May 27, 2021
With demands for AI, hybrid cloud and quantum computing expanding daily, IBM is joining an initiative to build a Discovery Accelerator Institute at the Universi Read more…
June 3, 2020
NSF has awarded the National Center for Supercomputing Applications (NCSA) $10 million for its next supercomputer - named Delta – “which will kick-start NCS Read more…
January 30, 2020
As electronics get smaller and smaller – and use more and more components – microchip development is in a never-ending battle for minimization. Now, researc Read more…
April 15, 2016
In keeping with its vision of an era of cognitive computing enabled by acceleration technology, IBM Research (NYSE: IBM) today announced plans for a multi-year Read more…
May 9, 2011
This week the University of Illinois, the Air Force Research Laboratory and the Air Force Office of Scientific Research launched a new initiative to tackle some of the most persistent security and data integrity related issues that plague the cloud. We discussed the effort and its projected outcomes with the project lead, Dr. Roy Campbell. Read more…
August 16, 2010
At this year's TeraGrid conference, Bob Wilhelmson, recently retired chief science officer of the National Center for Supercomputing Applications (NCSA) and former applications lead for the Blue Waters project, delivered a keynote address in which he discussed the Blue Waters architecture and shared several planned projects for the new supercomputer. This is our fourth in a series covering the TeraGrid conference. 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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