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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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Data And Storage At The Center Of The AI Stack

FuriosaAI and Broadcom Team Up to Build Rack-Scale Inference Clusters

FuriosaAI and Broadcom are teaming up to develop a next-generation AI inference cluster that combines hundreds of FuriosaAI’s third-generation chips with Broadcom’s high-bandwidth, low-latency Ethernet interconnect. The as-yet unnamed system will start sampling in early 2028. FuriosaAI is a South Korean chip company founded in 2017 by June Paik, a former Samsung and AMD engineer […]

The post FuriosaAI and Broadcom Team Up to Build Rack-Scale Inference Clusters appeared first on HPCwire.

Harness the Power of Rack-Scale Performance for Large-Scale AI

AI has entered an industrial phase, no longer confined to isolated models or experimental deployments. AI now operates as always-on AI factories that continuously transform electricity and data into intelligence at scale. For service providers and neoclouds, this shift introduces a new class of infrastructure demands. Modern AI workloads require processing hundreds of thousands of […]

The post Harness the Power of Rack-Scale Performance for Large-Scale AI appeared first on HPCwire.

GPUs And RAM Are In Short Supply, But The Real Bottleneck For AI Is Electricians

TOP500 News



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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