high performance computing on graphics processing units: hgpu.org

This paper is devoted to the development of highly efficient kernels performing vector operations relevant in linear system solvers. In particular, we focus on the low arithmetic intensity operations (i.e., streaming operations) performed within the conjugate gradient iterative method, using the parameters specified in the CEED benchmark problems for high-order hexahedral finite elements. We propose a suite of new Benchmark Streaming tests to focus on the distinct streaming operations which must be performed. We implemented these new tests using the OCCA abstraction framework to demonstrate portability of these streaming operations on different GPU architectures, and propose a simple performance model for such kernels which can accurately capture data movement rates as well as kernel launch costs.