November 8, 2023
If the U.S. government intends to curb China's adoption of emerging RISC-V architecture to develop homegrown chips, it may be getting late. Last month, China Read more…
October 4, 2023
The configuration of Europe's first exascale supercomputer, Jupiter, has been finalized, and it is a win for Nvidia and a disappointment for x86 chip vendors In Read more…
July 31, 2023
Esperanto Technologies has ambitious plans for its next RISC-V processor: to undo the accelerator model and build a chip that has both CPU and GPU capabilities Read more…
July 24, 2023
A specification that could standardize the development of RISC-V server chips and systems is currently being drafted by RISC-V International, an organization th Read more…
May 28, 2023
We in HPC sometimes roll our eyes at the term “AI supercomputer,” but a new system from Nvidia might live up to the moniker: the DGX GH200 AI supercomputer. 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…
March 13, 2023
After getting bruised in servers by AMD, Intel hopes to stop the bleeding in the server market with next year's chip offerings. The difference-making products will be Sierra Forest and Granite Rapids, which are due out in 2024, said Dave Zinsner, chief financial officer at Intel, last week at the Morgan Stanley Technology, Media and Telecom conference. Read more…
December 16, 2022
The European Union will release €270 million in funds as it tries to attain technology independence by building chips based on the open RISC-V instruction set 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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