Automatically Optimizing Stencil Computations on Many-Core NUMA Architectures

This paper presents a system for automatically supporting the optimization of stencil kernels on emerging Non-Uniform Memory Access (NUMA) many-core architectures, through a combined compiler + runtime approach. In particular, we use a pragma-driven compiler to recognize the special structures and optimization needs of stencil computations and thereby to automatically generate low-level code that efficiently utilize the data placement and management support of a C++ runtime on top of NUMA API, a programming interface to the NUMA policy supported by the Linux kernel. Our results show that through automated specialization of code generation, this approach provides a combined benefit of performance, portability, and productivity for developers.