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…
December 27, 2021
Today, the LLVM compiler infrastructure world is essentially inescapable in HPC. But back in the 2000 timeframe, LLVM (low level virtual machine) was just getting its start as a new way of thinking about how to overcome shortcomings in the Java Virtual Machine. At the time, Chris Lattner was a graduate student of... Read more…
August 10, 2021
Intel reported in a blog this week that its adoption of the open source LLVM architecture for Intel’s C/C++ compiler is complete. The transition is part of In Read more…
July 13, 2021
The recent proliferation of new hardware technologies has galvanized the high-performance computing (HPC) community and created the ability to deliver the natio Read more…
June 9, 2021
The Exascale Computing Project (ECP) is working to combine two key technologies, LLVM and continuous integration (CI), to ensure that current and future compile 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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