November 15, 2023
Software implementation in high-performance computing is getting more fragmented as organizations opt for tools in their walled garden environments. Howeve Read more…
May 18, 2023
If you work in scientific computing, MPI (message passing interface) is likely a part of your life. It may be hidden underneath the applications you run or you Read more…
March 10, 2023
The emergence of Covid in 2020 saw an explosion in HPC-powered health research. As the pandemic raged on, though, one limiting factor became increasingly clear: Read more…
September 26, 2022
Since 2017, plans for the Leadership-Class Computing Facility (LCCF) have been underway. Slated for full operation somewhere around 2026, the LCCF’s scope ext Read more…
February 25, 2022
The Covid-19 pandemic has brought into sharp relief how small elements of a virus can play a crucial role in combating it with therapeutic drugs and vaccines. I Read more…
December 17, 2021
2021 marked the 18th annual HPCwire Readers’ and Editors’ Choice Awards. Coming off a tumultuous 2020, this year marked something of a return to normalcy: m 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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