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A new technique for estimating and understanding the speed improvement that can result from executing a program on a parallel computer is described. The technique requires no additional programming and minimal effort by a program's author. The analysis begins by tracing a sequential program. A parallelism analyzer uses information from the trace to simulate parallel execution of the program. In addition to predicting parallel performance, the parallelism analyzer measures many aspects of a program's dynamic behavior. Measurements of six substantial programs are presented. These results indicate that the three symbolic programs differ substantially from the numeric programs and, as a consequence, cannot be automatically parallelized with the same compilation techniques.
Aurélien François Gilbert Bloch
Felix Schürmann, Michael Lee Hines, Bruno Ricardo Da Cunha Magalhães
Anastasia Ailamaki, Iraklis Psaroudakis