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Roadmap for Building a US National AI Research Resource Released
Last week the National AI Research Resource (NAIRR) Task Force released its final report and roadmap for building a national AI infrastructure to include computational resources, high-quality dat …
Researchers Present Vision for HPC Fusion Data Gateway
Fusion energy is having a moment – an increasingly fruitful one – but as radio astronomers and particle physicists know, bigger and better experiments and simulations mean data deluges that q …
Jack Dongarra: A Not So Simple Matter of Software
November 16, 2022
For a few moments, the atmosphere was more Rock Concert than Supercomputing Conference with many members of a packed audience standing, cheering, and waving signs as Jack Dongarra took the stage to deliver the annual ACM Turing Award lecture at SC22. Read more…
Hyperion Paints a Positive Picture of the HPC Market
November 8, 2022
Return to normalcy is too strong, but the latest portrait of the HPC market presented by Hyperion Research yesterday is a positive one. Total 2022 HPC revenue ( Read more…
CEO Jack Hidary on SandboxAQ’s Ambitions and Near-term Milestones
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…
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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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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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