March 1, 2023
Ayar Labs, founded in 2015, is pursuing optics as a means of driving higher interconnect speeds and efficiencies in computing. Now, the company is announcing th Read more…
April 24, 2019
A team of UC Berkeley researchers has reported fabricating the “largest integrated photonic switch ever.” Their achievement comes at a time when there are m Read more…
April 26, 2018
While not new, the challenges presented by computer cabling/PCB circuit routing design – cost, performance, space requirements, and power management – have Read more…
February 9, 2011
If chip progress stalls, blame the interconnect bottleneck. Read more…
February 9, 2010
Wireless technology promises energy-efficient chip-to-chip communication. 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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