When planning an AI or HPC investment, applications are where the rubber meets the road and ultimately determine the benefits of any hardware investment. In addition, anyone concerned about compu …
A recent article appearing in EDN (Electrical Design News) points out that on this day, September 20, 1954, the first Fortran program ran on a mainframe computer. Originally developed by IBM, For …
Check out our list of 108 illustrious winners across 22 different categories of HPC.
July 12, 2023
Editor’s note; In light of recent updates to Google’s Privacy Policy, “For example, we use publicly available information to help train Google’s AI mo Read more…
June 13, 2023
Steady technical progress and continued market traction were key points of emphasis coming from the PCI-SIG Developers Conference held this week in Santa Clara. Read more…
June 7, 2023
The first numbers of the available bandwidth between chiplets is out – UCIe is estimating that chiplet packages could squeeze out communication speeds of 630Gbps, or 0.63Tbps, in a very tight area. That number was shared by the Universal Chiplet Interconnect Express consortium last month... Read more…
April 5, 2023
MLCommons today released the latest MLPerf Inferencing (v3.0) results for the datacenter and edge. While Nvidia continues to dominate the results – topping al Read more…
March 9, 2023
Time’s up: nearly everyone agrees it’s about time to become serious about bringing security safeguards to high-performance computing systems, which has been Read more…
February 28, 2023
Enabling interoperability across U.S. exascale supercomputers is one of the chief goals for the U.S. Exascale Computing Project (ECP), which has broadly oversee Read more…
January 31, 2023
Last week the National AI Research Resource (NAIRR) Task Force released its final report and roadmap for building a national AI infrastructure to include comput Read more…
January 23, 2023
Global computer and chip manufacturer Fujitsu today reported that a new study performed on its 39-qubit quantum simulator suggests it will remain difficult for 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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