An introduction to parallel algorithms
An introduction to parallel algorithms
IEEE Transactions on Parallel and Distributed Systems
Parallel computation: models and methods
Parallel computation: models and methods
Information Processing Letters
The Parallel Evaluation of General Arithmetic Expressions
Journal of the ACM (JACM)
An Efficient Implementation for the BROADCAST Instruction of BSR+
IEEE Transactions on Parallel and Distributed Systems
A theorem on the relation between BSRk amd BSR+
Information Processing Letters
Rearranging scattered information on BSR
Information Processing Letters
An Optimal Implementation of Broadcasting with Selective Reduction
IEEE Transactions on Parallel and Distributed Systems
Optimal Parallel Merging Algorithms on BSR
ISPAN '00 Proceedings of the 2000 International Symposium on Parallel Architectures, Algorithms and Networks
Merging, sorting and matrix operations on the SOME-bus multiprocessor architecture
Future Generation Computer Systems - Special issue: Advanced services for clusters and internet computing
O(1) time algorithm on BSR for constructing a binary search tree with best frequencies
PDCAT'04 Proceedings of the 5th international conference on Parallel and Distributed Computing: applications and Technologies
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Constant time solutions for many applications have been obtained on BSR, but some theoretical problems on BSR that were raised when BSR was proposed have not been solved. Three of them are: 1) No lower bound for any problem on BSR is known except trivial constant time, 2) is there any improvement with nonconstant BSR time but still better than the lower bound for CRCW?, and 3) how to characterize problems for which BSR achieves constant time performance. In this paper, we have solved these three problems. For Problem 1, a lower bound on BSR is shown for any computational problem with an optimal sequential solution. An efficient sorting algorithm answers the second problem. A necessary condition is given for the third problem. The Work-Time (WT) Scheduling Principle and optimality for BSR are also introduced for investigating the BSR performance when the number of processors available, p, is different from the input size, n, of problems.