Iterative linear solvers are popular in large-scale computing as they consume less memory than direct solvers. Contrary to direct linear solvers, iterative solvers approach the solution gradually requiring the computation of sparse matrix- vector (SpMV) products. The evaluation of SpMV products can emerge as a bottleneck for computational performance within the context of the simulation of large problems. In this work, we focus on a linear system arising from the discretiza- tion of the Cahn{Hilliard equation, which is a fourth order non- linear parabolic partial differential equation that governs the separation of a two-component mixture into phases [3]. The underlying spatial discretization is performed using the dis- continuous Galerkin method and Newton's method. A number of parallel algorithms and strategies have been eval- uated in this work to accelerate the evaluation of SpMV prod- ucts. “
