Showing papers by "James C. Phillips published in 2012"
TL;DR: This work explores the computational challenges facing GB/SA calculations on hybrid GPU/CPU computers and demonstrates how NAMD, a parallel molecular dynamics program, is able to efficiently utilize GPUs and CPUs simultaneously for fastGB/SA simulations.
Abstract: Molecular dynamics methodologies comprise a vital research tool for structural biology. Molecular dynamics has benefited from technological advances in computing, such as multicore CPUs and graphics processing units (GPUs), but harnessing the full power of hybrid GPU/CPU computers remains difficult. The generalized Born/solvent-accessible surface area implicit solvent model (GB/SA) stands to benefit from hybrid GPU/CPU computers, employing the GPU for the GB calculation and the CPU for the SA calculation. Here, we explore the computational challenges facing GB/SA calculations on hybrid GPU/CPU computers and demonstrate how NAMD, a parallel molecular dynamics program, is able to efficiently utilize GPUs and CPUs simultaneously for fast GB/SA simulations. The hybrid computation principles demonstrated here are generally applicable to parallel applications employing hybrid GPU/CPU calculations.
52 citations
10 Nov 2012
TL;DR: This work analyzes communication bottlenecks in NAMD and its CHARM++ runtime, and optimize the runtime, built on the uGNI library for Gemini, to improve the fine-grained communication.
Abstract: Achieving good scaling for fine-grained communication intensive applications on modern supercomputers remains challenging. In our previous work, we have shown that such an application --- NAMD --- scales well on the full Jaguar XT5 without long-range interactions; Yet, with them, the speedup falters beyond 64K cores. Although the new Gemini interconnect on Cray XK6 has improved network performance, the challenges remain, and are likely to remain for other such networks as well. We analyze communication bottlenecks in NAMD and its CHARM++ runtime, using the Projections performance analysis tool. Based on the analysis, we optimize the runtime, built on the uGNI library for Gemini. We present several techniques to improve the fine-grained communication. Consequently, the performance of running 92224-atom Apoa1 with GPUs on TitanDev is improved by 36%. For 100-million-atom STMV, we improve upon the prior Jaguar XT5 result of 26 ms/step to 13 ms/step using 298,992 cores on Jaguar XK6.
25 citations