The Challenges of Commodity-Based Visualization Clusters (English)

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The performance of commodity computer components continues to increase dramatically. Processors, internal I/O buses, graphics cards, and network adapters have all exhibited significant improvements without significant increases in cost. Due to the increase in the price/performance ratio of computers utilizing such components, clusters of commodity machines have become commonplace in todays computing world and are steadily displacing specialized, high-end, shared-memory machines for many graphics and visualization workloads. Acceptance, and more importantly utilization, of commodity clusters has been hampered, however, due to the significant challenges introduced when switching from a shared-memory architecture to a distributed memory one. Such challenges range from having to redesign applications for distributed computing to gathering pixels from multiple sources and finally synchronizing multiple video outputs when driving large displays. In addition to these impediments for the application developer, there are also many mundane problems which arise when working with clusters, including their installation and general system administration. This paper details these challenges and the many solutions that have been developed in recent years. As the nature of commodity hardware components suggests, the solutions to these research challenges are largely softwarebased, and include middleware layers for distributing the graphics workload across the cluster as well as for aggregating the final results to display for the user. At the forefront of this discussion will be IBMs Deep View project, whose goal has been the design and implementation of a scalable, affordable, high-performance visualization system for parallel rendering. In the past six years, Deep View has undergone numerous redesigns to make it as efficient as possible. We highlight the issues involved in this process, up to and including the current incarnation of Deep View, as well as whats on the horizon for cluster-based rendering.

  • Title:
    The Challenges of Commodity-Based Visualization Clusters
  • Author / Creator:
  • Published in:
  • Publisher:
    The Eurographics Association
  • Place of publication:
    Postfach 8043, 38621 Goslar, Germany
  • Year of publication:
    2006
  • Size:
    2 pages
  • ISBN:
  • ISSN:
  • DOI:
  • Type of media:
    Conference paper
  • Type of material:
    Electronic Resource
  • Language:
    English
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Table of contents conference proceedings

The tables of contents are generated automatically and are based on the data records of the individual contributions available in the index of the TIB portal. The display of the Tables of Contents may therefore be incomplete.

9
Rendering on Demand
Chalmers, A. / Debattista, K. / Sundstedt, V. / Longhurst, P. / Gillibrand, R. | 2006
19
An Application of Scalable Massive Model Interaction using Shared-Memory Systems
Stephens, Abe / Boulos, Solomon / Bigler, James / Wald, Ingo / Parker, Steven | 2006
27
Accelerating the Irradiance Cache through Parallel Component-Based Rendering
Debattista, Kurt / Santos, Luís Paulo / Chalmers, Alan | 2006
35
Parallel Simulation of Cloth on Distributed Memory Architectures
Thomaszewski, B. / Blochinger, W. | 2006
43
Dynamic Load Balancing for Parallel Volume Rendering
Marchesin, Stéphane / Mongenet, Catherine / Dischler, Jean-Michel | 2006
51
Interactive Volume Rendering of Unstructured Grids with Time-Varying Scalar Fields
Bernardon, Fábio F. / Callahan, Steven P. / Comba, João L. D. / Silva, Cláudio T. | 2006
59
Optimized Volume Raycasting for Graphics-Hardware-based Cluster Systems
Müller, C. / Strengert, M. / Ertl, T. | 2006
67
Accelerated Volume Rendering with Homogeneous Region Encoding using Extended Anisotropic Chessboard Distance on GPU
Es, A. / Keles, H. Y. / Isler, V. | 2006
75
Parallel Texture-Based Vector Field Visualization on Curved Surfaces Using GPU Cluster Computers
Bachthaler, S. / Strengert, M. / Weiskopf, D. / Ertl, T. | 2006
83
Distributed Force-Directed Graph Layout and Visualization
Mueller, Christopher / Gregor, Douglas / Lumsdaine, Andrew | 2006
91
Time Step Prioritising in Parallel Feature Extraction on Unsteady Simulation Data
Wolter, M. / Hentschel, B. / Schirski, M. / Gerndt, A. / Kuhlen, T. | 2006
99
Parallelization of Inverse Design of Luminaire Reflectors
Magallon, J. A. / Patow, G. / Seron, F. J. / Pueyo, X. | 2006
109
The Challenges of Commodity-Based Visualization Clusters
Klosowski, J. T. | 2006
111
WinSGL: Software Genlocking for Cost-Effective Display Synchronization under Microsoft Windows
Waschbüsch, M. / Cotting, D. / Duller, M. / Gross, M. | 2006
119
Sorted Pipeline Image Composition
Roth, Marcus / Reiners, Dirk | 2006
127
Optimized Visualization for Tiled Displays
Lorenz, Mario / Brunnett, Guido | 2006
137
Parallel Particle Rendering: a Performance Comparison between Chromium and Aura
Schaaf, Tom van der / Koutek, Michal / Bal, Henri | 2006
145
Piggybacking for More Efficient Parallel Out-of-Core Isosurfacing
Newman, Timothy S. / Ma, Wenjun | 2006
153
A Scalable, Hybrid Scheme for Volume Rendering Massive Data Sets
Childs, Hank / Duchaineau, Mark / Ma, Kwan-Liu | 2006
163
Remote Large Data Visualization in the ParaView Framework
Cedilnik, Andy / Geveci, Berk / Moreland, Kenneth / Ahrens, James / Favre, Jean | 2006
171
Multi-layered Image Caching for Distributed Rendering of Large Multiresolution Datasets
Strasser, Jonathan / Pascucci, Valerio / Ma, Kwan-Lui | 2006