May 10, 2023
A pattern is emerging on how U.S. government wants to boost its AI research. The approach is similar to how the early supercomputing infrastructures were built: Read more…
January 31, 2023
Last week the National AI Research Resource (NAIRR) Task Force released its final report and roadmap for building a national AI infrastructure to include comput 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…
September 26, 2022
Since 2017, plans for the Leadership-Class Computing Facility (LCCF) have been underway. Slated for full operation somewhere around 2026, the LCCF’s scope ext Read more…
September 15, 2022
Jetstream2, a collaborative cloud HPC system spread across five institutions, has entered full production following an early operations phase that began earlier Read more…
September 14, 2022
Well-heeled Google spinout SandboxAQ announced its first acquisition today – snapping up cybersecurity software specialist Cryptosense – while quantum netwo Read more…
August 18, 2022
Thanks to a grant from the National Science Foundation, Oklahoma State University (OSU) will be building a new supercomputer. The as-yet unnamed system will succeed OSU’s existing system, which is simply named “Pete.” “This is a big moment for OSU and the High Performance Computing Center (HPCC),” said Pratul Agarwal, assistant vice president of research cyberinfrastructure and... 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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