26 citations · 29 across the 5 of their papers we have counts for
5 papers
LAPIS: A Performance Portable, High Productivity Compiler Framework
Brian Kelley, Sivasankaran Rajamanickam
Portability, performance, and productivity are three critical dimensions for evaluating a programming model or compiler infrastructure. Several modern programming models for comput…
Performance Portable Gradient Computations Using Source Transformation
Kim Liegeois, Brian Kelley, Eric Phipps +2
Derivative computation is a key component of optimization, sensitivity analysis, uncertainty quantification, and nonlinear solvers. Automatic differentiation (AD) is a powerful tec…
Parallel, Portable Algorithms for Distance-2 Maximal Independent Set and Graph Coarsening
Brian Kelley, Sivasankaran Rajamanickam
Given a graph, finding the distance-2 maximal independent set (MIS-2) of the vertices is a problem that is useful in several contexts such as algebraic multigrid coarsening or mult…
Two-Stage Gauss--Seidel Preconditioners and Smoothers for Krylov Solvers on a GPU cluster
Luc Berger-Vergiat, Brian Kelley, Sivasankaran Rajamanickam +5
Gauss-Seidel (GS) relaxation is often employed as a preconditioner for a Krylov solver or as a smoother for Algebraic Multigrid (AMG). However, the requisite sparse triangular solv…
Kokkos Kernels: Performance Portable Sparse/Dense Linear Algebra and Graph Kernels
Sivasankaran Rajamanickam, Seher Acer, Luc Berger-Vergiat +7
As hardware architectures are evolving in the push towards exascale, developing Computational Science and Engineering (CSE) applications depend on performance portable approaches f…