Abstract. Stencil computations are at the core of applications in many domains such as computational electromagnetics, image processing, and partial differential equation solvers used in a variety of scientific and engineering applications. Short-vector SIMD instruction sets such as SSE and VMX provide a promising and widely available avenue for enhancing performance on modern processors. However a fundamental memory stream alignment issue limits achieved performance with stencil computations on modern short SIMD architectures. In this paper, we propose a novel data layout transformation that avoids the stream alignment conflict, along with a static analysis technique for determining where this transformation is applicable. Significant performance increases are demonstrated for a variety of stencil codes on several modern processors with SIMD capabilities.
Henretty et al. REF propose a novel data layout transformation, dimensionlifted transposition, for stencil computations.
Data layout transformation for stencil computations on short simd architectures
In ETAPS International Conference on Compiler Construction (CC’11
Computer Science