Application specific dataflow machine construction for programming FPGAs via Lucent
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Field Programmable Gate Arrays (FPGAs) have the potential to accelerate specific HPC codes. However even with the advent of High Level Synthesis (HLS), which enables FPGA programmers to write code in C or C++, programming such devices still requires considerable expertise. Much of this is due to the fact that these architectures are founded on dataflow rather than the Von Neumann abstraction of CPUs or GPUs. Thus programming FPGAs via imperative languages is not optimal and can result in very significant performance differences between the first and final versions of algorithms on dataflow architectures with the steps in between often not obvious and requiring considerable expertise. In this position paper we argue that languages built upon dataflow principals should be exploited to enable fast by construction codes for FPGAs, and this is akin to the programmer adopting the abstraction of developing a bespoke dataflow machine specialised for their application. It is our belief that much can be learnt from the generation of dataflow languages that gained popularity in the 1970s and 1980s around programming general purpose dataflow machines, and we introduce Lucent which is a modern derivative of Lucid, and used as a vehicle to explore this hypothesis. The idea behind Lucent is to provide high programmer productivity and performance for FPGAs by giving developers the most suitable language level abstractions. The focus of Lucent is very much to support the acceleration of HPC kernels, rather than the embedded electronics and circuit level, and we provide a brief overview of the language driven by examples.
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