Iterative solution methods
Computer architecture (2nd ed.): design and performance
Computer architecture (2nd ed.): design and performance
Iterative methods for solving linear systems
Iterative methods for solving linear systems
Using MPI (2nd ed.): portable parallel programming with the message-passing interface
Using MPI (2nd ed.): portable parallel programming with the message-passing interface
Principles of Distributed Systems
Principles of Distributed Systems
Numerical Linear Algebra for High Performance Computers
Numerical Linear Algebra for High Performance Computers
Performance Prediction of PVM Programs
IPPS '96 Proceedings of the 10th International Parallel Processing Symposium
Grid Computing: Making the Global Infrastructure a Reality
Grid Computing: Making the Global Infrastructure a Reality
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The solution of large, sparse systems of linear equations is an inherent part of many computational methods in science and engineering. For such systems, iterative methods are often more attractive than direct methods because of their small (and constant) memory requirements. Also, the performance of iterative solvers can easily be improved by using distributed systems. A common performance characteristic of distributed applications is their speedup which is usually defined as the ratio of the execution time of an application on a single processor to the execution time of the same workload on a P-processor system. The paper estimates the speedup of distributed linear iterative solvers, analyzes the influence of different communication schemes on the speedup, and compares the estimates with the measurements of real distributed programs.