November 20, 2023
This year's fantastic Supercomputing 2023 was back in full form. Attendees seemed to be glad that the show was back in Denver, which was a preferred destination Read more…
October 3, 2023
Recently, Dan Stanzione, Executive Director, TACC and Associate Vice President for Research, UT-Austin, gave a presentation on HPC sustainability at the Fall 20 Read more…
July 28, 2023
Editor's note; The Day 1 and Day 2 reports from PEARC23 got crossed in the wires. Both reports are now posted. Thanks to Ken Chiacchia of the Pittsburgh Superco Read more…
July 27, 2023
Editor's note; The Day 1 and Day 2 reports from PEARC23 got crossed in the wires. Both reports are now posted. Thanks to Ken Chiacchia of the Pittsburgh Superco Read more…
February 14, 2023
Each November, HPCwire’s readers and editors recognize dozens of individuals and organizations across more than 20 very serious award categories, celebrating Read more…
January 28, 2023
A tremendous portion of the world depends on the output of the oceans’ major fisheries, which have, in recent decades, found themselves under near-constant th Read more…
December 20, 2022
By now, most people are aware of the vast amount of trash currently clogging our oceans, with the Great Pacific garbage patch alone estimated to be twice the si Read more…
December 14, 2022
Texas Advanced Computing Center Director Dan Stanzione and HPCwire Managing Editor Tiffany Trader met in Dallas to discuss the biggest trends in HPC and the hot 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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