August 16, 2023
The default method for accelerating Deep Learning projects is increasing the size of a GPU cluster. However, the cost is increasingly prohibitive. According to� Read more…
July 12, 2023
Worldwide revenue for the public cloud services market totaled $545.8 billion in 2022, an increase of 22.9% over 2021, according to new data from the IDC Worldw Read more…
May 22, 2023
Intel has finally provided specific details on wholesale changes it has made to its supercomputing chip roadmap after an abrupt reversal of an ambitious plan to Read more…
May 21, 2023
At ISC this week, Nvidia announced plans for a new hybrid classical-quantum computing lab with partners Jülich Supercomputing Centre and ParTec. The new lab is Read more…
May 10, 2023
Cloud providers are building armies of GPUs to provide more AI firepower. Google is joining the gang with a new supercomputer that has almost 2.5 times the number of GPUs than the world’s third-fastest supercomputer called LUMI. Google announced an AI supercomputer with 26,000 GPUs at its developer conference on Wednesday. Read more…
March 5, 2023
Intel CEO Pat Gelsinger is taking a no-holds-barred approach to cutting costs as he whips the company back into financial shape. Intel has already exited seven businesses, and recently made wholesale graphics processors changes by axing products and changing its enterprise GPU roadmap. Intel has scrapped a supercomputer GPU codenamed Rialto Bridge, which was advertised... Read more…
February 20, 2023
Microsoft and Google are driving a major computing shift by bringing AI to people via search engines, and one measure of success may come down to the hardware a Read more…
October 18, 2022
Oracle is bringing Nvidia's AI Enterprise software suite alongside thousands of its latest GPUs to its cloud infrastructure, which could fuel the chipmaker’s 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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