EGPGV14: Eurographics Symposium on Parallel Graphics and Visualization

Permanent URI for this collection

https://diglib.eg.org/handle/10.2312/7757

Browse

Browsing EGPGV14: Eurographics Symposium on Parallel Graphics and Visualization by Subject "Graphics Systems"

Now showing 1 - 2 of 2
  • Thumbnail Image
    Item
    Collaborative High-fidelity Rendering over Peer-to-peer Networks
    (The Eurographics Association, 2014) Bugeja, Keith; Debattista, Kurt; Spina, Sandro; Chalmers, Alan; Margarita Amor and Markus Hadwiger
    Due to the computational expense of high-fidelity graphics, parallel and distributed systems have frequently been employed to achieve faster rendering times. The form of distributed computing used, with a few exceptions such as the use of GRID computing, is limited to dedicated clusters available to medium to large organisations. Recently, a number of applications have made use of shared resources in order to alleviate costs of computation. Peer-to-peer computing has arisen as one of the major models for off-loading costs from a centralised computational entity to benefit a number of peers participating in a common activity. This work introduces a peer-to-peer collaborative environment for improving rendering performance for a number of peers where the program state, that is the result of some computation among the participants, is shared. A peer that computes part of this state shares it with the others via a propagation mechanism based on epidemiology. In order to demonstrate this approach, the traditional Irradiance Cache algorithm is extended to account for sharing over a network within the presented collaborative framework introduced. Results, which show an overall speedup with little overheads, are presented for scenes in which a number of peers navigate shared virtual environments.
  • Thumbnail Image
    Item
    Performance Modeling of vl3 Volume Rendering on GPU-Based Clusters
    (The Eurographics Association, 2014) Rizzi, Silvio; Hereld, Mark; Insley, Joseph; Papka, Michael E.; Uram, Thomas; Vishwanath, Venkatram; Margarita Amor and Markus Hadwiger
    This paper presents an analytical model for parallel volume rendering of large datasets using GPU-based clusters. The model is focused on the parallel volume rendering and compositing stages and predicts their performance requiring only a few input parameters. We also present vl3, a novel parallel volume rendering framework for visualization of large datasets. Its performance is evaluated on a GPU-based cluster, weak and strong scaling are studied, and model predictions are validated with experimental results on up to 128 GPUs.