Compiling C-like Languages to FPGA Hardware: Some Novel Approaches Targeting Data Memory Organisation

This paper describes our approaches to raise the level of abstraction at which hardware suitable for accelerating computationally-intensive applications can be specified. Field-Programmable Gate Arrays (FPGAs) are becoming adopted as a computational platform by the high-performance computing community, but there are challenges to extract maximum performance from these devices. Unlike other approaches, our focus is on data memory organisation and input-output bandwidth considerations, which are the typical stumbling block of existing hardware compilation schemes. We describe our approaches, which are based on formal optimization techniques, and present some results showing the advantage of exposing the interaction between data memory system design and parallelism extraction to the compiler.