May 18, 2023
The ASC23 cluster competition was held in a basketball stadium on the campus of the University of Science and Technology of China, located in Hefei, China – Read more…
May 17, 2023
The tenth edition of the Asian Supercomputing Challenge took place last week in Hefei, China, and it was tougher than ever. 24 university teams (20 on site, 4 Read more…
March 9, 2023
HPL. HPCG. Bookends. One will show you the best possible performance from your cluster while the other will show you the worst. Running and optimizing these t Read more…
December 2, 2022
The Frontier supercomputer – still fresh off its chart-topping 1.1 Linpack exaflops run and maintaining its number-one spot on the Top500 list – was still v Read more…
April 6, 2021
The wait is over. Today Intel officially launched its 10nm datacenter CPU, the third-generation Intel Xeon Scalable processor, codenamed Ice Lake. With up to 40 Read more…
November 17, 2019
A significant swath of the HPC community has come to Denver for SC19, which began today (Sunday) with a rich technical program. As is customary, the ribbon cutt Read more…
July 7, 2019
The biggest benchmark the student warriors tackled during the ISC19 Student Cluster Competition was the colossal HPC Challenge. This is a collection of benchmar Read more…
April 20, 2016
At 11:30 am local time on Wednesday in Wuhan, China, Zhejiang University was declared the winner of the High Performance LINPACK (HPL) benchmark portion of the 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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