Finding Opportunity in the High-Growth “AI Market” 

December 6, 2023

 “What’s the size of the AI market?” It’s a totally normal question for anyone to ask me. After all, I’m an analyst, and my company, Intersect360 Res Read more…

Grace Hopper’s Big Debut in AWS Cloud While Graviton4 Launches

November 29, 2023

Editors Note: Additional Coverage of the AWS-Nvidia 65 Exaflop ‘Ultra-Cluster’ and Graviton4 can be found on our sister site Datanami. Amazon Web Service Read more…

re:Invent 2023: AWS Talks a Little Quantum, Showcases Error Correction Progress

November 28, 2023

Quantum computing held sway in the last few minutes of AWS senior vice president Peter DeSantis’ keynote yesterday at the AWS re:Invent 2023 conference, being Read more…

AWS/Harvard Report Optical Interface Advance for Quantum Networks

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…

AWS Summit 2023

AWS Cramming up to 20,000 Nvidia GPUs in AI Supercomputing Clusters 

July 27, 2023

The AI supercomputing options in the cloud have expanded at an unprecedented rate over the last few weeks.  Amazon joined the party on Wednesday by announci Read more…

Catch the Flying Qubit – AWS Center for Quantum Networking

July 11, 2023

Quantum networking – like quantum computing – holds tantalizing promise. Rather than use classical bits, quantum networks work with quantum bits (qubits) an Read more…

AWS Makes Homegrown Arm Processor Available for Cloud Supercomputing

June 22, 2023

AWS has finally made available its Arm-based CPUs available for supercomputing – but it's not a chip you can buy off the shelf. The chip, Graviton3E, is acces Read more…

Shutterstock 1194728515

Microsoft and ETH Take Aim at Quantum Computing’s Hype (and Promise)

May 2, 2023

A fascinating ACM paper by researchers Torsten Hoefler (ETH Zurich), Thomas Häner (Microsoft*) and Matthias Troyer (Microsoft) – "Disentangling Hype from Pra Read more…

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Whitepaper

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Making the Most of Today’s Cloud-First Approach to Running HPC and AI Workloads With Penguin Scyld Cloud Central™

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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.

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