About two years ago, the Swiss National Supercomputing Centre (CSCS), HPE and Nvidia announced plans to launch a powerful new supercomputer in 2023 to replace Piz Daint, CSCS’ current flagship …
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’s a promotion, new company hire, o …
December 7, 2022
Hyperion Research delivered its latest outlook for the quantum computing market yesterday at the Q2B22 Conference, estimating revenues for 2022 will finish arou Read more…
November 14, 2022
MLCommons last week issued its third annual set of MLPerf HPC (v2.0) results intended to showcase the performance of larger systems when training more rigorous Read more…
November 10, 2022
MLCommons yesterday issued its latest round of MLPerf benchmarks – for Training, HPC, and Tiny. Releasing three sets of benchmarks at the same time makes pars Read more…
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…
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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