SC²S Colloquium - April 7, 2017
|Date:||April 7, 2017|
|Time:||3:00 pm, s.t.|
Nora Hagmeyer: Developing an auto-tuned manycore enabled finite element solver for the numerical modeling of nanoscale light/matter interaction using BOAST
My master thesis/ internship at INRIA, France, was concerned with the auto-tuning of an existing finite element type solver for the numerical modelling of light interaction with nanometer scale structures for the modern accelerator architecture of the Intel Xeon Phi processor, codenamed Knights Landing, by using the BOAST environment. BOAST is an auto-tuning tool, developed at INRIA Grenoble, employing a meta-programming approach for porting kernels to different architectures. From a physical point of view, the program deals with the partial differential system of Maxwell equations in the time domain, coupled to an appropriate differential model for the behaviour of the underlying material. Numerically, these differential equations are solved by a Discontinuous Galerkin approach. This highly local approach, in contrast to classical Finite Element Methods, leads to many very small matrix-vector products, making it highly parallelizable. But, this property also gives rise to the challenge of efficiently using the KNL's 512bit-wide vector registers. In this talk, I will present my approach of using the BOAST tool to create a framework for efficiently applying various SIMD optimization strategies, and I will discuss some results produced by it.