Exploiting computing power of Xeon and Intel Xeon Phi for a molecular dynamics application
Benny Mathew, Nitin Rai, Apaar Gupta, Amit Harode · IEEE International Conference on High Performance Computing, Data, and Analytics · 2015
Molecular Dynamics (MD) is a computational technique with applicability in fields as diverse as material science, biomolecules and chemical physics. Assisted Model Building with Energy Refinement (AMBER) is an MD package and it uses Message Passing Interface (MPI) to scale in multi-core and cluster environments.In our earlier work [1], we modified one of AMBER's algorithms called Generalized Born (GB) algorithm to run optimally on the Xeon Phi co-processor. This improved performance by 277% on the co-processor. The same changes improved performance on the host server by 80%.In this paper, we extend our earlier work and implement a symmetric solution using both the host server and the co-processor. Since the calculations in GB algorithm involve interactions between all possible atom combinations, it has been very difficult to scale GB algorithm in distributed memory. We evaluate various alternate techniques using combination of MPI and Open Multi-Processing (OpenMP) to get a scalable solution that utilizes the computing power of both the host server as well as the co-processor.