Optimization of a discontinuous Galerkin solver with OpenCL and StarPU
Université de Strasbourg, Icube, Inria Camus
hal-01942863, (30 January 2020)
Since the recent advance in microprocessor design, the optimization of computing software becomes more and more technical. One of the difficulties is to transform sequential algorithms into parallel ones. A possible solution is the task-based design. In this approach, it is possible to describe the parallelization possibilities of the algorithm automatically. The task-based design is also a good strategy to optimize software in an incremental way. The objective of this paper is to describe a practical experience of a task-based parallelization of a Discontinuous Galerkin method in the context of electromagnetic simulations. The task-based description is managed by the StarPU runtime. Additional acceleration is obtained by OpenCL.
February 2, 2020 by hgpu