February 10, 2021
The U.S. Department of Energy's Oak Ridge National Laboratory (ORNL) is now home to one of the first HPE Cray EX supercomputing deployments, which ORNL's Nation Read more…
October 3, 2019
The U.S. military’s approach to AI is equal parts offense and defense, acknowledging that primary adversary China could also weaponize the technology as a for Read more…
December 18, 2014
SGI was awarded a contract worth $30,750,000 to supply the Air Force Research Laboratory (AFRL) with a 3.9 petaflops SGI ICE X supercomputer. This is the second Read more…
October 8, 2014
The Air Force Research Laboratory recently welcomed its newest supercomputer, a 1.28 petaflops Cray XC30 machine dubbed “Lightning,” nearly doubling its su Read more…
July 4, 2013
A new SGI system has been installed at Wright-Patterson Air Force base in Dayton, Ohio as part of the Department of Defense's HPC Modernization Program. The Air Force will be using the new SGI ICE X machine for particular modeling and simulation efforts as well as.... Read more…
February 11, 2013
The Air Force taps Green500 list creator to design a better class of insect-like drones. 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…
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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