Apple inc. (20240265233). SCALABLE NEURAL NETWORK PROCESSING ENGINE simplified abstract
Contents
SCALABLE NEURAL NETWORK PROCESSING ENGINE
Organization Name
Inventor(s)
Erik Norden of San Jose CA (US)
Sung Hee Park of Cupertino CA (US)
Jaewon Shin of Los Altos CA (US)
Christopher L. Mills of Saratoga CA (US)
Seungjin Lee of Los Gatos CA (US)
Fernando A. Mujica of Los Altos CA (US)
SCALABLE NEURAL NETWORK PROCESSING ENGINE - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240265233 titled 'SCALABLE NEURAL NETWORK PROCESSING ENGINE
Simplified Explanation: The patent application describes a neural processor circuit with a scalable architecture for instantiating neural networks. The circuit includes a data buffer, memory external to the circuit, and multiple neural engine circuits that generate output data using input data and kernel coefficients.
- The neural processor circuit has a scalable architecture for instantiating one or more neural networks.
- It includes a data buffer coupled to external memory and multiple neural engine circuits.
- Each neural engine circuit generates output data using input data and kernel coefficients.
- The circuits can be selectively activated or deactivated based on configuration data of the tasks.
- An electronic device may include multiple neural processor circuits that execute tasks by activating or deactivating the circuits.
Potential Applications: 1. Artificial intelligence systems 2. Machine learning applications 3. Neural network training and inference tasks
Problems Solved: 1. Scalability in instantiating neural networks 2. Efficient execution of tasks using neural engine circuits 3. Flexibility in activating or deactivating circuits based on task requirements
Benefits: 1. Improved performance in neural network tasks 2. Enhanced flexibility and scalability in neural network implementations 3. Efficient utilization of resources in executing tasks
Commercial Applications: Neural processor circuits with scalable architectures can be utilized in various industries such as: 1. Robotics 2. Autonomous vehicles 3. Healthcare diagnostics
Prior Art: Prior research in neural processor circuits and scalable architectures for neural networks can be found in academic journals and patent databases.
Frequently Updated Research: Stay updated on the latest advancements in neural processor circuits and neural network architectures through academic publications and industry conferences.
Questions about Neural Processor Circuits: 1. How do neural engine circuits contribute to the performance of neural networks? 2. What are the key factors to consider when designing a scalable architecture for neural processor circuits?
Original Abstract Submitted
embodiments relate to a neural processor circuit with scalable architecture for instantiating one or more neural networks. the neural processor circuit includes a data buffer coupled to a memory external to the neural processor circuit, and a plurality of neural engine circuits. to execute tasks that instantiate the neural networks, each neural engine circuit generates output data using input data and kernel coefficients. a neural processor circuit may include multiple neural engine circuits that are selectively activated or deactivated according to configuration data of the tasks. furthermore, an electronic device may include multiple neural processor circuits that are selectively activated or deactivated to execute the tasks.
