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The Influence of HPC-ers: Setting the Standard for What’s “Cool”
Jan. 16, 2025

A look back to supercomputing at the turn of the century

When I first attended the Supercomputing (SC) conferences back in the early 2000s as an IBMer working in High Performance Computing (HPC), it was obvious this conference was intended for serious computer science researchers and industries singularly focused on pushing the boundaries of computing. Linux was still in its infancy. I vividly remember having to re-compile kernels with newly released drivers every time there was a new server that came to market just so I could get the system to PXE boot over the network. But there was one …


The Evolution, Convergence and Cooling of AI & HPC Gear
Nov. 7, 2024

Years ago, when Artificial Intelligence (AI) began to emerge as a potential technology to be harnessed as a powerful tool to change the way the world works, organizations began to kick the AI tires by exploring it’s potential to enhance their research or business. However, to get started with AI, neural networks needed to be created, data sets trained, and microprocessors were needed that could perform matrix-multiplication calculations ideally suited to perform these computationally demanding tasks. Enter the accelerator.


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CERN: Smarter Decisions at the Speed of Collisions

Machine learning is reshaping how ATLAS and CMS filter collisions in real time May 7, 2026 — Smart and fast decision making is key when dealing with the onslaught of collisions at the LHC. At the High-Luminosity LHC (HiLumi LHC), the ATLAS and CMS experiments are expected to process detector data at rates corresponding to roughly a […]

The post CERN: Smarter Decisions at the Speed of Collisions appeared first on HPCwire.

AMD Launches Instinct MI350P PCIe Cards for Enterprise AI Inference

May 7, 2026 — As organizations adopt AI, many discover that their infrastructure struggles to keep up. Running AI in the cloud is an option, but the cloud can introduce privacy concerns and unpredictable costs. Upgrading on-prem infrastructure is another option, but supporting large GPU-accelerator platforms can require expensive redesigns in data center power and cooling. […]

The post AMD Launches Instinct MI350P PCIe Cards for Enterprise AI Inference appeared first on HPCwire.

Arista Rides AI Scale Out Networks, Moves Into Scale Across, And Awaits Scale Up

If You Can Make A Compute Engine, You Can Sell A Compute Engine

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The Influence of HPC-ers: Setting the Standard for What’s “Cool”
Jan. 16, 2025

A look back to supercomputing at the turn of the century

When I first attended the Supercomputing (SC) conferences back in the early 2000s as an IBMer working in High Performance Computing (HPC), it was obvious this conference was intended for serious computer science researchers and industries singularly focused on pushing the boundaries of computing. Linux was still in its infancy. I vividly remember having to re-compile kernels with newly released drivers every time there was a new server that came to market just so I could get the system to PXE boot over the network. But there was one …


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11/2025 Highlights

On the 66th edition of the TOP500 El Capitan remains No. 1 and JUPITER Booster becomes the fourth Exascale system.

The JUPITER Booster system at the EuroHPC / Jülich Supercomputing Centre in Germany at No. 4 submitted a new measurement of 1.000 Exflop/s on the HPL benchmark. It is the fourth Exascale system on the TOP500 and the first one outside of the USA.

El Capitan, Frontier, and Aurora are still leading the TOP500. All three are installed at DOE laboratories in the USA.

The El Capitan system at the Lawrence Livermore National Laboratory, California, USA remains the No. 1 system on the TOP500. The HPE Cray EX255a system was remeasured with 1.809 Exaflop/s on the HPL benchmark. LLNL also achieved 17.41 Petaflop/s on the HPCG benchmark which makes the system the No. 1 on this ranking as well.

El Capitan has 11,340,000 cores and is based on AMD 4th generation EPYC processors with 24 cores at 1.8 GHz and AMD Instinct MI300A accelerators. It uses the Cray Slingshot 11 network for data transfer and achieves an energy efficiency of 60.9 Gigaflops/watt.

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