Performance Prediction and Calibration for a Class of Multiprocessors
IEEE Transactions on Computers
Parallel applications performance methodology
Instrumentation for future parallel computing systems
A method for performance prediction of parallel programs
CONPAR 90 Proceedings of the joint international conference on Vector and parallel processing
A methodology for performance analysis of parallel computations with looping constructs
Journal of Parallel and Distributed Computing
A static performance estimator in the Fortran D programming system
Languages, compilers and run-time environments for distributed memory machines
A static parameter based performance prediction tool for parallel programs
ICS '93 Proceedings of the 7th international conference on Supercomputing
Fortran RED - A Retargetable Environment for Automatic Data Layout
LCPC '98 Proceedings of the 11th International Workshop on Languages and Compilers for Parallel Computing
Compiler Synthesis of Task Graphs for Parallel Program Performance Prediction
LCPC '00 Proceedings of the 13th International Workshop on Languages and Compilers for Parallel Computing-Revised Papers
Automatic exploitation of dual level parallelism on a network of multiprocessors
HPDC '96 Proceedings of the 5th IEEE International Symposium on High Performance Distributed Computing
Parallel program performance prediction using deterministic task graph analysis
ACM Transactions on Computer Systems (TOCS)
International Journal of High Performance Computing Applications
| Hi-index | 0.00 |
In this paper we present a novel interpretive approach for accurate and cost-effective performance prediction in a high performance computing environment, and describe the design of a source-driven HPF/Fortran 90D performance prediction framework based on this approach. The performance prediction framework has been implemented as part of a HPF/Fortran 90D application development environment. A set of benchmarking kernels and application codes are used to validate the accuracy, utility, usability, and cost-effectiveness of the performance prediction framework. The use of the framework for selecting appropriate compiler directives and for application performance debugging is demonstrated.