- 文件说明
- model/:模型参数预处理
- paras.json:模型各层类型,参数。
- vgg16_main.cu:模型主函数,负责读取数据,初始化,调用推理函数,对比正确性
- model.hpp:模型定义,初始化,推理
- layers.cuh:定义具体层(kernel function)操作
- utils.h:一些帮助函数
- json.hpp:c++ 读取json库, 原仓库链接
- Makefile:
- make: 编译
- make clean: 清除输出文件
- 代码架构:
- 通过传如传入模型参数以及权重参文件路径,构造VGG16类,初始化模型。
- 调用类函数VGG16::inference(float*,float*)进行推理,传出输出。
- 优化:
- 并行方式:
- 卷积层: 并行粒度为每个thread计算每张特征图上的一个点,每个block计算一张特征图
- 池化层: 并行粒度为每个thread计算每张输出特征图上的一个点
- ,每个block计算输出的一个二维矩阵
- 全连接层: 并行粒度为每个thread计算每张输出矩阵上的一个点
- 共享内存:
- 在卷积中,每个卷积核对应一张特征图,并且被一个block计算,所以说可以先将卷积核加载到共享内存中,然后在每个block中thread对其进行取用。
- 寄存器优化:
- 在每个函数当中使用寄存器加快访问速度
- 集成relu到各个层当中
- 减小线程数量: 在每个线程进行多个计算,减小overhead。
- 并行方式:
- 步骤
- 模型解析,
- 模型读取
- 模型编写-cuda
- 测试正确性
- 优化
- 在服务器上执行:
$ cd /home/group3/workspace/VGG $ make $ ./model.o
- 代码效果:
vgg16-cuda's Introduction
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