• Data Assimilation for Ocean Drift Trajectories Using Massive Ensembles and GPUs 

      Holm, Håvard Heitlo; Sætra, Martin Lilleeng; Brodtkorb, André R. (Springer Proceedings in Mathematics & Statistics;volume 323, Chapter; Peer reviewed; Conference object, 2020-06-10)
      In this work, we perform fully nonlinear data assimilation of ocean drift trajectories using multiple GPUs. We use an ensemble of up to 10000 members and the sequential importance resampling algorithm to assimilate ...
    • Evaluation of selected finite-difference and finite-volume approaches to rotational shallow-water flow 

      Holm, Håvard Heitlo; Brodtkorb, André R.; Brostrøm, Gøran; Christensen, Kai Håkon; Sætra, Martin Lilleeng (Communications in Computational Physics;Volume 27, Issue 4, Journal article; Peer reviewed, 2020-05-24)
      The shallow-water equations in a rotating frame of reference are important for capturing geophysical flows in the ocean. In this paper, we examine and compare two traditional finite-difference schemes and two modern finite-volume ...
    • GPU Computing with Python: Performance, Energy Efficiency and Usability 

      Holm, Håvard Heitlo; Brodtkorb, André R.; Sætra, Martin Lilleeng (Computation;Volume 8, Issue 1, Journal article; Peer reviewed, 2020-01-06)
      In this work, we examine the performance, energy efficiency, and usability when using Python for developing high-performance computing codes running on the graphics processing unit (GPU). We investigate the portability of ...
    • Massively parallel implicit equal-weights particle filter for ocean drift trajectory forecasting 

      Holm, Håvard Heitlo; Sætra, Martin Lilleeng; van Leeuwen, Peter Jan (Journal of Computational Physics: X;Volume 6, March 2020, 100053, Journal article; Peer reviewed, 2020-03-04)
      Forecasting of ocean drift trajectories are important for many applications, including search and rescue operations, oil spill cleanup and iceberg risk mitigation. In an operational setting, forecasts of drift trajectories ...
    • Performance and Energy Efficiency of CUDA and OpenCL for GPU Computing using Python 

      Holm, Håvard Heitlo; Brodtkorb, André R.; Sætra, Martin Lilleeng (Advances in Parallel Computing;Volume 36: Parallel Computing: Technology Trends, Journal article; Peer reviewed, 2020)
      In this work, we examine the performance and energy efficiency when using Python for developing HPC codes running on the GPU. We investigate the portability of performance and energy efficiency between CUDA and OpenCL; ...