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 8, 2023
A wintery mix with a chance for scattered dependencies was the forecast as students tackled the NASA WRF Challenge in the 2023 Winter Classic Invitational Stude Read more…
November 25, 2022
I left Dallas very early Friday morning after the conclusion of SC22. I had a race with the devil to get from Dallas to Mountain View, Calif., by Sunday. Accord Read more…
April 15, 2022
“HPC Matters!” was the big, bold title of a talk by Piyush Mehrotra, division chief of NASA’s Advanced Supercomputing (NAS) Division at its Ames Research Center, during the meeting of the HPC Advisory Council at Stanford last week. At the meeting, Mehrotra offered a glimpse into the state of supercomputing at NASA—and how its systems are being applied. Read more…
March 18, 2022
NASA hosted and mentored the twelve teams competing in the Winter Classic Invitational Student Cluster Competition last week and we’re ready to reveal the results. The student teams competed to run and optimize three subsets of the NAS Parallel benchmarks, namely BT-MZ, SP-MZ, and the ever so challenging... Read more…
December 15, 2021
The last moon landing occurred nearly half a century ago, in December of 1972. NASA’s Artemis III mission is looking to change that, with the agency planning Read more…
November 12, 2021
This year, Penn State launched the NEID (NN-explore Exoplanet Investigations with Doppler spectroscopy) astronomical spectrograph, part of a collaboration betwe Read more…
June 9, 2021
Solar winds are a hot topic in the HPC world right now, with supercomputer-powered research spanning from the Princeton Plasma Physics Laboratory (which used Oak Ridge’s Titan system) to University College London (which used resources from the DiRAC HPC facility). One of the larger... 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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