VTK-m: Accelerating the Visualization Toolkit for Massively Threaded Architectures
IEEE Computer Graphics and Applications2016Vol. 36(3), pp. 48–58
Citations Over TimeTop 1% of 2016 papers
Kenneth Moreland, Christopher Sewell, Will Usher, Li‐Ta Lo, Jeremy Meredith, David Pugmire, James Kress, Hendrik Schroots, Kwan‐Liu Ma, Hank Childs, Matthew Larsen, Chunming Chen, Robert Maynard, Berk Geveci
Abstract
One of the most critical challenges for high-performance computing (HPC) scientific visualization is execution on massively threaded processors. Of the many fundamental changes we are seeing in HPC systems, one of the most profound is a reliance on new processor types optimized for execution bandwidth over latency hiding. Our current production scientific visualization software is not designed for these new types of architectures. To address this issue, the VTK-m framework serves as a container for algorithms, provides flexible data representation, and simplifies the design of visualization algorithms on new and future computer architecture.
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