Authors: Camille Coti (Ecole de Technologie Superieure), Yann Pfau-Kempf (University of Helsinki), Markus Battarbee (University of Helsinki), Urs Ganse (University of Helsinki), Sameer Shende (University of Oregon), Kevin Huck (University of Oregon), Jordi Rodriguez (University of Oregon), Leo Kotipalo (University of Helsinki), Allen Malony (University of Oregon), Minna Palmroth (University of Helsinki, Finnish Meteorological Institute)
Abstract: Delivering sustained exascale applications requires a dedicated development and optimization effort to leverage the power of heterogeneous architectures, complex memory hierarchies, and scalable interconnect technologies fueling exascale computing. The challenge is complicated by the fact that application codes might need to use hybrid programming methods, more sophisticated memory management, and adaptive algorithms to leverage exascale capabilities. However, it is also the case that the factors contributing to performance variability will be more prevalent and difficult to understand. Thus, it is important that exascale environments include robust performance analysis technologies that application teams can integrate within their code development and use to conduct experiments that can help elucidate performance problems. The paper reports on a collaboration to integrate exascale-ready performance tools (TAU and APEX from the University of Oregon) with the Vlasiator application, a leading simulation code from the University of Helsinki for modeling the space plasma environment of the Earth. Our goal is to show the benefits of modern performance tool integration in Vlasiator as it is being ported
to the EU’s flagship supercomputer in Finland (LUMI). In addition to presenting Vlasiator performance results, we will offer useful guidance and approaches for other exascale application projects.
Long Description: Delivering sustained exascale applications requires a dedicated development and optimization effort to leverage the power of heterogeneous architectures, complex memory hierarchies, and scalable interconnect technologies fueling exascale computing. The challenge is complicated by the fact that application codes might need to use hybrid programming methods, more sophisticated memory management, and adaptive algorithms to leverage exascale capabilities. However, it is also the case that the factors contributing to performance variability will be more prevalent and difficult to understand. Thus, it is important that exascale environments include robust performance analysis technologies that application teams can integrate within their code development and use to conduct experiments that can help elucidate performance problems. The paper reports on a collaboration to integrate exascale-ready performance tools (TAU and APEX from the University of Oregon) with the Vlasiator application, a leading simulation code from the University of Helsinki for modeling the space plasma environment of the Earth. Our goal is to show the benefits of modern performance tool integration in Vlasiator as it is being ported
to the EU’s flagship supercomputer in Finland (LUMI). In addition to presenting Vlasiator performance results, we will offer useful guidance and approaches for other exascale application projects.
Paper: PDF