Enabling and Scaling Biomolecular Simulations of 100~Million Atoms on Petascale Machines with a Multicore-optimized Message-driven Runtime
| Chao Mei | Yanhua Sun | Gengbin Zheng | Eric Bohm | Laxmikant Kale | James Phillips | Chris Harrison
International Conference for High Performance Computing, Networking, Storage and Analysis (SC) 2011
Publication Type: Paper
Repository URL: papers/201103_NAMD100MAtoms
Abstract
A 100-million-atom biomolecular simulation with \namd{} is one of the three benchmarks for the NSF-funded sustainable petascale machine. Simulating this large molecular system on a petascale machine presents great challenges, including handling I/O, large memory footprint and getting good strong-scaling results. In this paper, we present parallel I/O techniques to enable the simulation. A new SMP model is designed to efficiently utilize ubiquitous wide multicore clusters by extending the \charmpp{} asynchronous message-driven runtime. We exploit node-aware techniques to optimize both the application and the underlying SMP runtime. Hierarchical load balancing is further exploited to scale \namd{} to the full Jaguar PF Cray XT5 (224,076 cores) at Oak Ridge National Laboratory, both with and without PME full electrostatics, achieving 93\% parallel efficiency (vs 6720 cores) at 9\,ms per step for a simple cutoff calculation. Excellent scaling is also obtained on 65,536 cores of the Intrepid Blue Gene/P at Argonne National Laboratory.
TextRef
Chao Mei, Yanhua Sun, Gengbin Zheng, Eric J. Bohm, Laxmikant V. Kale, James C.Phillips and Chris Harrison, "Enabling and Scaling Biomolecular Simulations of 100 Million Atoms on Petascale Machines with a Multicore-optimized Message-driven Runtime", Proceedings of the ACM/IEEE Supercomputing Conference 2011
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