Vendor: BrainChip Inc. Category: Edge AI Accelerator

Neuromorphic Processor IP (Second Generation)

Akida is a neural processor platform inspired by the cognitive ability and efficiency of the human brain.

Overview

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.

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

Block Diagram

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

What’s Included?

  • 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.

Specifications

Identity

Part Number
Akida 2
Vendor
BrainChip Inc.
Type
Silicon IP

Files

Note: some files may require an NDA depending on provider policy.

Provider

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Frequently asked questions about Edge AI Accelerator IP cores

What is Neuromorphic Processor IP (Second Generation)?

Neuromorphic Processor IP (Second Generation) is a Edge AI Accelerator IP core from BrainChip Inc. listed on Semi IP Hub.

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.

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