Aaron Knoll is a Research Scientist at the SCI Institute, University of Utah. He completed his Ph.D. at the University of Utah in 2009 on optimized ray tracing methods for implicit surfaces. He has authored papers on efficient CPU and GPU visualization published in leading journals and conferences including IEEE Visualization, ACM Siggraph, IEEE TVCG, and Computer Graphics Forum. At Argonne National Laboratory, he developed Nanovol, a GPU volume raycasting application for computational chemistry problems. At TACC, he supported users of Paraview and VisIt, and developed new rendering technology for the Intel® Xeon Phi™ architecture on the Stampede supercomputer. At SCI, he is continuing his collaboration with Argonne National Laboratory on visualizing large materials data, and pursuing new research in unstructured and particle visualization in the Visus framework, as part of the DOE Scalable Data Management, Analysis and Visualization (SDAV) initiative.
The goal of the Intel® Parallel Computing Center(s) (Intel® PCC) for Scientific Rendering is to research and develop visualization techniques for Intel hardware, finding solutions for large scale and in situ visualization that would not be effective with existing methods. In partnership with the Software Defined Visualization (SDVis) initiative at the Intel Technical Computing Group (TCG), SCI proposes to:
- Develop techniques for rendering of large unstructured data, particularly of particle data, in the Intel OSPRay framework, including support for unstructured VTK data.
- Port, optimize and extend the University of Utah’s Visus technology to be the premier parallel in situ visualization tool based on Intel® architecture, supporting streaming LOD visualization of petascale HPC simulations.
- Port, optimize and extend the University of Utah’s SCIRun software to support CPU visualization, providing a virtual workbench for larger biomechanical simulations on SMP workstation hardware.
- Increase awareness of Intel’s visualization framework as well as OSPRay and Embree technologies.
Our effort will showcase Intel’s commitment to scientific advancement, and the performance of its CPU and Xeon Phi hardware in GPU-dominated applications of graphics and visualization.
- August 30, 2018, A Virtual Reality Visualization Tool for Neuron Tracing, IEEE TVCG 2018
- August 6, 2018, abelFlow: An Embedded Domain Specific Language for Parallel Analysis and Visualization, IPDPS 2018
- April 14, 2018, Third-Party Use Cases Illustrate the Success of CPU-based Visualization, Tech Enablement
- Qi Wu, Will Usher, Steve Petruzza, Sidharth Kumar, Feng Wang, Ingo Wald, Valerio Pascucci and Charles D. Hansen, June 4, 2018, VisIt-OSPRay: Toward an Exascale Volume Visualization System. Eurographics Symp. on Parallel Graphics and Visualization, EGPGV2 018, Conference
- Sidharth Kumar, Alan Humphrey, Will Usher, Steve Petruzza, Brad Peterson, John A. Schmidt, Derek Harris, Ben Isaac, Jeremy Thornock, Todd Harman, Valerio Pascucci, Martin Berzins, January 1, 2018, Scalable Data Management of the Uintah Simulation Framework for Next-Generation Engineering Problems with Radiation. Supercomputing Frontiers, 2018, SC Asia 2018/ Springer, Conference
- Cameron Christensen, Shusen Liu, Giorgio Scorzelli, Ji-Woo Lee, Peer-Timo Bremer, Valerio Pascucci, August 6, 2018, Embedded Domain-Specific Language and Runtime System for Progressive Spatiotemporal Data Analysis and Visualization, IPDPS 2018, Conference
- Will Usher, Pavol Klacansky, Frederick Federer, Peer-Timo Bremer, Aaron Knoll, Jeff Yarch, Alessandra Angelucci, Valerio Pascucci, August 30, 2018, A Virtual Reality Visualization Tool for Neuron Tracing, IEEE TVCG 2018, Conference
- T.A.J Ouermi, Aaron Knoll, Robert M. Kirby, Martin Bezins, October 3, 2017, Optimization Strategies for WRF Single-Moment 6-Class Microphysics Scheme (WSM6) on Intel Microarchitectures, SCI, White Paper
- Martin Berzins, July 2014, Large Scale Engineering Simulations Multicore and Heterogeneous Architectures, IXPUG
- Jim Jeffers, March 2017, CPU-based Visualization Positions for Exascale Supercomputing, HPCWire
- A.V.Pascal Grosset, Aaron Knoll, and Charles Hansen, January 2016, Dynamically Scheduled Region-Based Image Compositing, sci.utah.edu
- Sean Thielen, March 2017, CPU, GPU Potential for Visualization and Irregular Code, The Next Platform
- I Wald, GP Johnson, J Amstutz, C Brownlee, A Knoll, J Jeffers, J Gunther, P Navratil, January 2016, OSPRay – A CPU Ray Tracing Framework for Scientific Visualization, sci.utah.edu
- W. Behel, E. Gobbetti, January 2016, In Situ Exploration of Particle Simulations with CPU Ray Tracing, sci.utah.edu
- Dynamically Scheduled Region-Based Image compositing
- VTK-m: Accelerating the Visualization Toolkit for Massively Threaded Architectures