Near Memory Compute is becoming important for future AI processing systems that need improvement in system performance and energy-efficiency. The Von Neumann computing model requires data to commute from memory to compute and this data movement burns energy. Is it time for NMC to solve this data movement bottleneck? This blog addresses this question and is inspired by Intel Fellow, Dr. Frank Hady’s recent presentation at the International Solid State Circuits Conference (ISSCC), titled “We have rethought our commute; Can we rethink our data’s commute?”
-
Articles récents
- Beewant’s Multimodal AI: Smarter Solutions for Training, Travel, and Safety
- Get Your Innovation to Go with Innovation Select Videos
- Building AI for Low-Resource Languages: Bezoku’s Innovative Approach
- Accelerate PyTorch* Inference with torch.compile on Windows* CPU
- DubHacks’24 Hackathon Where Developers Innovatively Utilized Intel® Tiber™ AI Cloud and AI PCs
-
Neural networks news
Intel NN News
- Beewant’s Multimodal AI: Smarter Solutions for Training, Travel, and Safety
Beewant’s cutting-edge multimodal AI redefines multimedia, driving innovative applications across […]
- Get Your Innovation to Go with Innovation Select Videos
Catch up on the latest Intel Innovation developer and technical content with demos, tech talks and […]
- Building AI for Low-Resource Languages: Bezoku's Innovative Approach
Bezoku, a member of the Intel® Liftoff program, is addressing the challenges of low-resource […]
- Beewant’s Multimodal AI: Smarter Solutions for Training, Travel, and Safety