May 2, 2023
Today, AMD reported its financial results for Q1 2023. The headline: revenues ($5.4 billion) are down by 9.2% year-over-year, just barely beating expectations a 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 18, 2023
Weather and climate applications are some of the most important for high-performance computing, often serving as raisons d'être and flagship workloads for the 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…
March 16, 2023
Optical I/O is being singled out by top companies to push computing beyond exascale and into zettascale. The technology was singled out in a recent speech by AM Read more…
March 13, 2023
After getting bruised in servers by AMD, Intel hopes to stop the bleeding in the server market with next year's chip offerings. The difference-making products will be Sierra Forest and Granite Rapids, which are due out in 2024, said Dave Zinsner, chief financial officer at Intel, last week at the Morgan Stanley Technology, Media and Telecom conference. Read more…
March 10, 2023
The emergence of Covid in 2020 saw an explosion in HPC-powered health research. As the pandemic raged on, though, one limiting factor became increasingly clear: Read more…
February 21, 2023
If a zettascale computer were assembled using today's supercomputing technologies, it would consume about 21 gigawatts, or equivalent to the energy produced by 21 nuclear power plants. The math was presented in a keynote speech by AMD CEO Lisa Su at the ISSCC trade show being held in San Francisco held this week. A zettaflop supercomputer would have the computing capability... 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
HPCwire is a registered trademark of Tabor Communications, Inc. Use of this site is governed by our Terms of Use and Privacy Policy.
Reproduction in whole or in part in any form or medium without express written permission of Tabor Communications, Inc. is prohibited.