July 24, 2023
While not a golden HPC spike, the final blade has been loaded into Aurora. As mentioned previously, final preparation of Aurora is underway. Aurora the "almost 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…
June 22, 2023
Aurora, one of the first three U.S. exascale supercomputers, has not had a straightforward path to installation and operation. The system has been repeatedly re Read more…
June 20, 2023
The high-performance computing options are thinning, and HPE is one of the last U.S. companies standing to build supercomputers – a fact indirectly acknowledg Read more…
May 21, 2023
Nvidia is ramping up deployment of its Superchips – amalgamated chips that include either two CPUs (the Grace CPU Superchip) or a CPU and a GPU (the Grace Hop Read more…
April 29, 2023
HPCwire 2023 Person to Watch Trish Damkroger is a long-time HPC enthusiast and seasoned exec hailing from a 17 year tenure at Lawrence Livermore Lab, followed by five years of leading HPC strategy at Intel, before one year ago making the move to HPE (where she is Chief Product Officer and Senior Vice President, HPC, AI & Labs). Read more…
April 24, 2023
February 14th to April 15th – it’s been a long run for the 2023 Winter Classic Student Cluster Competition. 63 students from HBCU and HSI schools learned ha Read more…
April 4, 2023
HPE today rolled out its first file storage offering for GreenLake, its everything-as-a-service offering. The new HPE GreenLake for File Storage offering pairs 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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