Using AMDAHL’s Law as a Metric to Drive Code Parallelization: Two Case Studies

Abstract

Using Amdahl’s law as a metric, the authors illustrate a technique for developing efficient code on massively parallel processor performance-class networks to solve nontrivial, high performance scientific problems. They also show the importance of collective communication within the message-passing interface paradigm for some applications. Given the popularity of Beowulf-like clusters of workstations, this work also indicates the necessity of a scalable high performance network for obtaining efficient performance in parallel code. Using this approach, the authors were able to obtain an effective speedup (comparison with the best sequential time) of 170 when using 256 of the Cray T3E 900 processing elements to solve a carbon, molecular-dynamic problem. The authors also examine the approach on a very different application: a Lanczos eigenvalue solver.