Deep Learning HDL Toolbox

Deep Learning HDL Toolbox

原型并在FPGA和SOC上部署深度学习网络

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Deep Learning Inference on FPGAs

原型并在FPGA进行边缘部署的深度学习网络。

可编程深度学习处理器

工具箱包括深度学习处理器,该处理器具有通过调度逻辑控制的通用卷积和完全连接的图层。这种深度学习处理器执行使用的基于FPGA的推理使用Deep Learning Toolbox™. High-bandwidth memory interfaces speed memory transfers of layer and weight data.

深度学习处理器包含被编程为执行指定网络的通用卷积和完全连接的处理模块。

Deep learning processor architecture.

Compilation and Deployment

将您的深度学习网络编译为由深度学习处理器运行的一组指令。在捕获实际的设备上性能指标时部署到FPGA并运行预测。

Compile your deep learning network into a set of instructions to be deployed to the deep learning processor.

编译和部署YOLO V2网络。

基于FPGA的Matlab推断

Run deep learning inferencing on FPGAs from MATLAB.

创建部署网络

首先使用深度学习工具箱来设计,列车和分析您的深度学习网络,以获取对象检测或分类等任务。您还可以通过从其他框架导入培训的网络或图层来开始。

将您的网络部署到FPGA

Once you have a trained network, use the部署命令用深度学习处理器与以太网或JTAG接口进行编程FPGA。然后用来编译命令为培训的网络生成一组指令,而不重新编程FPGA。

使用MATLAB配置电路板和接口,编译网络,并部署到FPGA。

使用MATLAB配置电路板和接口,编译网络,并部署到FPGA。

Running FPGA-Based Inferencing as Part of Your MATLAB Application

在matlab中运行整个应用程序®,包括您的测试台,预处理和后处理算法,以及基于FPGA的深度学习推理。单个matlab命令,predict, performs the inferencing on the FPGA and returns results to the MATLAB workspace.

MATLAB循环捕获图像,通过调整亚历纳网的大小来预处理它,在FPGA上运行深度学习推理,然后在处理后并显示结果。

运行在FPGA上执行深度学习推理的MATLAB应用程序。

Network Customization

Tune your deep learning network to meet application-specific requirements on your target FPGA or SoC device.

Profile FPGA Inferencing

根据您在FPGA上运行预测以找到性能瓶颈,测量层级延迟。

深度学习推论分析指标。

从MATLAB的FPGA进行深入学习网络推断。

调整网络设计

Using the profile metrics, tune your network configuration with Deep Learning Toolbox. For example, use Deep Network Designer to add layers, remove layers, or create new connections.

Deep Learning Quantization

Reduce resource utilization by quantizing your deep learning network to a fixed-point representation. Analyze tradeoffs between accuracy and resource utilization using the Model Quantization Library support package.

Deploying Custom RTL Implementations

Deploy custom RTL implementations of the deep learning processor to any FPGA, ASIC, or SoC device with HDL Coder.

Custom Deep Learning Processor Configuration

Specify hardware architecture options for implementing the deep learning processor, such as the number of parallel threads or maximum layer size.

生成可合成的RTL.

使用HDL编码器从深度学习处理器生成可合成的RTL,以用于各种实现工作流程和设备。重用相同的深度学习处理器进行原型和生产部署。

The dlhdl.BuildProcessor class generates synthesizable RTL from the custom deep learning processor.

从深度学习处理器生成可合成的RTL。

为集成生成IP核心

When HDL Coder generates RTL from the deep learning processor, it also generates an IP core with standard AXI interfaces for integration into your SoC reference design.

HDL Coder generates an IP core that maps deep learning processor inputs and outputs to AXI interfaces.

目标平台接口表显示I / O和AXI接口之间的映射。