Analysis of a Computational Biology Simulation Technique on Emerging Processing Architectures

Multi-paradigm, multi-threaded and multi-core computing devices available today provide several orders of magnitude performance improvement over mainstream microprocessors. These devices include the STI Cell Broadband Engine, graphical processing units (GPU) and the Cray massively-multithreaded processors - available in desktop computing systems as well as proposed for supercomputing platforms. The main challenge in utilizing these powerful devices is their unique programming paradigms. GPUs and the Cell systems require code developers to manage code and data explicitly, while the Cray multithreaded architecture requires them to generate a very large number of threads or independent tasks concurrently. In this paper, we explain strategies for optimizing a molecular dynamics (MD) calculation that is used in biomolecular simulations on three devices: Cell, GPU and MTA-2. We show that the Cray MTA-2 system requires minimal code modification and does not outperform the microprocessor runs; but it demonstrates an improved workload scaling behavior over the microprocessor implementation. On the other hand, substantial porting and optimization efforts on the Cell and the GPU systems result in a 5times to 6times improvement, respectively, over a 2.2 GHz Opteron system.