A comparison of receiver-initiated and sender-initiated adaptive load sharing
Performance Evaluation
DIB—a distributed implementation of backtracking
ACM Transactions on Programming Languages and Systems (TOPLAS)
Parallel depth first search. Part I. implementation
International Journal of Parallel Programming
Parallel depth first search. Part II. analysis
International Journal of Parallel Programming
Dynamic load balancing for distributed memory multiprocessors
Journal of Parallel and Distributed Computing
Chare kernel—a runtime support system for parallel computations
Journal of Parallel and Distributed Computing
A Dynamic Load-Balancing Policy with a Central Job Dispatcher (LBC)
IEEE Transactions on Software Engineering
The PMESC programming library for distributed-memory MIMD computers
Journal of Parallel and Distributed Computing
Parallel Computing - High performance computing in operations research
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
A taxonomy of scheduling in general-purpose distributed computing systems
IEEE Transactions on Software Engineering
An analytical comparison of nearest neighbor algorithms for load balancing in parallel computers
IPPS '95 Proceedings of the 9th International Symposium on Parallel Processing
Euro-Par '99 Proceedings of the 5th International Euro-Par Conference on Parallel Processing
Task Parallelism: What a Tool Can Provide and What Should Be Left to the User
Euro-Par '96 Proceedings of the Second International Euro-Par Conference on Parallel Processing - Volume I
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We describe a new load-balancing strategy, applied here to the protein structure prediction problem, for improving the efficiency of the hierarchical approach when dealing with coarse-grained problems associated with large tree searches. Unlike other load-balancing strategies that reassign load from the heavily loaded processors to the lightly loaded or idle ones, the proposed strategy changes the virtual communication tree among the processors as the computational tree changes. The strategy incurs minimal overhead and is scalable.