Clustering resources for faster performance is not new. In the early days of clustering, the Beowulf project demonstrated that high performance was achievable from commodity hardware. These days, …
Editors Note: Additional Coverage of the AWS-Nvidia 65 Exaflop ‘Ultra-Cluster’ and Graviton4 can be found on our sister site Datanami.
Amazon Web Services will soon be home to a new Nvidia …
Check out our list of 108 illustrious winners across 22 different categories of HPC.
November 27, 2023
Should you start exploring quantum computing? Yes, said a panel of analysts convened at Tabor Communications HPC and AI on Wall Street conference earlier this y Read more…
November 16, 2023
Nvidia was invisible with a very small booth and limited floor presence, but thanks to its sheer AI dominance, it was a winner at the Supercomputing 2023. Nv Read more…
November 13, 2023
The fall 2023 TOP500 list is out and Frontier retains its top spot and is still the only exascale machine. However, five new or upgraded systems have shaken up Read more…
November 8, 2023
If the U.S. government intends to curb China's adoption of emerging RISC-V architecture to develop homegrown chips, it may be getting late. Last month, China Read more…
November 6, 2023
Roaring demand for Generative AI enabling technology – mainly GPUs and GPU-accelerated systems – prompted Intersect360 Research to nudge up its 2023 HPC-AI Read more…
November 1, 2023
Hyperscalers Google, Amazon, and Meta have developed barebones servers by stripping down parts, but you cannot buy them off the shelf. Startup Oxide took on Read more…
October 19, 2023
The recent HPC + AI on Wall Street show presented a panel that brought together key vendors to discuss the current GPU Squeeze (shortage). The "Squeeze" is Read more…
October 11, 2023
Financial institutions need more compute capacity when trading spikes during the day, which could be available by just flicking a switch. Gone are the days of p 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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