%0 Generic %1 Bonati2018Portable %A Bonati, Claudio %A Calore, Enrico %A D'Elia, Massimo %A Mesiti, Michele %A Negro, Francesco %A Sanfilippo, Francesco %A Schifano, Sebastiano F. %A Silvi, Giorgio %A Tripiccione, Raffaele %D 2018 %K hpc %T Portable multi-node LQCD Monte Carlo simulations using OpenACC %U http://arxiv.org/abs/1801.01473 %X This paper describes a state-of-the-art parallel Lattice QCD Monte Carlo code for staggered fermions, purposely designed to be portable across different computer architectures, including GPUs and commodity CPUs. Portability is achieved using the OpenACC parallel programming model, used to develop a code that can be compiled for several processor architectures. The paper focuses on parallelization on multiple computing nodes using OpenACC to manage parallelism within the node, and OpenMPI to manage parallelism among the nodes. We first discuss the available strategies to be adopted to maximize performances, we then describe selected relevant details of the code, and finally measure the level of performance and scaling-performance that we are able to achieve. The work focuses mainly on GPUs, which offer a significantly high level of performances for this application, but also compares with results measured on other processors.

@misc{Bonati2018Portable, abstract = {{This paper describes a state-of-the-art parallel Lattice QCD Monte Carlo code for staggered fermions, purposely designed to be portable across different computer architectures, including GPUs and commodity CPUs. Portability is achieved using the OpenACC parallel programming model, used to develop a code that can be compiled for several processor architectures. The paper focuses on parallelization on multiple computing nodes using OpenACC to manage parallelism within the node, and OpenMPI to manage parallelism among the nodes. We first discuss the available strategies to be adopted to maximize performances, we then describe selected relevant details of the code, and finally measure the level of performance and scaling-performance that we are able to achieve. The work focuses mainly on GPUs, which offer a significantly high level of performances for this application, but also compares with results measured on other processors.}}, added-at = {2019-02-23T22:09:48.000+0100}, archiveprefix = {arXiv}, author = {Bonati, Claudio and Calore, Enrico and D'Elia, Massimo and Mesiti, Michele and Negro, Francesco and Sanfilippo, Francesco and Schifano, Sebastiano F. and Silvi, Giorgio and Tripiccione, Raffaele}, biburl = {https://www.bibsonomy.org/bibtex/225431b91a1c1cef05a1d3cb0d650cf83/cmcneile}, citeulike-article-id = {14513541}, citeulike-linkout-0 = {http://arxiv.org/abs/1801.01473}, citeulike-linkout-1 = {http://arxiv.org/pdf/1801.01473}, day = 4, eprint = {1801.01473}, interhash = {de76a7001b5fb8e91cb423ab5b416a71}, intrahash = {25431b91a1c1cef05a1d3cb0d650cf83}, keywords = {hpc}, month = jan, posted-at = {2018-01-08 13:21:53}, priority = {2}, timestamp = {2019-02-23T22:15:27.000+0100}, title = {{Portable multi-node LQCD Monte Carlo simulations using OpenACC}}, url = {http://arxiv.org/abs/1801.01473}, year = 2018 }