October 13, 2016
A team of US scientists may have just breathed new life into a faltering Moore’s law and advanced the limits of microelectronic miniaturization with the fabrication of a transistor with a 1nm gate. The breakthrough portends a path beyond silicon-based transistors, which have been widely predicted to hit a wall at 5-nanometers. Read more…
July 28, 2016
The final International Technology Roadmap for Semiconductors (ITRS) is now out. The highly-detailed multi-part report, collaboratively published by a group of international semiconductor experts, offers guidance on the technological challenges and opportunities for the semiconductor industry through 2030. One of the major takeaways is the insistence that Moore's law will continue for some time even though traditional transistor scaling (through smaller feature sizes) is expected to hit an economic wall in 2021. Read more…
March 4, 2015
Over the last half a century, computers have transformed nearly every facet of society. The information age and its continuing evolution can be traced to the i Read more…
July 2, 2014
The effect of five decades of exponential progress with silicon chips doubling in speed every couple years as observed by Intel cofounder Gordon Moore in 1965 c 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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