April 28, 2022
As the pandemic swept across the world, virtually every research supercomputer lit up to support Covid-19 investigations. But even as the world transformed, the Read more…
March 9, 2021
The COVID-19 pandemic poses a greater challenge to the high-performance computing community than any before. HPCwire's coverage of the supercomputing response t Read more…
February 23, 2021
More than a year ago, the Italian-based Exscalate4CoV consortium stormed onto the scene to fight COVID-19 through drug discovery, powered by supercomputers and Read more…
December 23, 2020
During SC20 in November, the HPCwire Readers’ and Editors’ Choice awards program celebrated its 17th year of honoring outstanding achievements in high-perfo Read more…
December 8, 2020
Well before COVID-19 struck New Mexico, New Mexico was striking COVID-19. Los Alamos National Laboratory (LANL) began its research on COVID-19 in late January, Read more…
November 30, 2020
Supercomputing, big data and artificial intelligence are crucial tools in the fight against the coronavirus pandemic. Around the world, researchers, corporation Read more…
November 18, 2020
Before the COVID-19 pandemic essentially stopped the world in its tracks in March, the global HPC server market was expected to grow from $13.7 billion in 2019 Read more…
November 17, 2020
COVID-19 isn’t over – not even close. With about six months until broad vaccine distribution is expected, the world will likely face a long, difficult winte 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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