May 17, 2023
After nearly seven years of service, thousands of user projects, and tens of billions of compute hours, the Cori supercomputer at the National Energy Research S Read more…
February 7, 2023
Time to finally(!) clear the 2022 decks and get the rest of the 2022 Great American Supercomputing Road Trip content out into the wild. The last part of the yea Read more…
November 17, 2022
At the awards ceremony at SC22 in Dallas today, ACM awarded the 2022 ACM Gordon Bell Prize to a team of researchers who used four major supercomputers – inclu 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…
May 4, 2022
With climate change dramatically accelerating, scientists continue to struggle to predict the shape of a substantially warmer world. This is particularly true with regard to weather and storms, which – due to the granular, mercurial processes at play – elude climate scientists more than, say, ice melt projections. Recently, a climate study commissioned by the City and County of San Francisco... Read more…
April 28, 2022
Roughly a year ago the National Energy Research Scientific Computing Center (NERSC) launched Perlmutter, which was hailed at the time as the “world’s fastest AI supercomputer” by Nvidia whose GPUs provide much of Perlmutter’s power. Since then, NERSC has been aggressively ramping up its mixed AI-HPC workload capability – software, early science apps... Read more…
March 10, 2022
In this regular feature, HPCwire highlights newly published research in the high-performance computing community and related domains. From parallel programmin Read more…
May 27, 2021
A ribbon-cutting ceremony held virtually at Berkeley Lab's National Energy Research Scientific Computing Center (NERSC) today marked the official launch of Perlmutter – aka NERSC-9 – the GPU-accelerated supercomputer built by HPE in partnership with Nvidia and AMD. 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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