May 14, 2015
Engineers at IBM have developed a fully integrated wavelength multiplexed silicon photonics chip, which the company says will soon enable manufacturing of 100 G Read more…
September 4, 2014
For much of the history of aviation, designers and engineers ran their calculations and experiments without the benefit of computers. But as the price of comput Read more…
July 16, 2014
Scientists at the Weizmann Institute say they have developed the world's first photonic router, an important advance towards building a full-on quantum computer Read more…
April 25, 2014
Physicists at UC Santa Barbara (UCSB) have taken a huge leap forward towards what they refer to as a “fully functional quantum computer” – long-considered Read more…
February 5, 2014
An international team of researchers led by Dr. Mark Thompson from the University of Bristol have for the first time successfully generated and manipulated sing Read more…
January 24, 2014
Exascale isn't the only international computing race currently underway. Around the world national interests are also scrambling to build quantum computers capa Read more…
January 23, 2014
For those of you following the D-Wave story, the designers of “the world's first commercial quantum computer" have published a revealing blog entry detailing Read more…
October 23, 2013
"If you think you understand quantum physics, you don't understand quantum physics." — Richard Feynman, Quantum Theorist The first commercial quantum co 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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