TY - GEN
T1 - Overcoming scaling challenges in biomolecular simulations across multiple platforms
AU - Bhatelé, Abhinav
AU - Kumarz, Sameer
AU - Mei, Chao
AU - Phillips, James C.
AU - Zheng, Gengbin
AU - Kalé, Laxmikant V.
PY - 2008
Y1 - 2008
N2 - NAMD† is a portable parallel application for biomolecular simulations. NAMD pioneered the use of hybrid spatial and force decomposition, a technique now used by most scalable programs for biomolecular simulations, including Blue Matter and Desmond developed by IBM and D. E. Shaw respectively. NAMD has been 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 developed to overcome these challenges. Since our approach involves automatic adaptive runtime optimizations, one interesting issue involves dealing with harmful interaction between multiple adaptive strategies. 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, we present performance results on NCSA's Abe, SDSC's DataStar and TACC's LoneStar cluster, to demonstrate efficient portability. We also compare NAMD with Desmond and Blue Matter.
AB - NAMD† is a portable parallel application for biomolecular simulations. NAMD pioneered the use of hybrid spatial and force decomposition, a technique now used by most scalable programs for biomolecular simulations, including Blue Matter and Desmond developed by IBM and D. E. Shaw respectively. NAMD has been 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 developed to overcome these challenges. Since our approach involves automatic adaptive runtime optimizations, one interesting issue involves dealing with harmful interaction between multiple adaptive strategies. 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, we present performance results on NCSA's Abe, SDSC's DataStar and TACC's LoneStar cluster, to demonstrate efficient portability. We also compare NAMD with Desmond and Blue Matter.
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U2 - 10.1109/IPDPS.2008.4536317
DO - 10.1109/IPDPS.2008.4536317
M3 - Conference contribution
AN - SCOPUS:51049100635
SN - 9781424416943
T3 - IPDPS Miami 2008 - Proceedings of the 22nd IEEE International Parallel and Distributed Processing Symposium, Program and CD-ROM
BT - IPDPS Miami 2008 - Proceedings of the 22nd IEEE International Parallel and Distributed Processing Symposium, Program and CD-ROM
T2 - IPDPS 2008 - 22nd IEEE International Parallel and Distributed Processing Symposium
Y2 - 14 April 2008 through 18 April 2008
ER -