December 6, 2023
“What’s the size of the AI market?” It’s a totally normal question for anyone to ask me. After all, I’m an analyst, and my company, Intersect360 Res Read more…
November 16, 2023
Nvidia was invisible with a very small booth and limited floor presence, but thanks to its sheer AI dominance, it was a winner at the Supercomputing 2023. Nv 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 25, 2023
Nvidia is now renting out its homegrown AI supercomputers with its newest GPUs in the cloud for those keen to access its hardware and software packages. Th Read more…
April 15, 2023
HPCwire presents our interview with Nidhi Chappell, General Manager of Azure HPC, AI, SAP, and Confidential Computing at Microsoft. As an HPCwire 2023 Person to Watch, Chappell shares her insights on the evolving HPC cloud market and key trends, including sustainability. She also discusses her role and responsibilities at Azure, and... 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…
October 13, 2022
The University of Bath has launched a new, cloud-based supercomputer, Nimbus, which the university is calling the “central pillar” of its new portfolio of c Read more…
September 16, 2022
Full-stack quantum computing startup Rigetti announced a number of new partnerships and strategic updates at its inaugural investor day meeting, held in-person 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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