Robert Maynard
Kitware
10 Papers
49 Citations
Robert Maynard is an academic researcher from Kitware. The author has contributed to research in topics: Visualization & Data visualization. The author has an hindex of 6, co-authored 10 publications.
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Papers
VTK-m: Accelerating the Visualization Toolkit for Massively Threaded Architectures
Kenneth Moreland,Christopher Sewell,Will Usher,Li-Ta Lo,Jeremy S. Meredith,David Pugmire,James Kress,Hendrik A. Schroots,Kwan-Liu Ma,Hank Childs,Matthew Larsen,Chun-Ming Chen,Robert Maynard,Berk Geveci +13 more
TL;DR: 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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Flexible Analysis Software for Emerging Architectures
Kenneth Moreland,Brad King,Robert Maynard,Kwan-Liu Ma +3 more
- 10 Nov 2012
TL;DR: The approach to accelerator programming forms the basis of the Dax toolkit, a framework to build data analysis and visualization algorithms applicable to exascale computing.
The SDAV Software Frameworks for Visualization and Analysis on Next-Generation Multi-Core and Many-Core Architectures
Christopher Sewell,Jeremy S. Meredith,Kenneth Moreland,Tom Peterka,Dave DeMarle,Li-Ta Lo,James Ahrens,Robert Maynard,Berk Geveci +8 more
- 10 Nov 2012
TL;DR: This paper surveys the four software frameworks being developed as part of the visualization pillar of the SDAV (Scalable Data Management, Analysis, and Visualization) Institute, to facilitate the adaptation of visualization and analysis algorithms to take advantage of the available parallelism in emerging multi-core and many-core hardware architectures.
External facelist calculation with data-parallel primitives
Brenton Lessley,Roba Binyahib,Robert Maynard,Hank Childs +3 more
- 06 Jun 2016
TL;DR: Overall, it is observed that the hashing-based implementation achieves better runtime performance for the majority of configurations, while also achieving the most-stable performance on highly unstructured data sets.
11
A classification of scientific visualization algorithms for massive threading
Kenneth Moreland,Berk Geveci,Kwan-Liu Ma,Robert Maynard +3 more
- 17 Nov 2013
TL;DR: The challenges of refactoring the authors' current visualization algorithms are characterized by considering the finest portion of work each performs and examining the domain of input data, overlaps of output domains, and interdependencies among work instances.
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