Performance Measurements for Musubi

Kurzfassung

Presentation of the core concepts of Musubi in its deployment in high-performance computing environments for detailed flow simulations and elaboration on its performance analysis over time on various supercomputing systems. Musubi is an open-source Lattice-Boltzmann (LBM) solver under development since 2011 within the APES framework using an octree mesh representation. It is implemented in modern Fortran and parallelized with the help of MPI and OpenMP. I briefly introduce some computational aspects of LBM and why it is attractive for some CFD tasks, detail the implementation ideas of Musubi, and explain the wider architecture in APES before diving into performance analyses conducted for the code. Performance assessments have been performed for the solver repeatedly over time by different means and methods, including some analysis by HLRS within the POP Cluster of Excellence project. I recount how those performance analyses shed light on the various aspects of the implementation and helped improve the execution of large-scale computing systems. The deployment of the code spreads across a range of architectures spanning from IBMs BlueGene to NECs SX vector computers. At the heart of those performance assessments, there always is the evaluation of the serial and node-level performance, which establishes a baseline for the parallel execution. An important observation in the overall consideration is that the performance depends on many factors acting together and depending on the features used in the code may vary widely. I address these points and elaborate on common themes and apparent differences.