Optical I/O Technology Needed for Zettascale, Say Top Chipmakers

March 16, 2023

Optical I/O is being singled out by top companies to push computing beyond exascale and into zettascale. The technology was singled out in a recent speech by AM Read more…

Light-enabled Microprocessor Holds Promise for Faster Computers

February 23, 2016

Combining electronics and photonics on semiconductor microchips to speed data transmission isn’t a new idea – the potential for better performance and power Read more…

  • arrow
  • Click Here for More Headlines
  • arrow

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.

Two recent studies show how Ansys Gateway powered by AWS can balance run times and costs, making it a compelling solution for automotive development.

Download Now

Sponsored by ANSYS

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.

Download Now

Sponsored by TotalCAE

Advanced Scale Career Development & Workforce Enhancement Center

Featured Advanced Scale Jobs:

SUBSCRIBE for monthly job listings and articles on HPC careers.

HPCwire Resource Library

HPCwire Product Showcase

Subscribe to the Monthly
Technology Product Showcase:

HPCwire