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 accelerating 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.

Over the past two years, Principal Investigators Chris Johnson, Valerio Pascucci, and Martin Berzins led more than 20 research papers and development of the OpenViSUS and Uintah software, and created rendering and scientific visualization algorithms for advanced graphics and visualization deployed within Intel OSPRay’s ray tracing API and engine through the Intel GVI.

The SCI Institute oneAPI Center of Excellence team is extending its Intel GVI work to pursue new high-performance visual computing methods that utilize oneAPI cross-architecture programming, which delivers performance and productivity, along with providing the ability to create single source code that takes advantage of CPUs, GPUs and other accelerator technologies can be deployed across a variety of architectures. For infrastructure, the Utah project provides an end-to-end computing and data movement environment using oneAPI to achieve seamless integration of large-scale simulations, data analytics, and visualization in practical scientific workflows. In particular, we will deploy an innovative data movement and streaming infrastructure based on a novel encoding approach that enables expressing new quality-vs-speed tradeoffs by modeling spatial resolution and numerical precision of the data independently. This model organizes scientific data in a single layout that allows decoding the data in various incremental decoding streams, each satisfying a different scientific workflow requirement. We use this data model as the foundation for a new generation of tools that combines Intel® oneAPI technology with the OpenViSUS and Uintah frameworks to efficiently manage, store, analyze, and visualize scientific data.

Projects include scalable ray tracing for adaptive mesh refinement data, multidimensional transfer function volume rendering, in situ visualization, multifield visualization and uncertainty visualization applied to large-scale problems in science, engineering, and medicine. Much of this work uses the Academy Award® winning Intel® Embree, Intel® OSPRay, and other components of the Intel® oneAPI Rendering Toolkit.

In particular, the OpenViSUS framework (visus.org) provides advanced data management and visualization infrastructure enabling data sharing and collaborative activities for national resources such the National Ecological Observatory Network (NEON) or the Materials Commons. Integration of OpenViSUS with the Uintah simulation code also allows archiving scalable computing and streaming of massive simulation data on leadership class computing resources in DOE national laboratories.

oneAPI cross-architecture programming is key to advancing simulations for challenging engineering problems using the Utah Uintah software on forthcoming exascale architectures such as the Argonne Leadership Computing Facility’s Aurora supercomputer.