MathWorks MATLAB with NVIDIA TensorRT integration

Wednesday, 04 April, 2018 | Supplied by: MathWorks Australia


MathWorks has announced that MATLAB now offers NVIDIA TensorRT integration through GPU Coder. This helps engineers and scientists develop AI and deep learning models in MATLAB with the performance and efficiency needed to meet the growing demands of data centres, as well as embedded and automotive applications.

MATLAB provides a complete workflow to rapidly train, validate and deploy deep learning models. Engineers can use GPU resources without additional programming so they can focus on their applications rather than performance tuning.

The integration of NVIDIA TensorRT with GPU Coder enables deep learning models developed in MATLAB to run on NVIDIA GPUs with high throughput and low latency. MathWorks’ internal benchmarks show that MATLAB-generated CUDA code combined with TensorRT can deploy Alexnet with 5x better performance than TensorFlow and can deploy VGG-16 with 1.25x better performance than TensorFlow for deep learning inference.

Online: au.mathworks.com
Phone: 02 8669 4700
Related Products

Yamaha YsUP software for SMT machinery

The YsUP software for SMT machinery enables PCH manufacturers to overcome the challenges of...

Siemens Process Preparation Stencil Engineering Tool

The Siemens Process Preparation Stencil Engineering Tool is designed to provide first-time-right...

Nordic Semiconductor nPM2100 Power Management IC

The nPM2100 PMIC features an efficient boost regulator and a range of energy-saving features to...


  • All content Copyright © 2025 Westwick-Farrow Pty Ltd