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At ISC, Sustainable Computing Leaders Discuss HPC’s Energy Crossroads
In the wake of SC22 last year, HPCwire wrote that “the conference’s eyes had shifted to carbon emissions and energy intensity” rather than the historical emphasis on flops-per-watt and powe …
Closing ISC Keynote by Sterling and Suarez Looks Backward and Forward
ISC’s closing keynote this year was given jointly by a pair of distinguished HPC leaders, Thomas Sterling of Indiana University and Estela Suarez of Jülich Supercomputing Centre (JSC). Ostensi …
ISC Keynote: To Reinvent HPC After Moore’s Law, Follow the Money
May 23, 2023
This year’s International Supercomputing Conference (ISC) kicked off yesterday in Hamburg, Germany, with a keynote from Dan Reed, presidential professor at th Read more…
Turing Award Winner Jack Dongarra Reflects on Career Ahead of ISC
May 19, 2023
The selection of Jack Dongarra as the recipient of the 2021 Turing Award was a well-deserved recognition of his invaluable contributions to the field of high pe Read more…
Q&A with ORNL’s Travis Humble, an HPCwire Person to Watch in 2023
May 12, 2023
Travis Humble is the director the Quantum Science Center (QSC) at Oak Ridge National Laboratory. QSC is one of six National QIS Research established by the U.S. National Quantum Initiative Act (NQIA) in 2018 and being overseen by the Department of Energy. Hopes are high that these centers, through their own research and in collaboration... Read more…
Microsoft and ETH Take Aim at Quantum Computing’s Hype (and Promise)
May 2, 2023
A fascinating ACM paper by researchers Torsten Hoefler (ETH Zurich), Thomas Häner (Microsoft*) and Matthias Troyer (Microsoft) – "Disentangling Hype from Pra Read more…
Education Costs, Lack of Engineering Interest Hurting Semiconductor Industry
May 2, 2023
The semiconductor industry could be worth $1 trillion by 2030, growing from $600 billion today – and there will be an acute shortage of talent to fill jobs as the sector grows. Read more…
HPC Career Notes: May 2023 Edition
May 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…
EuroHPC Executive Director Talks Europe’s Supercomputing Future
May 1, 2023
Following the EuroHPC Summit conference in Gothenburg, Sweden, last month, HPCwire asked Steve Conway, senior analyst at Intersect360 Research, to interview And Read more…
Q&A with HPE’s Trish Damkroger, an HPCwire Person to Watch in 2023
April 29, 2023
HPCwire 2023 Person to Watch Trish Damkroger is a long-time HPC enthusiast and seasoned exec hailing from a 17 year tenure at Lawrence Livermore Lab, followed by five years of leading HPC strategy at Intel, before one year ago making the move to HPE (where she is Chief Product Officer and Senior Vice President, HPC, AI & Labs). Read more…
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Whitepaper
Powering Up Automotive Simulation: Why Migrating to the Cloud is a Game Changer
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.
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Whitepaper
How to Save 80% with TotalCAE Managed On-prem Clusters and Cloud
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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Whitepaper: Streamlining AI Data Management
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Whitepaper: Reducing Bias and Increasing Accuracy in AI Models
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Whitepaper: A New Standard in CAE Solutions for Manufacturing
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Whitepaper: Porting CUDA Applications to Run on AMD GPUs
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Whitepaper: QCT HPC BeeGFS Storage: A Performance Environment for I/O Intensive Workloads
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Webcasts and webinars: Leveraging Exascale Era Technology for Advanced Computer-Aided Engineering
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