Inside AWS’s Plans to Make S3 Faster and Better

As far as big data storage goes, Amazon S3 has won the war. Even among storage vendors whose initials are not A.W.S., S3 is the defacto standard for storing lots of data. But AWS isn’t resting

By Alex Woodie

Quantum Market, Though Small, will Grow 22% and Hit $1.5B in 2026

Few markets as small as the quantum information sciences market generate as much lively discussion. Hyperion Research pegged the worldwide quantum market at $848 million for 2023 and expects it t

By John Russell

AMD’s Horsepower-packed MI300X GPU Beats Nvidia’s Upcoming H200

AMD and Nvidia are locked in an AI performance battle – much like the gaming GPU performance clash the companies have waged for decades.

AMD has claimed its new Instinct MI300X GPU is the fa

By Agam Shah

Finding Opportunity in the High-Growth “AI Market” 

 “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 Research, specializes in scalable, hig

By Addison Snell

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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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Sponsored by Penguin Solutions

Whitepaper

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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