Scalability and parallel execution of warp processing: dynamic hardware/software partitioning

  • Authors:
  • Roman Lysecky

  • Affiliations:
  • Department of Electrical and Computer Engineering, University of Arizona, Tucson, AZ

  • Venue:
  • International Journal of Parallel Programming
  • Year:
  • 2008

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Abstract

Warp processors are a novel architecture capable of autonomously optimizing an executing application by dynamically re-implementing critical kernels within the software as custom hardware circuits in an on-chip FPGA. Previous research on warp processing focused on low-power embedded systems, incorporating a low-end ARM processor as the main software execution resource. We provide a thorough analysis of the scalability of warp processing by evaluating several possible warp processor implementations, from low-power to high-performance, and by evaluating the potential for parallel execution of the partitioned software and hardware. We further demonstrate that even considering a high-performance 1 GHz embedded processor, warp processing provides the equivalent performance of a 2.4GHz processor. By further enabling parallel execution between the processes and FPGA, the parallel warp processor execution provides the equivalent performance of a 3.2 GHz processor.