Section: New Results
High performance computing
High order DGTD- method on hybrid CPU/GPU
parallel systems
Participants : Tristan Cabel, Stéphane Lanteri.
Modern massively parallel computing platforms most often take the form
of hybrid shared memory/distributed memory heterogeneous systems
combining multi-core processing units with accelerator cards. In
particular, graphical processing units (GPU) are increasingly adopted
in these systems because they offer the potential for a very high
floating point performance at a low purchase cost. DG methods are
particularly appealing for exploiting the processing capabilities of a
GPU because they involve local linear algebra operations (mainly
matrix/matrix products) on relatively dense matrices whose size is
directly related to the approximation order of the physical quantities
within each mesh element. We have initiated this year a technological
development project aiming at the adaptation to hybrid CPU/GPU
parallel systems of a high order DGTD-