Solving Linear Algebraic Equations on an MIMD Computer
Journal of the ACM (JACM)
Experience Using Multiprocessor Systems—A Status Report
ACM Computing Surveys (CSUR)
Probability and Statistics with Reliability, Queuing and Computer Science Applications
Probability and Statistics with Reliability, Queuing and Computer Science Applications
Operating Systems Theory
Algorithm partitioning tools for a high-performance multiprocessor
Algorithm partitioning tools for a high-performance multiprocessor
Decomposition and performance in parallel algorithms
Decomposition and performance in parallel algorithms
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A unique decomposition model using two-task replacement sets is used to model algorithm decomposition and algorithm performance. This technique provides a parametric representation of decomposition and performance analysis that is more general and powerful than previous methods. The model is used to investigate the performance of algorithms for MIMD architectures, and the results include statistical descriptions of task and synchronization penalty behavior under decomposition and analytical representations of algorithm performance. The analysis provides insight into the effect of decomposition on performance at both the local task and global algorithm levels. This information would be useful to those interested in compiler technology or algorithm development tools.