March 24, 2022
Digital biology and healthcare have been a long time coming. In fact, they’re hardly here in any complete sense. But they seem much closer and were on impressive virtual display at GTC22 in a blend of product introductions/updates and promising case histories underpinned by – no surprise – Nvidia technology and collaborator expertise. It is Nvidia’s conference... Read more…
April 12, 2021
Nvidia Corp. continues to expand its Clara healthcare platform with the addition of computational drug discovery and medical imaging tools based on its DGX A100 platform, related InfiniBand networking and its AGX developer kit. The Clara partnerships announced during... Read more…
May 18, 2020
Supercomputing, big data and artificial intelligence are crucial tools in the fight against the coronavirus pandemic. Around the world, researchers, corporation Read more…
May 14, 2020
A new set of AI models released by the U.S. National Institutes of Health (NIH) in collaboration with Nvidia is designed to help clinicians detect and examine n 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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