May 25, 2023
ISC’s closing keynote this year was given jointly by a pair of distinguished HPC leaders, Thomas Sterling of Indiana University and Estela Suarez of Jülich S Read more…
May 23, 2023
Europe has clearly jumped into the global race to achieve practical quantum, though perhaps a step later (by a year or two) than the U.S. and China. Impressivel Read more…
May 21, 2023
At ISC this week, Nvidia announced plans for a new hybrid classical-quantum computing lab with partners Jülich Supercomputing Centre and ParTec. The new lab is Read more…
July 27, 2022
Graphics processors are taking on a new role beyond gaming and artificial intelligence – they are now serving as surrogate quantum computers until the real hardware arrives. The Jülich Supercomputing Centre is using GPUs and a software toolkit from Nvidia to emulate quantum computers and research... Read more…
January 21, 2022
On Saturday, an enormous eruption on the volcanic islands of Hunga Tonga and Hunga Haʻapai shook the Pacific Ocean. The explosion, which could be heard six tho Read more…
December 20, 2021
Photovoltaic solar – what most people know as solar panels – generated a record 821 terawatt-hours in 2020, a 23 percent increase over 2019 and an impressiv Read more…
December 10, 2021
The exascale era of supercomputing is here, with early applications of confirmed systems including quantum circuit simulation, fusion energy and advanced spectr Read more…
June 7, 2021
In this regular feature, HPCwire highlights newly published research in the high-performance computing community and related domains. From parallel programmin 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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