October 19, 2022
Cerebras Systems has secured another U.S. government win for its wafer scale engine chip – which is considered the largest chip in the world. The company's chip technology will be part of a research project sponsored by the National Nuclear Security Administration to find... Read more…
August 6, 2022
Lawrence Livermore National Laboratory (LLNL) is one of the laboratories that operates under the auspices of the National Nuclear Security Administration (NNSA), which manages the United States’ stockpile of nuclear weapons. Amid major efforts to modernize that stockpile, LLNL has announced that researchers from its own Energetic Materials Center... Read more…
June 21, 2022
Additional details of the architecture of the exascale El Capitan supercomputer were disclosed today by Lawrence Livermore National Laboratory’s (LLNL) Terri Read more…
March 30, 2022
From weather sensors and autonomous vehicles to electric grid monitoring and cloud gaming, the world’s edge computing is getting increasingly complex — but the world of HPC hasn’t necessarily caught up to these rapid innovations at the edge. At a panel at Nvidia’s virtual GTC22 (“HPC, AI, and the Edge”), five experts discussed how leading-edge HPC applications... Read more…
September 28, 2021
In support of the Department of Energy’s National Nuclear Security Administration (NNSA), the Tri-Lab CTS-2 system contract award was announced last week. The NNSA TriLab partnership – comprising Livermore, Los Alamos and Sandia national labs – awarded Dell Technologies... Read more…
March 11, 2021
Through the magic of video and Zoom, we've reached out to five Winter Classic Invitational cluster competition teams for our trademark up close and personal interviews. Our associate Jessi Lanum has given us Cliff Notes for each interview, along with some teasers, but check out the videos to get... Read more…
February 18, 2021
A near node local storage innovation called Rabbit factored heavily into Lawrence Livermore National Laboratory’s decision to select Cray’s proposal for its CORAL-2 machine, the lab’s first exascale-class supercomputer, El Capitan. Details of this new storage technology were revealed... Read more…
December 8, 2020
In this regular feature, HPCwire highlights newly published research in the high-performance computing community and related domains. From parallel programming Read more…
Five Recommendations to Optimize Data Pipelines
When building AI systems at scale, managing the flow of data can make or break a business. The various stages of the AI data pipeline pose unique challenges that can disrupt or misdirect the flow of data, ultimately impacting the effectiveness of AI storage and systems.
With so many applications and diverse requirements for data types, management systems, workloads, and compliance regulations, these challenges are only amplified. Without a clear, continuous flow of data throughout the AI data lifecycle, AI models can perform poorly or even dangerously.
To ensure your AI systems are optimized, follow these five essential steps to eliminate bottlenecks and maximize efficiency.
Karlsruhe Institute of Technology (KIT) is an elite public research university located in Karlsruhe, Germany and is engaged in a broad range of disciplines in natural sciences, engineering, economics, humanities, and social sciences. For institutions like KIT, HPC has become indispensable to cutting-edge research in these areas.
KIT’s HoreKa supercomputer supports hundreds of research initiatives including a project aimed at predicting when the Earth’s ozone layer will be fully healed. With HoreKa, projects like these can process larger amounts of data enabling researchers to deepen their understanding of highly complex natural processes.
Read this case study to learn how KIT implemented their supercomputer powered by Lenovo ThinkSystem servers, featuring Lenovo Neptune™ liquid cooling technology, to attain higher performance while reducing power consumption.
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