Q&A with ORNL’s Travis Humble, an HPCwire Person to Watch in 2023

May 12, 2023

Travis Humble is the director the Quantum Science Center (QSC) at Oak Ridge National Laboratory. QSC is one of six National QIS Research established by the U.S. National Quantum Initiative Act (NQIA) in 2018 and being overseen by the Department of Energy. Hopes are high that these centers, through their own research and in collaboration... Read more…

Quantum – Are We There (or Close) Yet? No, Says the Panel

November 19, 2022

For all of its politeness, a fascinating panel on the last day of SC22 – Quantum Computing: A Future for HPC Acceleration? – mostly served to illustrate the Read more…

Glimpse into ORNL Quantum Science Center Efforts to Find the Elusive Majorana and Much More

August 16, 2022

The Quantum Science Center (QSC), headquartered at Oak Ridge National Laboratory, is one of five such centers created by the National Quantum Initiative Act in 2018 and run by the Department of Energy. They all have distinct and overlapping goals. That’s sort of the point, to bring both focus and cooperation... Read more…

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Whitepaper

Penguin Computing Scyld Cloud Central™: A New Cloud-First Approach to HPC and AI Workloads

Making the Most of Today’s Cloud-First Approach to Running HPC and AI Workloads With Penguin Scyld Cloud Central™

Bursting to cloud has long been used to complement on-premises HPC capacity to meet variable compute demands. But in today’s age of cloud, many workloads start on the cloud with little IT or corporate oversight. What is needed is a way to operationalize the use of these cloud resources so that users get the compute power they need when they need it, but with constraints that take costs and the efficient use of existing compute power into account. Download this special report to learn more about this topic.

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QCT POD- An Adaptive Converged Platform for HPC and AI

Data center infrastructure running AI and HPC workloads requires powerful microprocessor chips and the use of CPUs, GPUs, and acceleration chips to carry out compute intensive tasks. AI and HPC processing generate excessive heat which results in higher data center power consumption and additional data center costs.

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