Akida is a neural processor platform inspired by the cognitive ability and efficiency of the human brain. The second-generation platform can independently perform complex inferencing and learning on extremely low-power AI devices, thus delivering highly accurate, intelligent, responsive, real-time applications with greater reliability and security. A scalable, self-contained co-processor for advanced neural networks. Extends support for advanced networks with spatio-temporal properties.
Neuromorphic Processor IP (Second Generation)
Overview
Key Features
Self-contained neural processor
- Scalable fabric of 1-128 nodes
- Each neural node supports 128 MACs
- 8,4,1, bit arithmetic precision
- Programmable activation functions
- Skip connections
- Configurable 50-130K embedded local SRAM
- DMA for all memory and model operations
- Multi-layer execution without host CPU
- AXI bus interface
Efficient algorithmic hybrid mesh
- Performs as Temporal Neural Processor (TNP), spatial Convolutional Neural Processor (CNP) and Fully-connected Neural Processor (FNP)
- Integrates CNNs, Spatio-Temporal, TENNs Buffer networks
Akida efficiently accelerates…
- Image and audio classification
- Object detection
- Scene segmentation
- Gesture and face recognition
- State-of-the-art algorithms in sequence prediction
- Video object detection
- Human action recognition
- Raw-audio classification
- Vital signs prediction
Notable features:
- Supports 8-,4-,and1-bit weights and activations
- Supports multiple layers simultaneously
- Supports long-range skip connections in hardware
Software development and deployment:
- Akida leverages standard frameworks and development platforms such as TensorFlow/Keras, Pytorch/ONNX and Edge Impulse
- Akida is model-, network-, and OS-agnostic
- BrainChip MetaTF supports model development and optimization for Akida hardware
- Akida model zoo offers a set of pre-built Akida-compatible models, pre-trained weights and training scripts
- Akida TENNs models are offered for evaluation
Benefits
- Accelerates today’s networks: CNNs, DNNs and more, directly in hardware with minimal CPU intervention
- Event-based processing: Computes only when necessary; substantially reduces number of operations executed and energy consumed
- At-memory compute: Significantly reduces memory movement; uses cost effective, scalable, standard RAMs
- Exceptional spatio-temporal capability: Patented Temporal Event-based Neural Nets (TENNs) revolutionize time-series data applications
- Event-based communication: Sends data between NPUs through integrated mesh without any CPU intervention; offloads system
- Intelligent runtime: Runtime manages all operation of neural processor, transparent to the user, accessible through a simple API
Block Diagram

Deliverables
- Fully synthesizable RTL.
- IP deliverables package with standard EDA tools.
- Complete test bench with simulation results.
- RTL synthesis scripts and timing constraints. Customized IP packaged targeted for your application.
- Run time software C++ library.
- Processor and OS agnostic.
Technical Specifications
Short description
Neuromorphic Processor IP (Second Generation)
Vendor
Vendor Name
Availability
now