Reconfigurable Designs for Radiosity

  • Authors:
  • Paul Baker;Tim Todman;Henry Styles;Wayne Luk

  • Affiliations:
  • Imperial College;Imperial College;Imperial College;Imperial College

  • Venue:
  • FCCM '05 Proceedings of the 13th Annual IEEE Symposium on Field-Programmable Custom Computing Machines
  • Year:
  • 2005

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Abstract

We develop reconfigurable designs to support radiosity, a computer graphics algorithm for producing highly realistic images of artificial scenes, but which is computationally expensive. We implement radiosity using stochastic ray-tracing, which affords both instruction-level and data parallelism. Our designs are parameterisable by bitwidth, allowing trade-offs between image quality and computation speed. We measure the speed of our designs for a Xilinx XC2V6000 device in the Celoxica RC2000 platform: at 53MHz it can run up to five times faster than a software implementation on an Athlon MP 2600+ processor at 2.1GHz. We estimate that retargeting our design for a Virtex-4 XCVSX55 device can result in over 160 times software speed, while a Spartan-3 XC3S5000 device can run more than 40 times faster than the software implementation.