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Image and data-parallel rendering across multiple nodes on HPC system is widely used in visualization to provide higher framerates, support large datasets, and render data in situ, Specifically for in situ, reducing bottlenecks incurred by the visualization and compositing tasks is of key concern to reduce the overall simulation run time, while for general interactive visualization improving rendering performance, and thus interactivity, is always desirable. In this talk, Will Usher will present our work on an asynchronous image processing and compositing framework for multi-node rendering in OSPRay, dubbed the Distributed FrameBuffer. We demonstrate that this approach achieves performance superior to the state of the art for common use cases, while providing the flexibility to support a wide range of parallel rendering algorithms and data distribution. By building on this framework, we have extended OSPRay with a data-distributed API, enabling its use in data-distributed and in situ visualization applications. Will Usher will cover our approach to developing this framework, performance considerations, and use cases and examples of the new data-distributed API in OSPRay.

Event Name

IXPUG Webinar Series


Xeon Phi,Xeon,Data Parallel,Parallel Rendering,FrameBuffer,In Situ Visualization