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Distributed Point Rendering

  • Ramgopal Rajagopalan
  • Sushil Bhakar
  • Dhrubajyoti Goswami
  • Sudhir P. Mudur
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3769)

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.

Keywords

Graphic Processing Unit Graphic Cluster Graphic Application Cache Block Functionality Distribution 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Ramgopal Rajagopalan
    • 1
  • Sushil Bhakar
    • 1
  • Dhrubajyoti Goswami
    • 1
  • Sudhir P. Mudur
    • 1
  1. 1.Dept. of Computer Science and Software EngineeringConcordia UniversityMontrealCanada

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