October 11, 2022
The launch of ESnet6 was announced at an event at Berkeley Lab this morning. ESnet – short for “energy sciences network” – is managed by Berkeley Lab, f Read more…
July 22, 2022
John Towns, principal investigator of the Extreme Science and Engineering Discovery Environment (XSEDE), gave an overview of the soon-to-complete NSF-funded cyb Read more…
July 31, 2020
The header image was captured over a 24-hour period—across all time zones—by a U.S. National Aeronautics and Space Administration (NASA) satellite. It illus Read more…
September 19, 2017
The National Science Foundation has awarded a second phase, $10 million grant to the Chameleon cloud computing testbed project led by University of Chicago with Read more…
September 6, 2017
For about a year the Renaissance Computing Institute (RENCI) has been assembling best practices and open source components around data-driven scientific researc Read more…
July 25, 2017
Earlier this month, the National Science Foundation issued a $1 million grant to Larry Smarr, director of Calit2, and a group of his colleagues to create a comm Read more…
January 12, 2017
In cased you missed it, the National Science Foundation posted a “Dear Colleague Letter” (DCL) late last week seeking input on needs for the next generation Read more…
August 31, 2016
Jetstream, the expansive NSF-funded cyberinfrastructure project intended in large measure to serve the long tail of science will officially launch tomorrow (9/1 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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