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Overview

Description

DRP-AI for RZ/V2H supports a feature for efficiently calculating the pruned AI model. The DRP-AI Extension Pack provides a pruning function optimized for RZ/V2H. The DRP-AI optimized pruning function can be used in combination with this tool and PyTorch or TensorFlow training code.

What is pruning?

Nodes in a neural network are interconnected as shown in the figure. Methods of reducing the number of parameters by removing weights between nodes or removing nodes are referred to as “pruning”. A neural network to which pruning has not been applied is generally referred to as a dense neural network. And a neural network to which pruning has been applied is generally referred to as a sparse neural network. Applying pruning leads to a slight deterioration in the accuracy of the model but can reduce the power required by hardware and accelerate the inference process.

Image
Dense neural network; after pruning: sparse neural network

How to embed the pruned model

The pruned model can be embedded using DRP-AI TVM. Refer to the DRP-AI TVM page on GitHub for details on TVM.
https://github.com/renesas-rz/rzv_drp-ai_tvm

Note: As shown in the figure, pruning is an optional function. (Dense model also can be embedded.)

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DRP-AI Development Environment

Features

  • Pruning functions optimized for RZ/V2H
  • Pruning ratio can be specified for balance between accuracy and power efficiency
  • Supports 2 pruning modes for improving accuracy (One Shot/Gradual)

Release Information

DRP-AI Extension Pack Version 1.1.0 is available. (Oct. 2024)

  • Supported PyTorch models with a multi-head attention structure for a transformer neural network.

Target Devices

Downloads

Type Title Date
Software & Tools - Software Log in to Download GZ 3.61 MB
1 item

Documentation

Type Title Date
Manual - Software PDF 1.61 MB
Application Note PDF 440 KB
2 items

Design & Development

Related Boards & Kits

Videos & Training

Overview of DRP-AI TVM

This video provides an overview of DRP-AI TVM, focusing on the integration of AI into "Endpoint" devices for efficient real-time processing. Renesas' DRP-AI acts as a powerful accelerator, offering key features that enhance the performance and capabilities of endpoint AI applications.