Automatic mapping of nested loops to FPGAS

Abstract

This paper present a framework for automatic mapping of perfectly nested loops with constant dependences onto regular processor arrays, suitable for direct implementation on Field Programmable Gate Arrays (FPGAs). The problem is modeled as that of finding a suitable completion procedure for a full-rank linear transformation on the iteration space. The approach enables extraction of necessary degrees of communication-free and pipelined parallelism to optimize performance under the resource constraints of limited logic resources and I/O bandwidth available on an FPGA. The generation of control signals for the custom processing elements is also addressed. Examples of automatic derivation of parallel designs for some common nested loops are provided. Experimental results on the Cray XD1 show that an FPGA-based matrix-multiplication design obtained using the framework attains significant speedup on the XD1's attached FPGA, when compared to execution on the XD1 CPU.