The IBM-Meta AI Alliance Promotes Safe and Open AI Progress

IBM and Meta have co-launched a massive industry-academic-government alliance to shepherd AI development. The new group has united under the AI Alliance banner to promote responsible innovation i

By Doug Eadline

ChatGPT Friendly Programming Languages
(hello-world.llm)

 Using OpenAI's ChatGPT to write code is an alluring goal. Describing "what to" solve, but not "how to solve" would be a huge breakthrough in computer programming. Alas, we are nowhere near this

By Doug Eadline

IBM Quantum Summit: Two New QPUs, Upgraded Qiskit, 10-year Roadmap and More

IBM kicks off its annual Quantum Summit today and will announce a broad range of advances including its much-anticipated 1121-qubit Condor QPU, a smaller 133-qubit Heron QPU, that’s optimized f

By John Russell

The Annual SCinet Mandala

Perhaps you have seen images of Tibetan Buddhists creating beautiful and intricate images with colored sand. These sand mandalas can take weeks to create, only to be ritualistically dismantled wh

By Doug Eadline

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Whitepaper

Penguin Computing Scyld Cloud Central™: A New Cloud-First Approach to HPC and AI Workloads

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.

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QCT POD- An Adaptive Converged Platform for HPC and AI

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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