LDAV 2021 Best Paper Honorable Mention

SCI at University of Utah Accelerates Visual Computing via oneAPI

oneAPI cross-architecture programming & Intel® oneAPI Rendering Toolkit to Improve Large-scale Simulations, Data Analytics & Visualization for Scientific Workflows
[Oct. 26, 2021] - The Scientific Computing and Imaging (SCI) Institute at the University of Utah is pleased to announce that it is expanding its Intel Graphics and Visualization Institute of Xellence (Intel GVI) to an Intel oneAPI Center of Excellence (CoE). The oneAPI Center of Excellence will focus on advancing research, development and teaching of the latest visual computing innovations in ray tracing and rendering, and using oneAPI to accelerate compute across heterogeneous architectures (CPUs, GPUs including future upcoming Intel Xe architecture, and other accelerators). Adopting oneAPI’s cross-architecture programming model provides a path to achieve maximum efficiency in multi-architecture deployments supporting CPUs + accelerators. This core approach based on open standards will allow fast, agile development and support new, advanced features without costly management of multiple vendors’ specific proprietary code bases.
Democratizing Data Access

The National Science Foundation (NSF) awarded a $5.6 million project to a team of researchers led by School of Computing professor Valerio Pascucci (pictured), who is also director of the Center for Extreme Data Management in the College of Engineering, to build the critical infrastructure needed to connect large-scale experimental and computational facilities and recruit others to data-driven sciences.
Chuck Hansen Elected to IEEE Board of Governors

Valerio Pascucci Wins a NASA Earth Exchange Award

WIFIRE Commons and BurnPro3D

Manish Parashar Named ACM Fellow

The ACM Fellows program recognizes the top 1% of ACM Members for their outstanding accomplishments in computing and information technology and/or outstanding service to ACM and the larger computing community, according to the organization. Fellows are nominated by their peers.
SCALE MoDL: Advancing Theoretical Minimax Deep Learning: Optimization, Resilience, and Interpretability

The past decade has witnessed the great success of deep learning in broad societal and commercial applications. However, conventional deep learning relies on fitting data with neural networks, which is known to produce models that lack resilience.
Conversion of Utah Coal into High-value Carbon Products Sustaining Rural Economies

U Part of World’s Ultimate IT Team
The world’s most important scientific facilities, from the CERN Large Hadron Collider to the National Radio Astronomy Observatory, deal with massive amounts of data every day that are mined, stored, analyzed and visualized. It’s a colossal task that requires help from the top minds in data management to handle.
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The CERN Large Hadron Collider in Switzerland is one of many of the world’s most important scientific facilities and research projects that will get help from team members from the University of Utah’s School of Computing and five other universities on how to best manage their scientific data. |
So the National Science Foundation (NSF) is turning to expert computer scientists from the University of Utah’s School of Computing and five other top universities, to help these facilities and other research projects manage their data in faster and more affordable ways.