Exploiting Irregular Memory Parallelism in Quasi-Stencils through Nonlinear Transformation

Abstract

Non-stencil kernels with irregular memory accesses pose unique challenges to achieving high computing performance and hardware efficiency in high-level synthesis (HLS) of FPGA. We present a highly versatile and systematic approach to effectively synthesizing a special and important subset of non-stencil computing kernels, quasi-stencils, which possess the mathematical property that, if studied in a particular kind of high-dimensional space corresponding to the prime factorization space, the distance between the memory accesses during each kernel iteration becomes constant and such an irregular non-stencil can be considered as a stencil. This opens the door to exploiting a vast array of existing memory optimization algorithms, such as memory partitioning/banking and data reuse, originally designed for the standard stencil-based kernel computing, therefore offering totally new opportunity to effectively synthesizing irregular non-stencil kernels. We show the feasibility of our approach implementing our methodology in a KC705 Xilinx FPGA board and tested it with several custom code segments that meet the quasi-stencil requirement vs some of the state-of the art methods in memory partitioning. We achieve significant reduction in partition factor, and perhaps more importantly making it proportional to the number of memory accesses instead of depending on the problem size with the cost of some wasted space.