EGPGV16: Eurographics Symposium on Parallel Graphics and Visualization

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https://diglib.eg.org/handle/10.2312/15271

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Browsing EGPGV16: Eurographics Symposium on Parallel Graphics and Visualization by Subject "Graphics Systems"

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    Dynamic Work Packages in Parallel Rendering
    (The Eurographics Association, 2016) Steiner, David; Paredes, Enrique G.; Eilemann, Stefan; Pajarola, Renato; Enrico Gobbetti and Wes Bethel
    Interactive visualizations of large-scale datasets can greatly benefit from parallel rendering on a cluster with hardware accelerated graphics by assigning all rendering client nodes a fair amount of work each. However, interactivity regularly causes unpredictable distribution of workload, especially on large tiled displays. This requires a dynamic approach to adapt scheduling of rendering tasks to clients, while also considering data locality to avoid expensive I/O operations. This article discusses a dynamic parallel rendering load balancing method based on work packages which define rendering tasks. In the presented system, the nodes pull work packages from a centralized queue that employs a locality-aware dynamic affinity model for work package assignment. Our method allows for fully adaptive implicit workload distribution for both sort-first and sort-last parallel rendering.
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    Dynamically Scheduled Region-Based Image Compositing
    (The Eurographics Association, 2016) Grosset, A. V. Pascal; Knoll, Aaron; Hansen, Charles; Enrico Gobbetti and Wes Bethel
    Algorithms for sort-last parallel volume rendering on large distributed memory machines usually divide a dataset equally across all nodes for rendering. Depending on the features that a user wants to see in a dataset, all the nodes will rarely finish rendering at the same time. Existing compositing algorithms do not often take this into consideration, which can lead to significant delays when nodes that are compositing wait for other nodes that are still rendering. In this paper, we present an image compositing algorithm that uses spatial and temporal awareness to dynamically schedule the exchange of regions in an image and progressively composite images as they become available. Running on the Edison supercomputer at NERSC, we show that a scheduler-based algorithm with awareness of the spatial contribution from each rendering node can outperform traditional image compositing algorithms.