Presentation
Optimizing Network Storage for AI-Powered EDA Deployments
DescriptionNearly all industries are striving to implement AI-powered solutions to significantly enhance performance across various workflows and functional groups. However, this shift brings a new, emerging issue. AI-driven EDA tools and workflows, while promising to enhance design processes, will substantially increase data volume and provisioning needs due to their dependence on large datasets for training and operation. These tools often magnify requirements by several orders of magnitude. Therefore, an effective method to optimize network storage is essential to manage the data explosion caused by AI-enabled EDA workflows.
In this proposal, we go over the challenges and demonstrate how a smart caching agent solution can provide maximum network storage optimization and the best performance when it comes to managing large datasets generated through such AI-powered EDA deployments.
In this proposal, we go over the challenges and demonstrate how a smart caching agent solution can provide maximum network storage optimization and the best performance when it comes to managing large datasets generated through such AI-powered EDA deployments.
Event Type
Engineering Poster
Networking
TimeMonday, June 235:00pm - 6:00pm PDT
LocationEngineering Posters, Level 2 Exhibit Hall