Distributed point rendering

  • Authors:
  • Ramgopal Rajagopalan;Sushil Bhakar;Dhrubajyoti Goswami;Sudhir P. Mudur

  • Affiliations:
  • Dept. of Computer Science and Software Engineering, Concordia University, Montreal, Canada;Dept. of Computer Science and Software Engineering, Concordia University, Montreal, Canada;Dept. of Computer Science and Software Engineering, Concordia University, Montreal, Canada;Dept. of Computer Science and Software Engineering, Concordia University, Montreal, Canada

  • Venue:
  • HiPC'05 Proceedings of the 12th international conference on High Performance Computing
  • Year:
  • 2005

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Abstract

Traditionally graphics clusters have been employed in real-time visualization of large geometric models (many millions of 3D points). Data parallel approaches have been the obvious choices when it comes to breaking up the computations over multiple processors. In recent years, programmable graphics hardware has gained widespread acceptance. Today, every processing node in a graphics cluster has two powerful and fully programmable processors – a CPU (Central Processing Unit) and a GPU (Graphics processing unit). It enables distribution of graphics computations targeting an applications’s needs in more flexible ways. In this paper we discuss and analyze our implementation of functionality distributed point-based rendering pipeline with impressive performance improvements. To the best of our knowledge, it is the first attempt to devise a functionality distribution scheme for a large data and compute-intensive application. We discuss the merits and limitations of such a distribution scheme by comparing it against traditional data parallel and single node schemes.