Parallelization of MATLAB Applications for a Multi-FPGA System

  • Authors:
  • Anshuman Nayak;Malay Haldar;Alok Choudhary;Prith Banerjee

  • Affiliations:
  • Northwestern University;Northwestern University;Northwestern University;Northwestern University

  • Venue:
  • FCCM '01 Proceedings of the the 9th Annual IEEE Symposium on Field-Programmable Custom Computing Machines
  • Year:
  • 2001

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Abstract

We present a compiler that takes high level signal and image processing algorithms described in MATLAB and generates an optimized hardware for the WildChild驴 board having nine FPGAs and external memory. We propose a Single Program Multiple Data (SPMD) style parallelization framework to automatically generate hardware for all the nine FPGAs. We propose a data alignment and data distribution scheme for minimizing communication across the different FPGAs and present a communication framework based on the WildChild interconnection network for sending and receiving data. Our results show that we get a speedup of around 6 to 7 on eight FPGAs. Further, we propose a prediction mechanism to extract parallelism within a single FPGA. We show that this results in much improved speedups of around 28 on eight FPGAs for the Image Thresholding benchmark. We show that such a framework generates hardwares which are three times slower than the most optimized manual designs, but which can be generated in seconds as compared to days taken by a manual designer.