The Front Range GigaPop (FRGP) is a longstanding network in Colorado that connects universities, government agencies, and schools to Internet2, peering exchanges, and the broader Internet through shared fiber-optic, routed and packet-switched infrastructure.
A recent NSF grant is funding the expansion of FRGP to the Western Slope, providing 10Gbps connections to Mesa State Metropolitan State University in Grand Junction (MSU), Western Colorado University in Gunnison (WSU), and the Rocky Mountain Biological Laboratory in Gothic (RMBL).
This presentation will highlight FRGP’s services and showcase its role in advancing cyberinfrastructure (CI) across the region.
In concert with the quantum computing-related workshop at this year's RMACC Symposium, this panel explores the current state of quantum-centric HPC from the perspective of prominent industry members of the ecosystem. We'll discuss the limitations inherent to classical approaches that might be overcome using quantum systems, domains and algorithms that are benefiting from today's quantum technology, where quantum advantage might be likely to emerge in the near future, and how HPC facilitators might support researchers integrating quantum computing into their workflows. Sustainability impacts inherent to quantum computing will also be considered.
David Allcock is Director of Science, North America atOxford Ionics where he leads the US-based teams with afocus on our Quantum Science & Engineering initiatives.Allcock received a PhD in Atomic & Laser Physics from theUniversity of Oxford, where he worked alongside OxfordIonics... Read More →
Wednesday May 21, 2025 11:15am - 12:15pm MDT Room 205
New to CU Research Computing, but don't know where to start? This RC Primer training is designed to give you an overview of Research Computing resources, procedures and best practices. You will learn how to log in, request allocations, store and transfer data, load software, run a job, and ask for help. In order to follow along with the hands-on component of this session, you’ll want to register for a Research Computing account beforehand.
AI workloads present new challenges for traditional HPC architectures, particularly as compute demands outpace I/O performance, power constraints tighten, and budgets remain stretched. The need for high-throughput, low-latency data access at extreme scale is forcing a re-evaluation of storage architectures to maximize efficiency without incurring unsustainable costs.
This session will explore how standard Linux and open storage technologies enable AI and HPC workloads to achieve parallel file system performance on commodity hardware—without requiring specialized infrastructure. Topics include: • Scaling AI Storage with Standard Linux: Leveraging NFSv4.2 advancements, including pNFS and FlexFiles, to enable parallel I/O at extreme scales. • Next-Generation SSD Integration: How embedding parallel file system capabilities into SSDs reduces data movement overhead while maximizing power efficiency. • Accelerating AI with Localized Storage on GPU/CPU Servers: Techniques to optimize checkpointing and ephemeral data storage, reducing I/O bottlenecks and overall infrastructure costs.
The session will feature real-world examples of how these innovations are being deployed today to drive high-performance AI workloads while addressing power and cost constraints.
CUDA-Q is an open-source quantum development platform orchestrating the hardware and software needed to run useful, large-scale quantum computing applications. The platform’s hybrid programming model allows computation on GPU, CPU, and QPU resources in tandem from within a single quantum program. CUDA-Q is “qubit-agnostic”—seamlessly integrating with all QPUs and qubit modalities and offering GPU-accelerated simulations when adequate quantum hardware is not available.
CUDA-Q extends simulation tools far beyond the NISQ-era—charting a course to large-scale, error-corrected quantum supercomputing.
