Efficiency of classical molecular dynamics algorithms on supercomputers

List of 500 Best Supercomputers. http://top500.org. Cited April 16, 2015.

High-Performance Computing Using FPGAsW, Ed. by W. Vanderbauwhede and K. Benkrid (Springer, New York, 2013).

I. Ohmura, G. Morimoto, Y. Ohno, A. Hasegawa, and M. Taiji, “MDGRAPE-4: a special-purpose computer system for molecular dynamics simulations,” Phil. Trans. R. Soc. A 372, 20130387 (2014).

D. E. Shaw et al., “Anton 2: raising the bar for performance and programmability in a special-purpose molecular dynamics supercomputer,” in Proceedings of the SC14 International Conference on High Performance Computing, Networking, Storage and Analysis, New Orleans, LA, USA, November 16–21, 2014 (IEEE Press, Piscataway, 2014), pp. 41–53.

V. O. Podryga and S. V. Polyakov, “Molecular dynamic simulation of thermodynamic equilibrium for nickel system,” Math. Models Comput. Simul. 7, 456–466 (2015).

V. O. Podryga, S. V. Polyakov, and D. V. Puzyr’kov, “Supercomputer molecular simulation of thermodynamic equilibrium in gas-metal microsystems,” Vychisl. Metody Programmir. 16 (1), 123–138 (2015).

W. Eckhardt et al., “591 TFLOPS multi-trillion particles simulation on SuperMUC,” Supercomputing 7905 (2013).

V. V. Stegailov and G. E. Norman, “Challenges to the supercomputer development in Russia: a HPC user perspective,” Program. Sistemy: Teor. Prilozh. 5 (1), 111–152 (2014).

A. Yu. Kuksin, A. V. Lankin, I. V. Morozov, G. E. Norman, N. D. Orekhov, V. V. Pisarev, G. S. Smirnov, S. V. Starikov, V. V. Stegailov, and A. V. Timofeev, “Predictive modeling and simulation of properties and multiscale processes in materials science. Tasks for Exaflops-era supercomputers,” Program. Sistemy: Teor. Prilozh. 5 (1), 191–244 (2014).

E. M. Pestryaev, “Testing of multi-cores graphic processors by molecular dynamics algorithm,” Mat. Model. 26 (1), 69–82 (2014).

F. Reid and I. Bethune, Optimising CP2K for the Intel Xeon Phi. http://www.praceri. eu/IMG/pdf/wp140.pdf. Cited April 16, 2015.

H. Jeong et al., Performance of Kepler GTX Titan GPUs and Xeon Phi System. http://arxiv.org/abs/1311.0590. Cited April 16, 2015.

E. Y. K. Chan, Benchmarks for Intel MIC Architecture. http://www.clustertech.com/wp-content/ uploads/2014/01/MICBenchmark.pdf. Cited April 16, 2015.

http://www.nvidia.ru/object/gpu-computing-facts-ru.html. Cited April 16, 2015.

S. J. Pennycook et al., “Exploring SIMD for molecular dynamics, using Intel Xeon processors and Intel Xeon Phi coprocessors,” in Proceedings of the 27th International Parallel and Distributed Processing Symposium IPDPS- 13, Cambridge, Boston, MA, May 20–24, 2013.

http://www.nvidia.com/object/io_1258360868914.html. Cited April 16, 2015.

http://www.anandtech.com/show/7521/nvidia-launches-tesla-k40. Cited April 16, 2015.

http://ark.intel.com/products/75800/Intel-Xeon-Phi-Coprocessor-7120X-16GB-1_238-GHz-61-core. Cited April 16, 2015.

J. D. McCalpin, “Memory bandwidth and machine balance in current high performance computers,” IEEE Comput. Soc. Tech. Comm. Comput. Archit. Newslett., 19–25 (1995).

http://www.cs.virginia.edu/stream/. Cited April 16, 2015.

https://devtalk.nvidia.com/default/topic/381934/stream-benchmark/. Cited April 16, 2015.

http://devblogs.nvidia.com/parallelforall/optimizing-high-performance-conjugate-gradient-benchmarkgpus/. Cited April 16, 2015.

http://www.cs.virginia.edu/stream/stream_mail/2013/0002.html. Cited April 16, 2015.

LAMMPS Software. http://lammps.sandia.gov. Cited April 16, 2015.

S. Plimpton, “Fast parallel algorithms for short-range molecular dynamics,” J. Comput. Phys. 117, 1–19 (1995).

W. M. Brown et al., “Implementing molecular dynamics on hybrid high performance computers-short range forces,” Comput. Phys. Commun. 182, 898–911 (2011).

E. H. Carter, C. R. Trott, and D. Sunderland, “Kokkos: enabling manycore performance portability through polymorphic memory access patterns,” J. Parallel Distrib. Comput. 74, 3202–3216 (2013).

I. V. Morozov, A. M. Kazennov, R. G. Bystryi, G. E. Norman, V. V. Pisarev, and V. V. Stegailov, “Molecular dynamics simulations of the relaxation processes in the condensed matter on GPUs,” Comput. Phys. Commun. 182, 1974–1978 (2011).

W. M. Brown, A. Kohlmeyer, S. J. Plimpton, and A. N. Tharrington, “Implementing molecular dynamics on hybrid high performance computers–particle-particle particle-mesh,” Comput. Phys. Commun. 183, 449–459 (2012).

W. M. Brown and M. Yamada, “Implementing molecular dynamics on hybrid high performance computers–three-body potentials,” Comput. Phys. Commun. 184, 2785–2793 (2013).

C. Begau and G. Sutmann, “Adaptive dynamic load-balancing with irregular domain decomposition for particle simulations,” Comput. Phys. Commun. 190, 51–61 (2015).

Vl. V. Voevodin, S. A. Zhumatii, S. I. Sobolev, A. S. Antonov, P. A. Bryzgalov, D. A. Nikitenko, K. S. Stefanov, and Vad. V. Voevodin, “Practics of ‘Lomonosov’ supercomputer,” Otkryt. Sistemy 7, 36–39 (2012).

http://lammps.sandia.gov/bench/lj_one.html. Cited April 16, 2015.

Y. Sun, G. Zheng, C. Mei, E. J. Bohm, J. C. Phillips, L. V. Kalé, and T. R. Jones, “Optimizing fine-grained communication in a biomolecular simulation application on Cray XK6,” in Proceedings of the ACM/IEEE International Conference on High Performance Computing, Networking, Storage and Analysis SC12, Salt Lake City, Utah, Nov. 10–16, 2012.

S. Kumar, Y. Sun, and L. V. Kalé, “Acceleration of an asynchronous message driven programming paradigm on IBM Blue Gene/Q,” in Proceedings of the 27th International Parallel and Distributed Processing Symposium IPDPS-13, Cambridge, Boston, MA, May 20–24, 2013.