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
- Introducing OpenFL 1.6: Federated LLM Fine-Tuning and Evaluation
- Emotion-based AI Prompts to Improve Dementia and Alzheimer’s Care: Developer Spotlight
- Intel-Powered BuzzOnEarth Hackathon Spurs Climate Tech Innovations in India
- TurinTech AI: Driving Scalable and Sustainable AI with Intel
- Smart Waste Management: WasteAnt’s AI Solutions for Energy Generation
-
Neural networks news
Intel NN News
- Introducing OpenFL 1.6: Federated LLM Fine-Tuning and Evaluation
The most recent OpenFL release enables the next wave of federated learning development.
- Emotion-based AI Prompts to Improve Dementia and Alzheimer’s Care: Developer Spotlight
This article highlights how emotion-based AI prompting application can support people with dementia […]
- Intel-Powered BuzzOnEarth Hackathon Spurs Climate Tech Innovations in India
India’s largest climate hackathon BuzzOnEarth at IIT Kanpur, powered by Intel® AI technologies
- Introducing OpenFL 1.6: Federated LLM Fine-Tuning and Evaluation