A Blog of the ZHAW Zurich University of Applied Sciences
For the past several months, we have been deep in the trenches with the ai8x-training tool and the training of various Convolutional Neural Network (CNN) architectures tailored explicitly for the MAX78000 and MAX78002 devices. Nevertheless, the ai8x training tool was more of a hindrance than a help. Among the myriad challenges we encountered, the inability to make […]
The Institute of Embedded Systems (InES) at ZHAW, with great experience in hardware and software development for NVIDIA Jetson computing modules, is presenting the successor of the NVIDIA Jetson AGX Xavier modular vision system based on the new high-performance NVIDIA Jetson Orin NX. As the Jetson AGX Xavier system, this new prototyping platform consists of […]
Using artificial intelligence algorithms, specifically neural networks on microcontrollers offers several possibilities but reveals challenges: limited memory, low computing power and no operating system. In addition, an efficient workflow to port neural networks algorithms to microcontrollers is required. Currently, several frameworks that can be used to port neural networks to microcontrollers are available. We evaluated […]
IntEdgPerf is a new benchmark for running machine learning algorithms on embedded devices. It was developed at the Institute of Embedded Systems (InES) at the Zürich University of Applied Sciences. IntEdgPerf is a framework that allows a fair comparison between different embedded processors that can be used for executing neural networks. The area of embedded […]
We have developed a simple software to show how a custom keras model can be automatically translated into c-code. The generated c-code can, in combination with the ARM-CMSIS-NN functions, be used to run neural-net calculations in an efficient way on an embedded micro-controller such as the CORTEX-M4. The example software on GitHub has also firmware which runs on the […]
The HDMI2CSI board for capturing 4K HDMI was ported to the latest release of L4T (28.2.1) including the bug fix in the Nvidia VI (see forum: [1], [2]). Major differences where adapted from L4T 28.1 to L4T 28.2.1 and our developed hardware is again able to capture 2160p30. Run the tc358840 outside its specification (>1Gbps) […]
Embedded devices like the Nvidia Tegra X1/2 offer tremendous video processing capabilities. But often there are bottlenecks hindering you from taking advantage of their full potential. One solution to this problem is to employ the general purpose compute capabilities of the GPU (GPGPU). For this purpose, we have developed a GStreamer Plug-In that lets you […]
The HDMI2CSI board for capturing 4K HDMI now supports both TX1 and TX2. Video capturing is fully supported for resolutions up to 2160p30 on Input A and 1080p60 on Input B. Driver development will continue on L4T 28.1. The previous 24.2.1 branch is considered deprecated. Get started with the Readme: https://github.com/InES-HPMM/linux-l4t-4.4 and find detailed instructions […]
Modern SoC devices offer high performance for data analysis and processing. In order to transfer accordingly high data rates, the choices for high speed general purpose interfaces are limited. The first that comes to mind is PCIe, which is available in most high performance SoCs. However, PCIe requires a relatively complex controller on both data […]
For our test driven way of development we build up a regression test system for our high performance video and audio transmission. The system is used to schedule and run tests and monitor the results in real time. For this, it provides a wide range of interfaces to interact with the system under test. This […]