program代做、代写Python设计程序

日期：2024-03-27 09:04

Machine Learning Intelligent Chip Design

Homework1 Implementation of AlexNet in SystemC

Description

In this task, you are required to implement the AlexNet convolutional neural network

architecture using SystemC. AlexNet is a seminal deep learning model that achieved

significant breakthroughs in image classification tasks. The network consists of multiple

layers, including convolutional layers, max-pooling layers, and fully connected layers.

Implementation Details

Network Architecture:

You are provided with the network architecture details, including the number of layers,

the size of input and output feature maps, filter sizes, and strides.

Input Data:

Input data for the network will be provided to you. Each input image will have the

appropriate dimensions compatible with the network's input layer.

Weights and Biases:

The weights and biases for each layer of the network will be provided. These parameters

are essential for the convolutional and fully connected layers' computations.

Simulation:

Once you have implemented the network in SystemC and integrated the input data,

weights, and biases, you should simulate the network to obtain the predicted output. This

will involve passing the input data through the network layers, applying convolutional

operations, activation functions, and pooling, followed by fully connected layers, until you

get the final output.

Alexnet Training Model

2

The Pre-trained AlexNet Model Information

Provided Data Description

Values in the pre-train model in Pytorch are floating points with 16 digits after the decimal.

We export these values as txt file for you. Values in these txt files are floating point but

rounded to the sixth decimal place.

Model layer parameters

imagenet_classes.txt

https://gist.github.com/ageitgey/4e1342c10a71981d0b491e1b8227328b

Input Data

dog.txt cat.txt

3

Reference Result

Simulation results of AlexNet executed in Python

Dog

Cat

Simulation results of AlexNet executed in SystemC

Dog

Cat

Implement Notes

The purpose of this assignment is just to make students familiar with SystemC, so as long as

the execution results are correct, we will not restrict how students implement it.

Here are some tips for your reference:

You can use one SC_MODULE to implement the entire module, or implement each layer

with different SC_MODULE.

You can use sc_signal to connect different modules.

We strongly recommend building a monitor module to receive output and print out the

execution results.

4

Submission Guidelines

Please compress a folder named HW<ID>_<studend-ID> into a zip file with the

same name and upload it to E3.

The folder should include:

o Report (Name: HW<ID>_<student ID>.pdf)

o Codes

o Makefile

Example:

You don’t need to upload parameters.

Ensure that your code is well-commented and organized for clarity and

understanding.

Plagiarism is forbidden, otherwise you will get 0 point!!!

Deliverables

SystemC Implementation:

Complete implementation of AlexNet architecture using SystemC.

Report:

A brief report containing

o Simulation results demonstrate the predicted output for the provided input data.

o Your implementation approach, challenges faced, and any observations or insights

gained during the implementation and simulation process.