Unstructured tree search on SIMD parallel computers: a summary of results
George Karypis, Vipin Kumar
Abstract
George Karypis, Vipin Kumar
Abstract
The authors present methods for load balancing of unstructured tree computations on large-scale SIMD (single-instruction multiple-data) machines and analyze the scalability of these and other schemes. An efficient formulation of tree search on a SIMD machine comprises two major components: (i) a triggering mechanism, which determines when the search space redistribution must occur to balance search space over processors; and (ii) a scheme to redistribute the search space. The authors devised a redistribution mechanism and a triggering mechanism. Either of these can be used in conjunction with triggering and redistribution mechanisms developed by other researchers. The authors analyze the scalability of these mechanisms. The results are verified experimentally. The analysis and experiments show that the novel load balancing methods are highly scalable on SIMD architectures. Their scalability is shown to be no worse than that of the best load balancing schemes on MIMD (multiple-instruction multiple-data) architectures. The authors verified their theoretical results by implementing the 15-puzzle problem on a CM-2 SIMD parallel computer.>
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The authors present methods for load balancing of unstructured tree computations on large-scale SIMD (single-instruction multiple-data) machines and analyze the scalability of these and other schemes. An efficient formulation of tree search on a SIMD machine comprises two major components: (i) a triggering mechanism, which determines when the search space redistribution must occur to balance search space over processors; and (ii) a scheme to redistribute the search space. The authors devised a redistribution mechanism and a triggering mechanism. Either of these can be used in conjunction with triggering and redistribution mechanisms developed by other researchers. The authors analyze the scalability of these mechanisms. The results are verified experimentally. The analysis and experiments show that the novel load balancing methods are highly scalable on SIMD architectures. Their scalability is shown to be no worse than that of the best load balancing schemes on MIMD (multiple-instruction multiple-data) architectures. The authors verified their theoretical results by implementing the 15-puzzle problem on a CM-2 SIMD parallel computer.>
Key concepts: Scalability, SIMD, Computer science, Parallel computing, Load balancing (electrical power), MIMD, Computation, Tree (set theory)