By using Deep Learning HDL Toolbox, engineers can customize the hardware implementation of their deep learning network and generate portable, synthesizable Verilog and VHDL code for deployment on any ...

The Deep Learning HDL Toolbox provides algorithm developers and hardware designers with functions and tools to prototype and implement deep learning networks on FPGAs and SoCs. It provides prebuilt ...

This workflow is already being used by the NXP Vision Toolbox to deploy deep learning networks on the Arm Cortex-A53 processor included in the NXPS32V234. Going further If you’re interested in finding ...

Leveraging the capabilities of HDL Coder ™, this innovative toolbox empowers users to customize, build, and deploy an efficient, high-performance Deep Learning Processor IP Core.

MathWorks has introduced Release 2018b of MATLAB and Simulink which contains significant enhancements for deep learning, along with new capabilities and bug fixes across the product families.

“Deep Learning with MATLAB” course is now available through NVIDIA’s Deep Learning Institute.

The Deep Learning Toolbox, part of MathWorks’ MATLAB 2018b release, targets the creation of machine-learning applications.

With the Simulink HDL Coder, the MathWorks hopes to have in place the "missing link" that bridges the yawning gap between those high-level Matlab models and synthesizable RTL (see the figure).