HPC

Overview High-Performance Computing Systems (i.e., Supercomputers) provide massive computing performance to solve diverse problems in science and engineering. At our laboratory, we research and develop software to fully utilize the performance of state-of-the-art HPC systems. We develop massively parallel scientific applications in close collaboration with domain scientists. Furthermore, we design and implement middleware for large-scale HPC systems. Research Topics Dynamic Interconnect Control using SDN Modern HPC systems are based on the cluster architecture where multiple computers are connected through a high-performance network (i.

Keichi Takahashi, an assistant professor at SDLab, gave an invited talk at the University of Melbourne Quantitative Methods Network (QMNET). His talk presented the latest research on accelerating Empirical Dynamic Modeling, an international collaboration project with institutes including the Salk institute and National Institute of Advanced Industrial Science and Technology. Video recording: Slide deck:

Keichi Takahashi, an assistant professor at SDLab, presented the following paper at the Practice & Experience in Advanced Research Computing (PEARC) conference: Keichi Takahashi, Wassapon Watanakeesuntorn, Kohei Ichikawa, Joseph Park, Ryousei Takano, Jason Haga, George Sugihara, Gerald M. Pao, “kEDM: A Performance-portable Implementation of Empirical Dynamic Modeling using Kokkos”, Practice & Experience in Advanced Research Computing (PEARC 2021), Jul. 2021. In this work, we developed and evaluated a performance-portable implementation of Empirical Dynamic Modeling (EDM) named kEDM using the Kokkos programming framework.

mpEDM, a parallel and high-performance implementation of Empirical Dynamic Modeling developed at SDLab, has been featured in ArrayFire’s website. Please follow the link below to read the case study: Whole Brain Dynamics at Single Neuron Resolution