(AS)2: Accelerator Synthesis using Algorithmic Skeletons for Rapid Design Space Exploration

Abstract—Hardware accelerators in heterogeneous multipro-cessor system-on-chips are becoming popular as a means of meeting performance and energy efficiency requirements of mod-ern embedded systems. Current design methods for accelerator synthesis, such as High-Level Synthesis, are not fully automated. Therefore, time consuming manual iterations are required to explore efficient accelerator alternatives: the programmer is still required to think in terms of the underlying architecture. In this paper, we present (AS)2: a design flow for Accelerator Synthesis using Algorithmic Skeletons. Skeletonization separates the structure of a parallel computation from an algorithms ’ func-tionality, enabling efficient implementations without requiring the programmer to have hardware knowledge. We define three such skeletons (for three image processing kernels) enabling FPGA specific parallelization techniques and optimizations. As a case study, we present a design space exploration of these skeletons and show how multiple design points with area–performance trade-offs for the accelerators can be efficiently and rapidly synthesized. We show that (AS)2 is a promising direction for accelerator synthesis as it generates a pareto front of 8 design points in under half an hour for each of the three image processing kernels. I