April 27, 2023
Oak Ridge National Laboratory's exascale Frontier supercomputer – the first public exascale system in the world – debuted almost a year ago. Now, more and m Read more…
April 7, 2023
The close of the 2023 Winter Classic Invitational Student Cluster Competition is coming up fast, and I have to get some material out to you, our vast viewing au Read more…
January 20, 2023
UT-Battelle, which manages Oak Ridge National Laboratory (ORNL) for the U.S. Department of Energy, has appointed Jeff Smith as interim director for the lab as t Read more…
December 2, 2022
The Frontier supercomputer – still fresh off its chart-topping 1.1 Linpack exaflops run and maintaining its number-one spot on the Top500 list – was still v Read more…
November 14, 2022
The 60th edition of the Top500 list, revealed today at SC22 in Dallas, Texas, showcases many of the same systems as the previous installment, with Frontier stil Read more…
September 19, 2022
The are many issues in quantum computing today – among the more pressing are benchmarking, networking and development of hybrid classical-quantum approaches. Read more…
August 17, 2022
“It is my privilege to welcome you to the dedication of Frontier, the supercomputer that broke the exascale barrier.” That was the introduction by Oak Ridge National Laboratory Director Thomas Zacharia, at a small, public event on August 17 to officially dedicate the supercomputer, which in May became the first system to achieve over 1.0 exaflops of 64-bit performance on the... Read more…
August 16, 2022
The Quantum Science Center (QSC), headquartered at Oak Ridge National Laboratory, is one of five such centers created by the National Quantum Initiative Act in 2018 and run by the Department of Energy. They all have distinct and overlapping goals. That’s sort of the point, to bring both focus and cooperation... Read more…
The increasing complexity of electric vehicles result in large and complex computational models for simulations that demand enormous compute resources. On-premises high-performance computing (HPC) clusters and computer-aided engineering (CAE) tools are commonly used but some limitations occur when the models are too big or when multiple iterations need to be done in a very short term, leading to a lack of available compute resources. In this hybrid approach, cloud computing offers a flexible and cost-effective alternative, allowing engineers to utilize the latest hardware and software on-demand. Ansys Gateway powered by AWS, a cloud-based simulation software platform, drives efficiencies in automotive engineering simulations. Complete Ansys simulation and CAE/CAD developments can be managed in the cloud with access to AWS’s latest hardware instances, providing significant runtime acceleration.
Two recent studies show how Ansys Gateway powered by AWS can balance run times and costs, making it a compelling solution for automotive development.
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.
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