changes in workstation availability. For example, a personal workstation may be reclaimed by its primary user for interactive use. In such situations, a node must be removed from the collection of workstations forming the ''virtual parallel machine'' allocated to the application, and data redistributed accordingly. Conversely, workstations may become available to join the virtual parallel machine. This paper identifies fundamental characteristics of efficient policies for data redistribution following addition/removal of workstations from the cluster. The following conclusions are obtained based on mathematical analysis and simulations: (a) allocating data to a new node from the center of the data domain substantially reduces data migration costs compared to allocation from the edge; (b) addition in groups is beneficial compared to repeated single additions; and (c) even a large number of incremental adjustments of the data domain partitions, owing to successive additions/removals of nodes, do not appear to substantially degrade partition quality compared to that obtained by partitioning from scratch. We believe that these observations can be fruitfully incorporated in the design of workstation cluster support systems for data parallel computing.