MathWorks MATLAB with NVIDIA TensorRT integration
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.
Phone: 02 8669 4700
STMicroelectronics STDRIVE102 gate-driver ICs
The STDRIVE102P and STDRIVE102BP gate-driver integrated circuits feature an SPI interface to...
Spectrum Control EMI-filtered MIL-DTL-38999 connectors
The custom EMI-filtered MIL-DTL-38999 connectors are designed for a range of military, aerospace...
Toshiba TB9M030FG SmartMCD motor control devices
The TB9M030FG Smart MCD motor control devices feature a sensorless control gate driver IC for...

