March 25, 2020
Chip designers are drawing on new cloud resources along with conventional electronic design automation (EDA) tools to accelerate IC templates from tape-out to c Read more…
June 17, 2013
The Top 500 list of the world's fastest computers has just been announced. Not surprisingly, since it's been reported on prior to the official announcement, the Chinese Tianhe-2 system tops the list. And that is an understatement. We talk with Jack Dongarra, Horst Simon, Hans Meuer and others from the.... Read more…
March 5, 2013
How does the Phi coprocessor measure up to Xeon "Sandy Bridge" brand-mate? Read more…
February 7, 2013
The United Kingdom is rapidly ramping up its HPC capabilities. The nation just launched its third HPC service in the last 12 months, a 200,000-core powerhouse, called "Accelerator," designed to accommodate a wide range of academic and industry workloads. Read more…
December 12, 2012
Intel's manycore wonder comes with its own programming challenges. Read more…
December 6, 2012
With the recent introduction of Intel's first Xeon Phi coprocessors, NVIDIA's latest Kepler GPUs, and AMD's new FirePro S10000 graphics cards, the competition for HPC chip componentry has entered a new phase. The three chipmakers have taken somewhat different paths, though, and it will be up to the market to decide which vendor's approach will win the day. Read more…
October 29, 2012
Kickstarter investment model notches another high-tech success. Read more…
November 2, 2011
Now that the new AMD "Interlagos" Opterons and Intel "Sandy Bridge" EP Xeons have begun shipping, at least for volume deployments, Appro has announced support for the latest x86 CPUs in its upgraded Xtreme-X HPC line-up. The new systems will soon be appearing in supercomputing centers in the US and elsewhere. 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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