Effective Data Redistribution and Load Balancing for Sort-Last Volume Rendering Using a Group Hierarchy

Detta är en Uppsats för yrkesexamina på avancerad nivå från KTH/Skolan för elektroteknik och datavetenskap (EECS)

Författare: Marcus Walldén; [2018]

Nyckelord: volume rendering; cuda; load balancing; sort-last; mpi;

Sammanfattning: Volumetric rendering is used to visualize volume data from e.g. scientific simulations. Many advanced applications use large gigabyte- or terabyte-sized data sets, which typically means that multiple compute nodes need to partake in the rendering process to achieve interactive frame rates. Load balancing is generally used to optimize the rendering performance. In existing load balancing techniques, nodes generally only render directly-connected data and handle load balancing based on data locality in kd-trees. This approach can result in redundant data transfers and unbalanced data distribution, which affect the frame rate and increase the hardware requirements of all nodes. In this thesis we present a novel load balancing technique for sort-last volume rendering which utilizes a group hierarchy. The technique allows nodes to render data from arbitrary positions in the volume, without inducing a costly image compositing stage. The technique is compared to a static load balancing technique as well as a dynamic kd-tree based load balancing technique. Our testing demonstrated that the presented technique performed better than or equal to the kd-tree based technique while also lowering the worst-case memory usage complexity of all nodes. Utilizing a group hierarchy effectively helped to lower the compositing time of the presented technique.

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