Intel used the latest MLPerf Inference (version 3.1) results as a platform to reinforce its developing “AI Everywhere” vision, which rests upon 4th gen Xeon CPUs and Gaudi2 (Habana) accelerat …
MLCommons this week issued the results of its latest MLPerf Inference (v3.1) benchmark exercise. Nvidia was again the top performing accelerator, but Intel (Xeon CPU) and Habana (Gaudi1 and 2) pe …
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September 12, 2023
During a recent earnings call, Tesla CEO Elon Musk, the world's richest man, summed up the shortage of Nvidia enterprise GPUs in a few sentences. "We're us Read more…
September 10, 2023
The shortage of Nvidia's GPUs has customers searching for scrap heap to kickstart makeshift AI projects, and Intel is benefitting from it. Customers seeking qui Read more…
September 7, 2023
At the recent Hot Chips meeting, Intel revealed technical specifications and features for the next-generation Xeon architecture arriving in 2024. While the next Read more…
September 6, 2023
Every vendor releases benchmarks when introducing a new processor. There are lots of application-based benchmarks available for HPC, and to be sure, vendors wil Read more…
September 1, 2023
The U.S. has put more curbs that block the sale of certain Nvidia GPUs to the Middle East, largely under fears that the technology will be accessible to China. The setback for Nvidia was revealed in the company's 10K filing with the U.S. Securities and Exchange Commission. Read more…
August 31, 2023
Supercomputing remains largely an on-premises affair for many reasons that include horsepower, security, and system management. Companies need more time to move Read more…
August 31, 2023
Google scientists Jeff Dean and Amin Vahdat delivered a fascinating tour of major ML hardware and software design trends in their joint Hot Chips 23 opening k Read more…
August 30, 2023
The dominance of Nvidia GPUs has companies scrambling to find non-GPU alternatives, and another mainstream option has emerged with Google's TPU v5e AI chip. Read more…
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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