Overcoming Scaling Challenges in Biomolecular Simulations across Multiple Platforms
IEEE International Parallel and Distributed Processing Symposium (IPDPS) 2008
Publication Type: Paper
Repository URL: 2008_NAMDIPDPS
NAMD is a portable parallel application for biomolecular simulations. NAMD pioneered the use of hybrid spatial and force decomposition, a technique used now by most scalable programs for biomolecular simulations, including Blue Matter and Desmond developed by IBM and D. E. Shaw respectively. NAMD is developed using Charm++ and benefits from its adaptive communication-computation overlap and dynamic load balancing. This paper focuses on new scalability challenges in biomolecular simulations: using much larger machines and simulating molecular systems with millions of atoms. We describe new techniques we have developed to overcome these challenges. Since our approach involves automatic adaptive runtime optimizations, one interesting issue involves harmful interaction between multiple adaptive strategies, and how to deal with them. Unlike most other molecular dynamics programs, NAMD runs on a wide variety of platforms ranging from commodity clusters to supercomputers. It also scales to large machines: we present results for up to 65,536 processors on IBM's Blue Gene/L and 8,192 processors on Cray XT3/XT4 in addition to results on NCSA's Abe, SDSC's DataStar and TACC's LoneStar cluster, to demonstrate efficient portability. Since our IPDPS'06 paper two years ago, two new highly scalable programs named Desmond and Blue Matter have emerged, which we compare with NAMD in this paper.
Abhinav Bhatele, Sameer Kumar, Chao Mei, James C. Phillips, Gengbin Zheng, Laxmikant V. Kale, Overcoming Scaling Challenges in Biomolecular Simulations across Multiple Platforms, IEEE International Parallel and Distributed Processing Symposium (IPDPS) 2008