May 22, 2023
Fresh off their third Top500 win for Frontier – now with an 8.4% higher Linpack score – the HPC team at Oak Ridge National Laboratory had some exciting news to share today. Frontier has passed its acceptance and is taking on grand scientific challenges. “Acceptance of Frontier took place at the... Read more…
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…
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 12, 2022
HPCwire presents our interview with Bronson Messer, distinguished scientist and director of Science at the Oak Ridge Leadership Computing Facility (OLCF), ORNL, and an HPCwire 2022 Person to Watch. Messer recaps ORNL's journey to exascale and sheds light on how all the pieces line up to support the all-important science. Also covered are the role... Read more…
August 3, 2022
Rare, severe flooding struck both Kentucky and Missouri in the last week alone — and with climate change accelerating, such events are likely to continue. However, flood modeling remains computationally expensive. Now, researchers from Oak Ridge National Laboratory (ORNL) and Tennessee Technological University have created the TRITON toolkit, which leverages... Read more…
July 1, 2022
Oak Ridge National Laboratory’s exascale Frontier system may be stealing some of the spotlight, but the lab’s 148.6 Linpack petaflops Summit system is still Read more…
June 28, 2022
With the Linpack exaflops milestone achieved by the Frontier supercomputer at Oak Ridge National Laboratory, the United States is turning its attention to the next crop of exascale machines, some 5-10x more performant than Frontier. At least one such system is being planned for the 2025-2030 timeline, and the DOE is soliciting input from the vendor community... Read more…
June 8, 2022
Back in 2008, the U.S. Defense Advanced Research Projects Agency (DARPA) set an ambitious target: an exascale supercomputer in a 20-megawatt envelope. That targ 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.
© 2023 HPCwire. All Rights Reserved. A Tabor Communications Publication
HPCwire is a registered trademark of Tabor Communications, Inc. Use of this site is governed by our Terms of Use and Privacy Policy.
Reproduction in whole or in part in any form or medium without express written permission of Tabor Communications, Inc. is prohibited.