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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…

2023 Winter Classic Finale – VIDEO RECAP

April 24, 2023

February 14th to April 15th – it’s been a long run for the 2023 Winter Classic Student Cluster Competition. 63 students from HBCU and HSI schools learned ha Read more…

Meet TempoQuest, a Startup Bringing Weather Code Into the Accelerated Era

April 18, 2023

Weather and climate applications are some of the most important for high-performance computing, often serving as raisons d'être and flagship workloads for the Read more…

2023 Winter Classic AWS GROMACS Results!

April 12, 2023

Hands off keyboards, the last computational challenge in the 2023 Winter Classic student cluster competition has been completed, the scores have been compiled, Read more…

Bloomberg Uses 1.3 Million Hours of GPU Time for Homegrown Large-Language Model

April 6, 2023

Financial firm Bloomberg is trying to prove that there are smarter ways to fine-tune artificial intelligence applications without the ethical or security concer Read more…

AWS, Partners Report Successful Quantum Key Distribution Trial in Singapore

March 6, 2023

While quantum computing makes its way haphazardly towards practical realty, quantum key distribution (QKD) is moving quickly towards greater commercial use. Tod Read more…

AWS Debuts Palace – Finite Element Analysis Suite Fine-Tuned for the Cloud

February 21, 2023

In an interesting twist on quantum-inspired work making its way into traditional HPC – and in this case a step further into cloud-based HPC – AWS today intr Read more…

Riken Plans ‘Virtual Fugaku’ on AWS

January 26, 2023

The development of a national flagship supercomputer aimed at exascale computing continues to be a heated competition, especially in the United States, the Euro 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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