January 21, 2021
Earlier this week (Jan. 19), HiPEAC — the European Network on High Performance and Embedded Architecture and Compilation — published the 8th edition of the HiPEAC Vision, detailing an increasingly interconnected computing landscape where complex tasks are carried out across multiple... Read more…
August 25, 2020
Larry Smarr may have stepped back from full-time work in the Computer Science and Engineering Department at the University of California, San Diego, but that do Read more…
March 16, 2020
For gamers, fighting against a global crisis is usually pure fantasy – but now, it’s looking more like a reality. As supercomputers around the world spin up Read more…
December 2, 2014
The ability to predict regional sea level changes over the next few decades takes on greater urgency as global carbon emissions continue to rise. The situation Read more…
August 18, 2014
Distributed computing has undergone many permutations, from its roots in grid computing to support large scientific endeavors to Sun-style utility computing, to Read more…
March 14, 2013
QMachine leverages the processing power of Web browsers to create a commodity supercomputer. Read more…
March 14, 2013
QMachine leverages the processing power of Web browsers to create a commodity supercomputer. Read more…
March 13, 2013
Quantum Cures wants your help identifying drug candidates for orphan and rare diseases. 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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