May 25, 2023
As HPC and AI continue to rapidly advance, the alluring vision of nuclear fusion and its endless zero-carbon, low-radioactivity energy is the sparkle in many a Read more…
March 30, 2023
When the EuroHPC Summit was held last week in Gothenburg, there was a distinct shift in tone for the maturing supercomputing play. With LUMI and Leonardo – pl Read more…
November 14, 2022
Over the past months, Nvidia has put a spotlight on its OVX hardware – purpose-built systems aimed at its Omniverse digital twins platform. Now, at SC22, Nvid Read more…
October 19, 2022
In late 2020, the European Union announced plans for its Destination Earth (“DestinE”) moonshot project to create multiple digital twins of Earth, including Read more…
June 1, 2022
“I don’t think anybody here is ignorant of what supercomputing is,” said Rev Lebaredian, Nvidia’s vice president of Omniverse and Simulation Technology, as he opened the first keynote at ISC 2022 in Hamburg, Germany. “We’ve been building supercomputers for decades, but our uses for them have been evolving over time.” In his keynote, Lebaredian made the case for what he views as... Read more…
March 25, 2022
With climate change accelerating and fossil fuel supplies proving increasingly contentious, ensuring a secure supply of clean energy is top-of-mind for many res Read more…
March 22, 2022
An accurate digital twin can be a boon to scientific endeavors, from recreating individual buildings in a city to understand energy use to recreating the Earth’s climate system to understand the effects of policies on climate change. At GTC21, Nvidia made waves by announcing that its Modulus framework for physics-based ML models and its... Read more…
November 15, 2021
Power plants are both crucial and mercurial; the whims of wind speeds, light availability, ambient temperatures and equipment failures can, under the wrong circ 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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