Journal
COMPUTER PHYSICS COMMUNICATIONS
Volume 192, Issue -, Pages 97-107Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.cpc.2015.02.028
Keywords
Multi-GPU; Molecular dynamics; MPI/CUDA; Strong scaling; Weak scaling; Domain decomposition; LAMMPS
Funding
- DOD/ASD (RE) [N00244-09-1-0062]
- DFG [GL733/1-1]
- National Science Foundation, Division of Materials Research [DMR 1409620, DMR 0907338]
- Simons Foundation
- Office of Science of the US Department of Energy [DE-AC05-00OR22725]
- National Science Foundation [ACI 1238993]
- state of Illinois
- NVIDIA
- Direct For Computer & Info Scie & Enginr [1515306] Funding Source: National Science Foundation
- Office of Advanced Cyberinfrastructure (OAC) [1515306] Funding Source: National Science Foundation
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We describe a highly optimized implementation of MPI domain decomposition in a GPU-enabled, general-purpose molecular dynamics code, HOOMD-blue (Anderson and Glotzer, 2013). Our approach is inspired by a traditional CPU-based code, LAMMPS (Plimpton, 1995), but is implemented within a code that was designed for execution on GPUs from the start (Anderson et al., 2008). The software supports short-ranged pair force and bond force fields and achieves optimal GPU performance using an autotuning algorithm. We are able to demonstrate equivalent or superior scaling on up to 3375 GPUs in Lennard-Jones and dissipative particle dynamics (DPD) simulations of up to 108 million particles. GPUDirect RDMA capabilities in recent GPU generations provide better performance in full double precision calculations. For a representative polymer physics application, HOOMD-blue 1.0 provides an effective GPU vs. CPU node speed-up of 12.5x. (C) 2015 Elsevier B.V. All rights reserved.
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