FPGA-based fine-grain parallel computing (abstract only)
Andrew William Hill, Andrea Di Blas, Richard Hughey · 2011
FPGAs are increasing in computing power at a significant rate while the non-recurring engineering costs and time-to-market remain significant lower than those for application-specific integrated circuits (ASICs), encouraging FPGAs to be used in areas previous dominated by ASICs. In this study, we examine the appropriateness of FPGAs for high-performance, low-volume prodution parallel computing by mapping an existing ASIC-based massively parallel single-instruction, multiple data (SIMD) computer, the UCSC Kestrel, to a variety of FPGAs. The design has a raw peak performance of over 187 billion 8-bit operations per second (OPS), 48 times faster than the original ASIC-based Kestrel, using a Xilinx Virtex-6, and a cost efficiency of up to 81 MOPS/$ using a Xilinx Spartan-3. We also show that we can implement the entire original Kestrel (512 processing elements) as a system on a single programmable chip.