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
Abstract
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.
TextRef
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
People
- Abhinav Bhatele
- Sameer Kumar
- Chao Mei
- James Phillips
- Gengbin Zheng
- Laxmikant Kale
Research Areas