Evaluation of leading scalar and vector architectures for scientific computations
Horst D. Simon, Leonid Oliker, Andrew Canning, Jonathan T. Carter, S. Ethier, John M. Shalf · 2004
The growing gap between sustained and peak performance for scientific applications is a well-known problem in high performance computing. The recent development of parallel vector systems offers the potential to reduce this gap for many computational science codes and deliver a substantial increase in computing capabilities. This project examines the performance of the cacheless vector Earth Simulator (ES) and compares it to superscalar cache-based IBM Power3 system. Results demonstrate that the ES is significantly faster than the Power3 architecture, highlighting the tremendous potential advantage of the ES for numerical simulation. However, vectorization of a particle-in-cell application (GTC) greatly increased the memory footprint preventing loop-level parallelism and limiting scalability potential.