November 20, 2023
This year's fantastic Supercomputing 2023 was back in full form. Attendees seemed to be glad that the show was back in Denver, which was a preferred destination Read more…
November 13, 2023
Chinese chip maker SophGo is developing a RISC-V chip based on designs from the U.S. company SiFive, which highlights challenges the U.S. government may face in Read more…
November 12, 2023
Editor note: See SC23 RISC-V events at the end of the article At this year's RISC-V Summit, the unofficial motto was "drain the swamp," that is, x86 and Read more…
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…
July 19, 2023
It is becoming clearer that China's plan to cut reliance on Western chip technology revolves around homegrown chips built using the open RISC-V architecture, wh 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.
© 2023 HPCwire. All Rights Reserved. A Tabor Communications Publication
HPCwire is a registered trademark of Tabor Communications, Inc. Use of this site is governed by our Terms of Use and Privacy Policy.
Reproduction in whole or in part in any form or medium without express written permission of Tabor Communications, Inc. is prohibited.