Quantization Workflow Prerequisites

This table lists the products required to quantize and deploy deep learning networks.

	Execution Environment
Development Host Requirements	FPGA	GPU
Setup Toolkit Environment	hdlsetuptoolpath (HDL Coder) The Calibrate workflow requires the MinGW C++ compiler or other compilers. For a list of supported compilers, see https://www.mathworks.com/support/requirements/supported-compilers.html Note The Calibrate workflow does not support the MinGW C compiler.	Setting Up the Prerequisite Products (GPU Coder)
Required Products	Deep Learning Toolbox™ Deep Learning HDL Toolbox™	Deep Learning Toolbox
Required Support Packages	Deep Learning Toolbox Model Quantization Library Deep Learning HDL Toolbox Support Package for Xilinx® FPGA and SoC Devices Deep Learning HDL Toolbox Support Package for Intel® FPGA and SoC Devices	Deep Learning Toolbox Model Quantization Library
Supported Networks and Layers	Supported Networks, Layers and Boards (Deep Learning HDL Toolbox)	Supported Networks and Layers (GPU Coder)
Deployment	Deep Learning HDL Toolbox	GPU Coder™
Additional Add Ons	MATLAB® Coder™ Interface for Deep Learning Libraries	GPU Coder Interface for Deep Learning Libraries CUDA® enabled NVIDIA® GPU with compute capability 6.1, 6.3 or higher.
Workflow Specific Requirements	When the Deep Network Quantizer Hardware Settings is set to Simulate In MATLAB the Quantize and Validate workflow requires the Image Processing Toolbox™.