Performance of Scientific Simulations on QCT Developer Cloud: A Case Study of Molecular Dynamic and Quantum Chemistry Simulations

We present direct performance measurements for four popular scientific simulations on the Knights Landing (KNL) platform. Performance numbers for Broadwell processors are provided for contrast. The applications (NAMD, LAMMPS, GROMACS and CP2K) were selected from among the ten most used in the QCT developer cloud as well as best representative of workloads used by many users and, given their diversity, should be representative of typical high performance computing workloads. All runs were performed with publicly available codes without modification and so results should be expected to improve as developers gain access to Knights Landing (KNL) processor. Current results are promising, with execution on a single KNL processor showing speedups up to 1.5x with respect to a dual socket Broadwell.

[1]  Yuxiang Gao,et al.  Future Enterprise Computing Looking into 2020 , 2014, FCC.

[2]  D. van der Spoel,et al.  GROMACS: A message-passing parallel molecular dynamics implementation , 1995 .

[3]  Laxmikant V. Kalé,et al.  Scalable molecular dynamics with NAMD , 2005, J. Comput. Chem..

[4]  Steve Plimpton,et al.  Fast parallel algorithms for short-range molecular dynamics , 1993 .

[5]  Meikang Qiu,et al.  Performance and Power Analysis of High-Density Multi-GPGPU Architectures: A Preliminary Case Study , 2015, 2015 IEEE 17th International Conference on High Performance Computing and Communications, 2015 IEEE 7th International Symposium on Cyberspace Safety and Security, and 2015 IEEE 12th International Conference on Embedded Software and Systems.

[6]  Jack J. Dongarra,et al.  Exascale computing and big data , 2015, Commun. ACM.

[7]  Peng Zhang,et al.  A Survey of Homogeneous and Heterogeneous System Architectures in High Performance Computing , 2016, 2016 IEEE International Conference on Smart Cloud (SmartCloud).