January 7, 2019
How do you know if an HPC system, particularly a larger-scale system, is well-suited for deep learning workloads? Today, that’s not an easy question to answer Read more…
January 3, 2019
In November at SC18 in Dallas, HPCwire Readers’ and Editors’ Choice awards program commemorated its 15th year of honoring achievement in HPC, with categories ranging from Best Use of AI to the Workforce Diversity Leadership Award and recipients across a wide variety of industrial and research sectors. Read more…
November 29, 2018
A report published a decade ago conveyed the results of a study aimed at determining if it were possible to achieve 1000X the computational power of the the Read more…
November 21, 2018
During the 30th annual SC conference in Dallas last week, SC18 hosted U.S. Department of Energy Under Secretary for Science Paul M. Dabbar. In attendance Nov. 13-14, Dabbar delivered remarks at the Top500 panel, met with a number of industry stakeholders and toured the show floor. He also met with HPCwire for an interview, where we discussed the role of the DOE in advancing leadership computing. Read more…
November 14, 2018
The CORAL supercomputers Summit and Sierra are now the world's fastest computers and are already contributing to science with early applications. Ahead of SC18, Maciej Chojnowski with ICM at the University of Warsaw discussed the details of the CORAL project with Dr. Dimitri Kusnezov from the U.S. Department of Energy. 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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