Commodity cluster computing for computational chemistry
Ken A. Hawick, D. A. Grove, Paul David Coddington, Mark A. Buntine · 2000
: Access to high-performance computing power remains crucial for many computational chemistry problems. Unfortunately, traditional supercomputers or cluster computing solutions from commercial vendors remain very expensive, even for entry level configurations, and are therefore often beyond the reach of many small to medium-sized research groups and universities. Clusters of networked commodity computers provide an alternative computing platform that can offer substantially better price/performance than commercial supercomputers. We have constructed a networked PC cluster, or Beowulf, dedicated to computational chemistry problems using standard ab initio molecular orbital software packages such as Gaussian and GAMESS-US. This paper introduces the concept of Beowulf computing clusters and outlines the requirements for running the ab initio software packages used by computational chemists at the University of Adelaide. We describe the economic and performance trade-offs and design choi...