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Field Programmable Gate Arrays (FPGAs) have the potential to acceleratespecific HPC codes. However even with the advent of High Level Synthesis (HLS),which enables FPGA programmers to write code in C or C++, programming suchdevices still requires considerable expertise. Much of this is due to the factthat these architectures are founded on dataflow rather than the Von Neumannabstraction of CPUs or GPUs. Thus programming FPGAs via imperative languages isnot optimal and can result in very significant performance differences betweenthe first and final versions of algorithms on dataflow architectures with thesteps in between often not obvious and requiring considerable expertise.  In this position paper we argue that languages built upon dataflow principalsshould be exploited to enable fast by construction codes for FPGAs, and this isakin to the programmer adopting the abstraction of developing a bespokedataflow machine specialised for their application. It is our belief that muchcan be learnt from the generation of dataflow languages that gained popularityin the 1970s and 1980s around programming general purpose dataflow machines,and we introduce Lucent which is a modern derivative of Lucid, and used as avehicle to explore this hypothesis. The idea behind Lucent is to provide highprogrammer productivity and performance for FPGAs by giving developers the mostsuitable language level abstractions. The focus of Lucent is very much tosupport the acceleration of HPC kernels, rather than the embedded electronicsand circuit level, and we provide a brief overview of the language driven byexamples.

Application specific dataflow machine construction for programming FPGAs via Lucent