What is Neural network processor designed for edge devices?
Neural network processor designed for edge devices is a Edge AI Accelerator IP core from Kneron listed on Semi IP Hub.
Vendor:
Kneron
Category:
Edge AI Accelerator
Neural network processor designed for edge devices
Kneron NPU IP Series are neural network processors that have been designed for edge devices.
Overview
Kneron NPU IP Series are neural network processors that have been designed for edge devices. These processors provide high computing performance with low power consumption and are small in size. Kneron NPU IP Series can be applied to smart homes, smart surveillance, smartphones, and wearable devices that have high requirement for low power and space. The entire product consumes under 0.5W and can even drop below 5mW for specific applications.
Key features
- High energy efficiency
- All series reach higher than 1.5 TOPS/W.
- Support mainstream deep learning frameworks
- Caffe, Keras, TensorFlow, and ONNX.
- Low power consumption
- Under 0.5W and can be less than 5 mW for specific applications.
- An integrated AI solution
- Include hardware IP, compiler, and model compression.
- Deep compression technology
- Compresses not only models but also data and coefficients during computing to reduce memory use.
- Filter decomposition and convolution acceleration
- Divides a large-scale convolutional block into a number of smaller ones for parallel computing and then integrates and accelerates the results.
- CNN model support optimization
- Supports diverse CNN models, including Vgg16, Resnet, GoogleNet, YOLO, Tiny YOLO, Lenet, MobileNet, and Densenet with model specific performance optimization.
- Interleaving computation architecture
- Enable parallel convolution computing and pooling to improve overall performance. The convolution layer can support both 8- and 16-bits fixed points concurrently.
- Adaptive data structure
- Adjusts the data structure dynamically to improve MAC efficiency depending on changing demand.
- Dynamic storage resource configuration
- Allows more efficient resource allocation between shared memory and operational memory. Increases storage resource utilization without affecting performance.
Specifications
Identity
Part Number
Kneron NPU IP
Vendor
Kneron
Type
Silicon IP
Files
Note: some files may require an NDA depending on provider policy.
Provider
HQ:
USA
Frequently asked questions about Edge AI Accelerator IP cores
How should engineers evaluate this Edge AI Accelerator?
Engineers should review the overview, key features, supported foundries and nodes, maturity, deliverables, and provider information before shortlisting this Edge AI Accelerator IP.
Can this semiconductor IP be compared with similar products?
Yes. Buyers can compare this product with similar semiconductor IP cores or IP families based on category, provider, process options, and structured technical specifications.