Bookmark and Share

"New Memory-centric Architecture Needed for AI," a Presentation from Crossbar

Register or sign in to access the Embedded Vision Academy's free technical training content.

The training materials provided by the Embedded Vision Academy are offered free of charge to everyone. All we ask in return is that you register, and tell us a little about yourself so that we can understand a bit about our audience. As detailed in our Privacy Policy, we will not share your registration information, nor contact you, except with your consent.

Registration is free and takes less than one minute. Click here to register, and get full access to the Embedded Vision Academy's unique technical training content.

If you've already registered, click here to sign in.

See a sample of this page's content below:

Sylvain Dubois, Vice President of Strategic Marketing & Business Development at Crossbar, presents the "New Memory-centric Architecture Needed for AI" tutorial at the May 2018 Embedded Vision Summit.

Artificial intelligence (AI) will not replace the need for humans any time soon, but it will have a profound impact on everyday lives, transforming industries from transportation to education, medical to entertainment. AI is about data computing, and the more data, the smarter the AI algorithms will be. However, the current bottleneck between data storage and computing cores is limiting the innovation of future AI applications.

In this presentation, Dubois discusses how non-volatile memory technologies, such as ReRAM, can be directly integrated on-chip with processing logic enabling brand new memory-centric computing architectures. The superior characteristics of ReRAM over legacy non-volatile memory technologies are helping to address the performance and energy challenges required by AI algorithms. High performance computing applications, such as AI, require high-bandwidth low latency data accesses across processors, storage and IOs. ReRAM memory technologies provide significant improvements by reducing the performance gap between storage and computing.