November 17, 2022
For three years running, ACM has awarded not only its long-standing Gordon Bell Prize (read more about this year’s winner here!) but also its Gordon Bell Spec Read more…
November 17, 2022
Large language models (LLMs) have taken the tech world by storm over the past couple of years, dominating headlines with their ability to generate convincing hu Read more…
November 18, 2021
For the second (and, hopefully, final) year in a row, SC21 included a second major research award alongside the ACM 2021 Gordon Bell Prize: the Gordon Bell Special Prize for High Performance Computing-Based COVID-19 Research. Last year, the first iteration of this award went to simulations of the SARS-CoV-2 spike protein; this year, the prize went... Read more…
March 11, 2021
Four months ago, Rommie Amaro and her colleagues were accepting the first-ever Gordon Bell Special Prize for High Performance Computing-Based COVID-19 Research. Read more…
November 19, 2020
2020 has proven a harrowing year – but it has produced remarkable heroes. To that end, this year, the Association for Computing Machinery (ACM) introduced the 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.
© 2023 HPCwire. All Rights Reserved. A Tabor Communications Publication
Reproduction in whole or in part in any form or medium without express written permission of Tabor Communications, Inc. is prohibited.