Experimental performance evaluation of the CM-5
Journal of Parallel and Distributed Computing - Special issue on performance of supercomputers
The SP2 high-performance switch
IBM Systems Journal
On Runtime Parallel Scheduling for Processor Load Balancing
IEEE Transactions on Parallel and Distributed Systems
DDE: a modified dimension exchange method for load balancing in k-ary n-cubes
Journal of Parallel and Distributed Computing
Synchronous load balancing in hypercube multicomputers with faulty nodes
Journal of Parallel and Distributed Computing
Fractal Programming in C
How Network Topology Affects Dynamic Load Balancing
IEEE Parallel & Distributed Technology: Systems & Technology
A Case for NOW (Networks of Workstations)
IEEE Micro
Strategies for Dynamic Load Balancing on Highly Parallel Computers
IEEE Transactions on Parallel and Distributed Systems
Runtime Incremental Parallel Scheduling (RIPS) on Distributed Memory Computers
IEEE Transactions on Parallel and Distributed Systems
An analytical comparison of nearest neighbor algorithms for load balancing in parallel computers
IPPS '95 Proceedings of the 9th International Symposium on Parallel Processing
Optimal Contention-Free Unicast-Based Multicasting in Switch-Based Networks of Workstations
IPPS '98 Proceedings of the 12th. International Parallel Processing Symposium on International Parallel Processing Symposium
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Recently, switch-based networks of workstations (NOWs) have been introduced as an alternative for traditional parallel computers. Although many dynamic load balancing algorithms have been developed for point-to-point networks (static networks), little progress has been made on the load balancing in switch-based networks (dynamic networks). Thus, in this paper, we propose a dynamic load balancing algorithm, called the Switch Walking Algorithm (SWA), suitable for switch-based networks. In SWA, each processor's load information is gathered to form global load information, which is then used for load balancing. SWA is compared to a previous algorithm, called the Tree Walking Algorithm (TWA), which has been applied to switch-based networks. Through analysis, we show that SWA requires less communication time for distribution of global load information and migrates fewer tasks than TWA. Also, we show, through the implementation of a Mandelbrot set generation program, that SWA achieves about 20% better performance than TWA on a system with 32 processing elements.