Technology Days - Training Material

cancel
Showing results for 
Show  only  | Search instead for 
Did you mean: 

Technology Days - Training Material

Training Sessions Material



Home

Home is where the heart is..

Home Control & Security; Development Software & Tools

Automotive

Automotive

Discussions

Sort by:
You need to get a lot of things right to build a truly secure system. Join this session to learn how the EdgeLock™ secure enclave that’s built into our i.MX 8ULP applications processors protects the entire system against attacks. Best of all, it simplifies complex implementations so you’re less likely to make errors when you configure security. With the secure enclave, you can achieve security goals with less security expertise, freeing you to focus on new ways to differentiate your application. Presenter: Lawrence Case, Systems Engineer and Security Architect, NXP
View full article
Learn how to use the LS1028A to quickly create industrial networks with TSN for deterministic, redundant communications.
View full article
See how to use and demonstrate the differentiating features of the newest Layerscape processor, the LS1028A. This live class will show how to enable the graphical capabilities of the LS1028A with the LSDK, and also how to take advantage of the integrated Ethernet switch and TSN features.
View full article
Edge computing puts cloud-computing software infrastructure on embedded-class processing platforms to reduce latency and uplink bandwidth consumption. Ranging from 1-core to 16-core devices, integrating important I/O features and integrating a hardware root of trust, the Layerscape family is ideal for edge-computing platforms. Complementary software like EdgeScale increases these platforms ease of use and accelerates customers' time to market. This session provides an overview of running Edge compute applications on Layerscape family of processors. It covers the concept of Edge computing and why it is needed, and goes on to elaborate the various use-cases where it can be used. It explains how customers can use the Layerscape SDK to run container based Edge compute applications, and leverage popular Edge Compute frameworks from AWS, Azure, Alibaba amongst others.
View full article
In this session you will learn how to use Machine Learning fundamentals using Layerscape family of processors. The class will cover: Machine Learning fundamentals; Networks used for training and different models; Sample Object recognition training and Inference use case; Ease of use to use with LS platform for Machine Learning.
View full article
You will learn on edge computing application, showing technical challenge to "manage" gateway and security, Layerscape microprocessors solutions including EdgeScale framework in cloud services context.
View full article
OpenIL is an open source software distribution for industrial and automation market.  OpenIL provides industrial-grade real time, security and network determinism. OpenIL is an ideal Linux distribution for PLC, HMI, industrial control and robotics. In this session, an overview of OpenIL is conducted including Xenomai, baremetal solution, TEE, TSN, Industrial network with OPCUA and EtherCAT and how they run on Layerscape.
View full article
Artificial intelligence and machine learning (AI/ML) are revolutionizing the industrial world. For maximal impact, AI/ML must be done close to where data is generated and the output of analysis used. It's an ideal workload for edge computing and complements NXP’s EdgeScale cloud-based device-management platform. Layerscape processors are well suited to hosting AI/ML workloads. Software from NXP and third parties helps enable developers to create industrial applications using AI/ML technology. These applications can be distributed, Layerscape-based edge nodes with endpoints performing multiple tasks including: addressing condition monitoring or first-level classification; running popular edge frameworks to deliver cloud-like services on premises, aggregating data from multiple endpoints or performing additional analysis; running cloud-based software analyzing data for long-term trends.
View full article
Machine learning can performed on a wide range of device categories - from MCUs with Arm® Cortex®-M4 and M7 cores to complex SoCs with high-end A-class cores, GPUs, DSPs, and dedicated machine learning accelerators. The first step is learning how to utilize proper training techniques for model development, but beyond that how to generate optimized inference engines that can be used to perform classifications, anomaly detection, predictions, and other types of decisions. This presentation highlights some basic training techniques, such as data augmentation, but the primary focus will be on various ways to deploy neural network frameworks and classical machine learning algorithms, and most importantly, utilizing a variety of open source tools and techniques. We will show how these techniques fit in with some real use cases such as object recognition and anomaly detection.
View full article