June 5, 2023
On Wednesday of this week the House Science Committee will hold a hearing as part of the reauthorization effort for the U.S. National Quantum Initiative Act pas Read more…
April 28, 2023
This year, the U.S. National Quantum Initiative Act (NQIA), passed in 2018, is up for re-authorization by Congress. NQIA is a complicated $2B-plus effort and on Read more…
March 9, 2023
Time’s up: nearly everyone agrees it’s about time to become serious about bringing security safeguards to high-performance computing systems, which has been Read more…
January 20, 2023
Security of high-performance computers is being neglected in the pursuit of horsepower, and there are concerns that the ignorance may be costly if safeguards ar Read more…
October 18, 2022
Spun out from Google last March, SandboxAQ is a fascinating, well-funded start-up targeting the intersection of AI and quantum technology. “As the world enter Read more…
October 4, 2022
Last week the Quantum Economic Development Consortium (QED-C) released a new report – Public-Private Partnerships in Quantum Computing – that calls for incr Read more…
September 8, 2022
The wheels are turning on the so-called CHIPS and Science Act, with a flurry of activity this week to turn the legislation into action. On Friday, U.S. President Joe Biden will be in Ohio alongside Intel CEO Pat Gelsinger to break ground on the chipmaker's new $20 billion manufacturing site, which will likely be partially... Read more…
August 3, 2022
After two-plus years of contentious debate, several different names, and final passage by the House (243-187) and Senate (64-33) last week, the Chips and Science Act will soon become law. Besides the $54.2 billion provided to boost US-based chip manufacturing, the act reshapes US science policy in meaningful ways. NSF’s proposed budget... 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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