May 31, 2023
The end goal is in sight for the multi-institutional Exascale Computing Project (ECP), which launched in 2016 with a mandate from the Department of Energy (DOE) Read more…
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…
May 12, 2023
Travis Humble is the director the Quantum Science Center (QSC) at Oak Ridge National Laboratory. QSC is one of six National QIS Research established by the U.S. National Quantum Initiative Act (NQIA) in 2018 and being overseen by the Department of Energy. Hopes are high that these centers, through their own research and in collaboration... 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…
April 24, 2023
February 14th to April 15th – it’s been a long run for the 2023 Winter Classic Student Cluster Competition. 63 students from HBCU and HSI schools learned ha Read more…
April 7, 2023
It’s an exciting time in supercomputing, with functional exascale systems beginning to consistently run crucial workloads. The Frontier supercomputer at Oak R 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…
April 1, 2023
In this monthly feature, we’ll keep you up-to-date on the latest career developments for individuals in the high-performance computing community. Whether it� 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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