Roaring demand for Generative AI enabling technology – mainly GPUs and GPU-accelerated systems – prompted Intersect360 Research to nudge up its 2023 HPC-AI forecast, which was first given at …
This week Nvidia released a paper demonstrating how generative AI can be used in semiconductor design. Nvidia chief scientist Bill Dally announced the new paper during his keynote at the Internat …
Check out our list of 108 illustrious winners across 22 different categories of HPC.
October 25, 2023
Everyone is looking to cash in on the GPU and AI craze, even a cannabis company. Last month, the Colorado based American Cannabis Company agreed to acquire H Read more…
October 24, 2023
D-Wave Quantum Inc. (formerly D-Wave Systems) is once again facing delisting from the New York Stock Exchange because its stock price has dropped and hovered be Read more…
October 24, 2023
Atom Computing, a developer of neutral atom-based quantum computers, today announced it has built a 1,225-site atomic array that contains 1,180 qubits. This fol Read more…
October 23, 2023
Optical networking inside and outside data centers is a way to create a sustainable large-scale computational infrastructure as artificial intelligence and othe Read more…
October 16, 2023
Preventing signal loss and garbling are key goals in developing effective quantum networks and eventually a quantum Internet. Today, AWS and Harvard researchers Read more…
October 10, 2023
We hear a lot about quantum computers – sometimes too much – but not as much about quantum networking which will also be a critical component in making wide Read more…
October 5, 2023
Somewhat quietly, while quantum hardware developers have been steadily improving today's early quantum computers (scale and error correction), developers of qua Read more…
October 3, 2023
The steady research into developing real-world applications for quantum computing is piling up interesting use cases. Today, IBM reported on work with Boeing to 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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