The new S32Z and S32E automotive real-time processor families supercharge real-time vehicle compute and control applications. This article highlights how the complementary S32G vehicle network processor for service-oriented gateways, combined with the S32Z and S32E real-time processor can enable new automotive applications. Combining real-time compute with secure cloud connectivity supports advanced sensing, processing and control applications that can adapt with the life of your vehicle.
DDR tool supports i.MX8M family and LX2160A\LX2162A. DDR tool is part of Config tools for i.MX offering configuration, inspection, optimization, vTSA, stressing and code generation. It can be downloaded from
Vehicle electrical architectures are going through a transformation to achieve the consumers demand for driver assistance, electrification and service functions. To support modern software-defined vehicles and reduce the cost of the vehicle network, and the associated wiring harness, it is being transitioned to a domain and zonal architectures (or a combination of them). While this evolution helps address the software and cost challenges, it brings other challenges, such as how to partition safety critical real time control operations, like vehicle propulsion.
As automotive manufacturers are modernizing their vehicle networks, they are increasingly integrating related functions into a single ECU. Choosing a processor for these new ECUs is a critical task, which NXP makes easier with the new S32Z/E Real-Time Processor families
The disruptive technologies of multi-gigabit Automotive Ethernet, IEEE time-sensitive networking (TSN) protocols and automotive cloud-native DevOps are coming together to enable the Software-Defined Vehicle (SDV). NXP is at the leading edge of these technology trends and recently announced the S32Z and S32E real-time processors families.
This article lays out some of the progress on the disruptive technology front and explains how NXP plays a critical role with the launch of the S32 real-time processors by enabling the integration of vehicle-wide, real-time functions and supporting new vehicle architectures involving central compute, domain control and the zonal edge.
This launch introduces our Smart Card Trust Provisioning Solution, bringing customers a major new capability in protecting their Software Intellectual Property (IP) and guarding against over-production and cloning.
Hooking up to the external world usually means that our MCUs must learn to “speak” analog. A high-performance analog system was added to the LPC553x family to enable more integrated, lower external component count designs.
NXP's free UI design tool for the open source LVGL graphics library continues to add great new features and capabilities. GUI Guider 1.3.0 was released on January 24th 2022 and includes exciting new widgets, more host platform support, Keil project output and Micropython.
After setting my new 16” M1Max Macbook Pro, I found some surprising results for the kernel compile time. The Ubuntu Virtual Machine on my M1 MBP compiled the i.MX Linux kernel faster than an Intel i9 3650 Dell Precision workstation running native Ubuntu. Since the comparison is a bit like apple to oranges, I tried to minimize the variables, and, I also compared an older i7 Dell Precision M4700 and a Xeon.
NXP has now introduced MCU-Link Pro - the second incarnation of the MCU-Link debug probe architecture, adding several powerful capabilities and features to build on the entry level MCU-Link standalone model. This includes power/energy measurement, USB bridging and a J-Link firmware option.
NXP has released a new library, replacing LPCUSBSIO, to enable communication via USB bridges available on evaluation boards with LPC-Link2 and upcoming MCU-Link probes. User documentation and a Python wrapper are also available.
An interactive tutorial on how to create your own MATLAB Simulink temperature sensor application by applying the model-based design approach, how to configure and use the i.MXRT1060 EVK using NXP MCUXpresso, a thermistor module and the IMXRT Toolbox.
NXP's innovative MCUs, based on Arm® Cortex®-M cores and part of the EdgeVerse™ edge computing platform, continue to transform the industry landscape with increasing performance and integration, further complemented by outstanding enablement including MCUXpresso software and tools and an extensive ecosystem of partners. Get started now!
PyeIQ is written on top of eIQ™ ML Software Development Environment and provides a set of Python classes allowing the user to run Machine Learning applications in a simplified and efficiently way without spending time on cross-compilations, deployments or reading extensive guides.
Now PyeIQ 3.0.x release is announced. This release is based on i.MX Linux BSP 5.4.70_2.3.0 & 5.4.70_2.3.2(8QM, 8M Plus) and can also work on i.MX Linux BSP 5.10.9_1.0.0 & 5.10.35_2.0.0 & 5.10.52_2.1.0. And also, in latest PyeIQ 3.1.0 release, BSP 5.10.72_2.2.0 is also added into supported list.
This article is a simple guide for users. For further questions, please post a comment on eIQ Community or just below this article.
In my previous twoarticles, we examined the core components to an RT600 hardware design using the code name “Super-Monkey”. The objective of the Super-Monkey project to produce minimal configuration design example using RT685 audio crossover MCU that would support my real-time audio processing projects. There is quite a bit IO available on the RT685, but I chose to constrain my design to the most common functions for real-time audio. My applications generally use professional, “flagship quality” audio codecs for musical instrument signal processing. Using this as a guide, the process of coming up with a minimal IO complement was simplified. It is time to now time reveal the Super-Monkey design!