November 21, 2023
The first Gordon Bell Prize for Climate Modeling was presented at SC23 in Denver. The award went to a team led by Sandia National Laboratories that had develope Read more…
November 20, 2023
Accurately calculating interactions among electrons has been a significant obstacle to reliable material exploration and design through computer modeling. Recen Read more…
November 14, 2023
In 2021, Intel famously declared its goal to get to zettascale supercomputing by 2027, or scaling today's Exascale computers by 1,000 times. Moving forward t Read more…
November 13, 2023
The fall 2023 TOP500 list is out and Frontier retains its top spot and is still the only exascale machine. However, five new or upgraded systems have shaken up Read more…
July 24, 2023
While not a golden HPC spike, the final blade has been loaded into Aurora. As mentioned previously, final preparation of Aurora is underway. Aurora the "almost Read more…
June 22, 2023
Aurora, one of the first three U.S. exascale supercomputers, has not had a straightforward path to installation and operation. The system has been repeatedly re Read more…
May 22, 2023
Fresh off their third Top500 win for Frontier – now with an 8.4% higher Linpack score – the HPC team at Oak Ridge National Laboratory had some exciting news to share today. Frontier has passed its acceptance and is taking on grand scientific challenges. “Acceptance of Frontier took place at the... Read more…
May 22, 2023
It’s not quite homeostasis, but it's close. There was little movement in the latest Top500, released today from the International Supercomputing Conference (I Read more…
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.
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.
Data centers traditionally use air cooling solutions including heatsinks and fans that may not be able to reduce energy consumption while maintaining infrastructure performance for AI and HPC workloads. Liquid cooled systems will be increasingly replacing air cooled solutions for data centers running HPC and AI workloads to meet heat and performance needs.
QCT worked with Intel to develop the QCT QoolRack, a rack-level direct-to-chip cooling solution which meets data center needs with impressive cooling power savings per rack over air cooled solutions, and reduces data centers’ carbon footprint with QCT QoolRack smart management.
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