Micro Time Cost Analysis of Parallel Computations
IEEE Transactions on Computers
PVM: Parallel virtual machine: a users' guide and tutorial for networked parallel computing
PVM: Parallel virtual machine: a users' guide and tutorial for networked parallel computing
Software—Practice & Experience
Heterogeneous System Performance Prediction and Analysis Using PS
IEEE Concurrency
A Case for NOW (Networks of Workstations)
IEEE Micro
Performance Prediction of PVM Programs
IPPS '96 Proceedings of the 10th International Parallel Processing Symposium
DiP: A Parallel Program Development Environment
Euro-Par '96 Proceedings of the Second International Euro-Par Conference on Parallel Processing-Volume II
Message-Passing Performance of Various Computers
Message-Passing Performance of Various Computers
Adding Dynamic Coscheduling Support to PVM
Proceedings of the 8th European PVM/MPI Users' Group Meeting on Recent Advances in Parallel Virtual Machine and Message Passing Interface
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Achieving satisfactory performance results in heterogeneous computing environments requires a careful workload assignment. The use of approximate analytical models can help to understand which are the parameters that mostly affect performance. In this paper we will show how to study analytically the behavior of a Cholesky factorization code running in a heterogeneous NOW under the PVM run-time system. Firstly the Cholesky factorization algorithm is introduced, and an analysis of the load distribution is performed. Then the construction of the analytic model of the application is described. Finally, the obtained results are compared to the performance figures obtained by executing the program in the real computing environment.