CodeWarrior for LA1224 plugin Hello,  I am currently In the middle of evaluating LA1224-RDB and I have some questions regarding the software environment. As I understand I can have a Linux app running on the existing NxP image on LX2160A for evaluation purposes. Furthermore I suppose LA1224 is running baremetal with freertos. I saw that I can have firmware for LA1224 in a Linux directory on the LX2160A. Is this given from NxP? What does it support? I suppose that if I want to develop something further than the given firmware I have to get a codewarrior license and TAP. I have downloaded CW_ARMv8_v2020.06_b200629GA_Win_Setup.exe however the LP1224 is not available. After searching the NxP site I read that I need an extra toolchain on top of CW_ARMv8. What is the full url to download the add on?  I read CodeWarrior for LA1224 and only a partial url is given "com.freescale.armv8.11.5.15.E200.INT.Win.updatesite.230810 1.zip" Any further information on how to work on those processors is welcome. Kind Regards N. Alexopoulos Re: CodeWarrior for LA1224 plugin Please download pack com.freescale.armv8.11.5.15.E200.INT.Win.updatesite.230810 1.zip from the following link. https://support.nxp.com/s/case/500Te00000eF7lOIAS/community-codewarrior-for-la1224-plugin?language=en_US Please prepare a clean installation environment. Please install CW_ARMv8_v2020.06_b200629GA_Win_Offline.exe first. Then open CodeWarrior IDE in a new worksapce path. Then install the service pack com.freescale.armv8.11.5.15.E200.INT.Win.updatesite.230810 1.zip from Help->Install New Software->Add->Archive in CodeWarrior IDE.

Fallback mechanism for failed AB_SWAP update Hello, We are developing an application that uses the AB_SWAP mechanism of the HSE firmware on the S32K342 to perform OTA updates. We are currently activating the passive block once the passive region of the flash is entirely written to. We were wondering whether there is a fallback mechanism that we can use to verify/check whether the image we are booting from is corrupted, and if we can fallback to the 'known good' active region that has become the passive region after resetting. This arises from the fact that on some occasions, we overwrite the passive region without issuing a reset and midway through we reset the processor, resulting in a corrupted image in the flash.  Re: Fallback mechanism for failed AB_SWAP update Hey @lukaszadrapa , Thanks for the clarification. We are still trying to understand which type of secure boot strategy to use in our application. Advance Secure boot seems a bit complicated with having to install the SMR and CR. On the other hand, Basic Secure boot seems slightly easier to install but the exact implementation and installation details seem unclear. I was wondering if you could provide some insight into these options. I am referring to the HSE B Reference Manual and was also wondering if there is any additional documentation I should be referring to for this. Regards, Shiv Re: Fallback mechanism for failed AB_SWAP update Hi @Shiv_peak  I answered very similar question a couple of days ago, please take a look at: https://community.nxp.com/t5/S32K/S32K-OTA-Rollback/m-p/2400332/highlight/true#M60125 If you need more details, just let me know. Regards, Lukas Re: Fallback mechanism for failed AB_SWAP update Can you also elaborate on what you mean by 'device goes in recovery mode' if the basic secure boot fails? Does this mean that the core will not be released from reset and there is no fallback or recovery in this case? I ask because we want to have the functionality where if the secure boot fails, we boot another image, possibly in the passive bank. Re: Fallback mechanism for failed AB_SWAP update We provide this application note: https://www.nxp.com/webapp/Download?colCode=AN13465   It’s updated version of Secure Boot application note v0.1.1.0 (AN744511) released in 2021 which can be downloaded from: https://www.nxp.com/products/S32K3 Application note can be found here: Documentation -> Secure Files -> Secure Boot Application note v0.1.1.0 (AN744511) Associated demo project can be downloaded here: Design Resources -> Software -> Secure Files -> SecureBootAppNoteDemo (SW745310) The software was not updated, so use mentioned SW745310 if you are interested. Other examples for secure boot can be found in HSE Demo Examples (recommended): https://www.nxp.com/webapp/Download?colCode=S32K3_HSE_DemoExamples There are examples for all three modes – advanced secure boot, basic secure boot and SHE secure boot. Generally, advanced secure boot mode is recommended. Yes, it is not trivial task to configure the secure boot in this mode. However, it provides the best protection and configurability. The advantage is that you can select any signature scheme you want,  you can cover multiple regions and you can configure different sanctions if the secure boot fails. On other hand, basic secure boot mode always uses only GMAC tag which is calculated using a key derived from ADKP and it can cover one region only. If it fails, the device goes directly to recovery mode. I recommend to study following projects in HSE DemoExamples: S32K344_Advanced_SecureBoot S32K344_Basic_SecureBoot These are configuration projects which are supposed to protect application S32K344_SecureBootBlinky which is linked to those projects. Regards, Lukas Re: Fallback mechanism for failed AB_SWAP update Thanks for the clarity Lukas. I will look into the application note and the HSE demo examples and revert back in case of any queries. Regards, Shiv Re: Fallback mechanism for failed AB_SWAP update Ok that clears things up, thanks! So from what I am understanding: The Basic Secure Boot goes into recovery mode if the image verification fails. This recovery mode can be configured as Secure recovery using the attribute HSE_SECURE_RECOVERY_CONFIG_ATTR_ID. Configuring this mode requires programming the UTEST mode. Configuring this also needs the BOOT_SEQ == 1 in the IVT. The ADKP needs to be configured using HSE_APP_DEBUG_KEY_ATTR_ID in order to compute the GMAC. Couple of follow ups as I wrap my head around this: The Application Note you shared mentioned that configuring the ADKP can only be done in the CUST_DEL lifecycle. How do I verify the lifecycle of my system and is it safe to do so? Is the AppBL same as the IVT in the Basic Secure Boot. Do I need to append the GMAC and Recovery Image address to the IVT? Hoping to get a bit more clarity on these before I start implementation and testing on my boards. Thank you so much for being responsive and clearing my doubts! Regards, Shiv Re: Fallback mechanism for failed AB_SWAP update Take a look at section “2.6.1.3 Recovery Mode” in HSE firmware reference manual rev. 2.7. In short, there are two modes: JTAG based recovery mode – the device just hangs in endless loop in RAM (this piece of code is loaded to RAM by SBAF), so user can connect a debugger and perform some recovery steps. Secure recovery mode – this needs to be enabled by attribute HSE_SECURE_RECOVERY_CONFIG_ATTR_ID. Notice that this is OTP attribute programmed to UTEST memory. This starts recovery image which needs to be verified first. So, it is similar to basic secure boot. If the verification fails, it goes to JTAG recovery mode. The secure recovery mode can be used for recovery/rollback in runtime. But I do not recommend to run this from passive partition. All the code should be executed from active partition. In AB swap mode, you will have a copy of secure recovery image in both partitions anyway. Another option is to put this code to data flash memory if there’s enough space. Re: Fallback mechanism for failed AB_SWAP update See please my comments below. The Basic Secure Boot goes into recovery mode if the image verification fails. Yes. This recovery mode can be configured as Secure recovery using the attribute HSE_SECURE_RECOVERY_CONFIG_ATTR_ID. Yes. Configuring this mode requires programming the UTEST mode. The UTEST is programmed by HSE when calling set attribute service with HSE_SECURE_RECOVERY_CONFIG_ATTR_ID. Common issue – be aware that flash block 0 and UTEST are in the same read partition. You code cannot run from flash block 0 when programming this attribute. Configuring this also needs the BOOT_SEQ == 1 in the IVT. Yes. The ADKP needs to be configured using HSE_APP_DEBUG_KEY_ATTR_ID in order to compute the GMAC. Yes. Couple of follow ups as I wrap my head around this: The Application Note you shared mentioned that configuring the ADKP can only be done in the CUST_DEL lifecycle. How do I verify the lifecycle of my system and is it safe to do so? Yes, you can’t advance the life cycle until ADKP is set. Once the life cycle is advanced, secure debug is enabled, so you need to configure your debugger accordingly to be able to establish the connection. Take a look at this post: https://community.nxp.com/t5/S32K/S32K3-HSE/m-p/2066312/highlight/true#M47070 The life cycle status can be read from register DCMLCC in DCM module. Is the AppBL same as the IVT in the Basic Secure Boot. AppBL and IVT is signed and verified in the same way. IV and GMAC is also appended to the IVT. You can see that in “Table 118. IVT structure” in HSE firmware reference manual. Do I need to append the GMAC and Recovery Image address to the IVT? If you want to verify IVT, IV and GMAC must be added to IVT as mentioned above. If you want to use secure recovery image, pointer to the image and length of the image must be added to IVT. Regards, Lukas Re: Fallback mechanism for failed AB_SWAP update Thanks for the reply Lukas, this clarifies things! I will start implementing the Basic Secure Boot and will be in touch in case of any queries or doubts. Regards, Shiv 

Memory error occurs during flashing in TRACE32 _0-1786361688597.png When flashing via TRACE32 scripts, memory cannot be accessed. What could be the root cause? Re: Memory error occurs during flashing in TRACE32 As shown in the attached script, Lauterbach occasionally fails to access RAM. This issue can be resolved by re‑flashing the software via PE. Re: Memory error occurs during flashing in TRACE32 Hello @代码织梦师, Could you share which device you are using? Also verify the flash algorithm path in the .cmm script matches the device derivative.  From the image, I assume you are reading SRAM in S32K3, which does need ECC initialization, can you confirm you, or the startup file is correctly initializing SRAM ECC after POR? Best regards, Julián  Re: Memory error occurs during flashing in TRACE32 Hello @代码织梦师, It could be SRAM ECC initialization, although both the debugger as well as the startup code should initialize the SRAM ECC, if enabled. You can try the init_sram.cmm from demo scripts in T32: Julin_AragnM_0-1786473457854.png Best regards, Julián

Unable to Communicate with FS2400 Using KITFS24SKTFDMEVM and NXP GUI Subject: Unable to Communicate with FS2400 Using KITFS24SKTFDMEVM and NXP GUI Hi, I am trying to configure and program the OTP on the FS2400 using the KITFS24SKTFDMEVM evaluation board. Evaluation board: https://www.nxp.com/design/design-center/development-boards-and-designs/KITFS24SKTFDMEVM However, when I connect the board to the NXP GUI, I am unable to establish communication with the device. The GUI reports the error shown below, and no communication takes place. I have previously used the same NXP GUI with the FS26 evaluation board without any issues, so I believe my PC setup and GUI installation are working correctly. The evaluation board is in its default configuration, and I have not intentionally changed any jumper or switch settings. To verify, the current configuration is as follows: S12 (OTP): OFF J30: Pins 1-2 connected SW4 (WAKE2): ON S19 (WAKE3): ON J33: Open J37: Pins 2-3 connected J36: Pins 2-3 connected J10: Pins 2-3 connected SW9: All switches ON J45: Pins 2-3 connected J26: Pins 5-6 and 9-10 connected SW20: All switches OFF S2: ON (I could not locate this switch in the schematic ) SW18: All switches ON SW1 (Main Power Switch): Position 3 (2-3) I have not programmed the S32K144 MCU on the evaluation board. My understanding is that the board is shipped with the required firmware already programmed. Could someone confirm whether this is correct, or whether the MCU needs to be flashed before the GUI can communicate with the FS2400? Below is the error message displayed by the GUI: Any help would be greatly appreciated. Thank you. FS85&FS84 FSBC+PMIC Re: Unable to Communicate with FS2400 Using KITFS24SKTFDMEVM and NXP GUI Hello, Thank you for contacting us. Could you please update the firmware according to Section 5, "Installing and Configuring Software and Tools," of the UM12015 KITFS24SKTFDMEVM User Manual? This procedure should resolve the error you are experiencing. If the issue persists after completing the update, could you please provide a picture of your hardware setup? This will help us review the configuration and investigate the problem further. Thanks! Re: Unable to Communicate with FS2400 Using KITFS24SKTFDMEVM and NXP GUI Hi @ErikaC , Thank you for your response. I checked Section 5, “Installing and Configuring Software and Tools,” of the UM12015 KITFS24SKTFDMEVM User Manual. However, I am unable to find the KITFS2400FRDMEVM_HW_Test_Package_W20.zip file mentioned in the document. Could you please let me know where I can download this .zip file? I need it to update the firmware as described in the manual. I was able to find fs23xx-fw-FS24-v0.86.hex in the NXP GUI. Is this the firmware file that should be used for the update, or is it a different file included in the KITFS2400FRDMEVM_HW_Test_Package_W20.zip? I also checked the link provided in the manual: https://www.nxp.com/webapp/swlicensing/sso/downloadSoftware.sp?catid=S32DS-IDE-ARM-V2-XI downloaded and installed the executable from there (this was design studio but not the main S31244_Flash File), but I could not find the required .zip package. Could you please provide the download location for KITFS2400FRDMEVM_HW_Test_Package_W20.zip, or let me know where I can find the correct firmware package needed to perform the update? Thank you for your help. Ganesh Bhagwat Re: Unable to Communicate with FS2400 Using KITFS24SKTFDMEVM and NXP GUI Hi @ErikaC  If fs23xx-fw-FS24-v0.86.hex is the correct firmware file, is there any specific procedure required to directly load/flash this .hex file to the KITFS24SKTFDMEVM, or is there a specific tool/setup that needs to be used? If possible, it would also be greatly appreciated if you could provide the KITFS2400FRDMEVM_HW_Test_Package_W20.zip package or the download location for it, as this would make it much easier to follow the firmware update procedure described in the manual. Thank you for your help. Ganesh Bhagwat Re: Unable to Communicate with FS2400 Using KITFS24SKTFDMEVM and NXP GUI Hello, I could not find the KITFS2400FRDMEVM_HW_Test_Package_W20.zip folder. It was likely included in an earlier version of NXPGUI. However, that package only contained the fs23xx-fw-FS24-v0.86.hex file, which is the only file required to program the firmware. ErikaC_1-1786381048598.png Please follow all the steps described in the UM12014 KITFS2400FRDMEVM User Manual. The use of a debugger is required, as shown in Figure 17, and you must also install the S32 Design Studio tool. The firmware update procedure cannot be completed successfully without the required debugger connection and software environment described in the user manual. Hope this helps! Re: Unable to Communicate with FS2400 Using KITFS24SKTFDMEVM and NXP GUI Hi @ErikaC , Thanks for this. It worked, and I am now able to communicate with the NXP-GUI. The only issue was that these two settings were not present by default. As you mentioned, after adding them, everything worked. The command added under Executable was: ${cross_prefix}gdb${cross_suffix} Thanks again for your support. Regards, Ganesh Bhagwat

mc9s08qg8 drivers device manager: Jungo connectivity WinDriver:      Windows cannot verify the digital signature for the drivers required for this device. A recent hardware or software change might have installed a file that is signed incorrectly or damaged, or that might be malicious software from an unknown source. (Code 52)   pemicrowindvr:    This device is working properly.   These r the drivers i have in jungo!!!   ur input:   In USB Multilink Universal and USB Multilink Universal FX Technical Summary [USBMLUNIVERSALFX] documentation Chapter 6 Driver Installation mention that a copy of the driver installation program may be downloaded from P&E page "Support Center">Downloads. if you need an updated driver.   Best Regards,   What do u mean by this. Is this where i can get my BDM driver for my Wiztronics.com P&E interface board? Re: mc9s08qg8 drivers Hello, From the other post, I was referring that, as you are using P&E USB multilink Universal, the support page could redirect you to download a patch or an upgrade to your driver, I found these resources that could maybe help you if you have an incorrectly driver. In these page, its mentioned some patches for CodeWarrior v10.2 or higher and v6.3, to add support for PE hardware if is not detected by the operating system. PEmicro FAQ ID 211 Another option USB Multilink Resources Install Is a resource package for USB Multilink Universal, for when running older software. Also could you help us share which exact version of USB multilink Universal are you using? I could not guarantee this will work, since it’s a partner page, but it could redirect you in how to look for a driver correction for your issue, hope this information was helpful and let me know if that work for you Best Regards.

What Are the Best IPTV Providers in 2026? The way people watch television has changed faster than ever. Cable bills keep rising, viewers want more flexibility, and streaming has become the new normal. That is why many users now ask, What Are the Best IPTV Providers in 2026? They want better channel choices, smoother playback, and access to entertainment without the limits of traditional TV. 🛰️ Explore Best IPTV Providers IPTV stands for Internet Protocol Television. It delivers live TV channels, movies, sports, and on-demand content through an internet connection. Instead of using satellite or cable lines, users stream content directly on Smart TVs, Firestick, Android devices, tablets, and laptops. In 2026, IPTV services continue to grow because they offer convenience, value, and modern viewing features. This guide explains what makes a provider stand out and how to find the best IPTV solution for your needs. What Are the Best IPTV Providers in 2026 Known For? The best IPTV providers in 2026 are not only about having many channels. Quality matters more than quantity. A top provider should deliver stable streams, easy navigation, and strong customer support. Reliable IPTV services invest in better servers to reduce buffering. They also refresh channel lists regularly and maintain smooth access during busy hours. This is especially important for sports fans and live event viewers. Another sign of a strong provider is a user-friendly setup process. Good IPTV platforms make activation simple and compatible with popular apps and streaming devices. Why IPTV Is More Popular in 2026 Many households now prefer streaming because it matches modern lifestyles. Users want entertainment on their schedule, not fixed cable packages. Flexible Viewing on Any Device One major reason IPTV is growing is device freedom. Users can switch between Smart TVs, phones, tablets, and streaming sticks with ease. This creates a seamless entertainment experience. 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Premium IPTV services often include HD, Full HD, and 4K options for supported channels. Responsive Customer Support Fast support helps when login issues, setup errors, or app problems happen. Reliable customer service is a major factor when choosing an IPTV provider. How to Choose the Best IPTV Provider for You Every viewer has different priorities. Some want sports coverage, while others focus on movies or family entertainment. If live sports matter most, look for stable event streams and wide sports channel coverage. If you enjoy films and series, choose a provider with a strong VOD library and updated content. Families may prefer multi-device access and children’s channels. Travelers may want worldwide compatibility and flexible login options. Testing before subscribing is also wise. Many users search for IPTV free trial services to check quality before purchasing a long plan. SEO Trends Driving IPTV Searches Search phrases like best IPTV providers in 2026, top IPTV services, premium IPTV plans, and no buffering IPTV are becoming more common. This reflects growing demand for flexible streaming solutions. As internet speeds improve worldwide, IPTV becomes easier to use. Smart TVs and streaming devices are also more affordable, which helps IPTV adoption rise. People want personalized entertainment, and IPTV gives them more control than standard television packages. Mistakes to Avoid When Choosing IPTV Some users choose only the cheapest option. Low prices can be attractive, but poor stream quality and weak support may lead to frustration. Another mistake is ignoring compatibility. Always confirm the provider works on your preferred device. Skipping research can also cause problems. Reading recent reviews and testing a trial can help avoid unreliable services. The Future of IPTV in 2026 IPTV is expected to become smarter and more user-focused. Faster networks, improved apps, and better content libraries will continue to shape the market. Many providers are improving interfaces, search tools, and streaming stability. This means users can expect smoother experiences in the future. As demand rises, competition among IPTV providers may also improve pricing and service quality. Conclusion So, What Are the Best IPTV Providers in 2026? They are the services that combine stable streaming, quality content, easy setup, and strong support. The best option depends on your viewing habits, devices, and budget. When choosing an IPTV provider, focus on performance rather than promises. A service with reliable playback and useful features will always offer better value. If you are ready to upgrade your entertainment experience, explore trusted IPTV providers and enjoy smarter streaming in 2026. Re: What Are the Best IPTV Providers in 2026? Looking for the best way to enjoy premium content without an immediate commitment? In 2026, the most effective way to find a high-quality provider is through a free IPTV trial. Why Start with a Free Test? A free trial allows you to verify several critical factors before subscribing: Stability: Ensure the service offers buffer-free streaming and high uptime (ideally 99% or more). Content Variety: Check for access to over 20,000+ live channels, including premium sports, news, and international networks. Quality: Verify support for HD, Full HD, and 4K streaming. Device Compatibility: Confirm it works on your preferred hardware, such as Amazon Firestick, Smart TVs, Android/iOS devices, or PCs. Top Recommendation for 2026 For a premium experience with a vast selection of channels and reliable performance, we recommend testing GoldCard TV. It is designed to provide a seamless entertainment solution with minimal downtime. 👉 Start your free trial now at: https://omeulink.com/GoldCardTv Re: What Are the Best IPTV Providers in 2026? I’ve tested several IPTV providers over the past few months, and in my experience, HypoTV is one of the best overall for stability, streaming quality, and everyday entertainment. If you’re looking for sports-focused streaming, BekuTV performs really well with smooth live channels and minimal buffering. For adult content and large VOD libraries, PillowIPTV is a strong option. I’ve also seen many users recommend MomIPTV for its reliable international channel selection and multi-device support. Overall, each service has its strengths depending on what type of content you watch most. Re: What Are the Best IPTV Providers in 2026? I’ve tested many IPTV services, and NexusIPTV honestly surprised me with its stability and picture quality. Fast channels, almost no buffering, and a huge selection of sports, movies, and international content in HD/4K. Works perfectly on Firestick, Smart TVs, Android, iPhone, and PC. If you want a reliable IPTV service in 2026, NexusIPTV is definitely worth trying. www.nexusiptv.live  Re: What Are the Best IPTV Providers in 2026? I’ve tested a few services recently mainly for live sports, and UHDSports has honestly been one of the smoother ones so far. What I liked most is that it didn’t feel overloaded or messy. The setup was simple, the channels opened quickly on my device, and the sports streams were stable during peak hours, which is usually where most providers start buffering. I also tested it on a Smart TV and Android device, and both worked fine. The VOD side is decent too, but for me the main reason to use it is live sports. If you’re choosing a provider, I’d still recommend asking for a free trial first and testing it during an actual live match, not just during quiet hours. That’s the real test. Not saying it’s perfect, but from my experience UHDSports is worth checking if your priority is stable live sports and quick support. Re: What Are the Best IPTV Providers in 2026? If you’re tired of hunting for links, switching apps, or dealing with lag during big matches, tvaccess.xyz is the platform built for you. This premium paid service delivers every major sport in the world — all in HD, Full HD, and 4K Ultra Quality with smooth, stable streaming. Watch every sport live in HD/4K tvaccess.xyz Re: What Are the Best IPTV Providers in 2026? I agree that choosing an IPTV provider in 2026 really comes down to reliability, channel selection, and streaming quality. I also like services that make it easy to verify information before making a decision. For unrelated research, I recently found Franklin Property Data useful for checking property related details. It’s always worth comparing options carefully and choosing a service that fits your needs.

CAN-FD maximum baud rate on KW47 and MCXW72 The clock tolerance for CAN FD at high baud rates is generally considered to be tight compared to lower baud rates, meaning that the clock frequency needs to be very precise to ensure reliable communication; this is due to the high data rate requiring precise bit timing. CAN generally requires crystal or PLL clock source due to accuracy requirements, on KW45/7 that is limited to 32 MHz crystal (SOSC) since there is no PLL available. However, the FRO192 (FIRC) can be fine trimmed to the SOSC crystal as reference, in a closed loop configuration. When operating in closed loop the FRO192 accuracy is +/-0.25%. The FRO192 when operating in open loop (default) will not be accurate enough for CAN-FD (+/-3%). Closed loop operation is enabled while SCG0→FIRCCSR[FIRCTRUP] = 1 and SCG0→FIRCCSR[FIRCTREN] =1. The auto trim continues as long as those bits are set (for example if change in temperature causes the FRO192clock frequency to drift). Once locked, only the fine trim bits would be updated on subsequent corrections. Refer to code snippet below for correct clock configuration: #include "clock_config.h" #include "fsl_clock.h" const scg_sosc_config_t g_scgSysOscConfig_BOARD_BootClockRUN = { .freq = 32000000U, /* System Oscillator frequency: 32000000Hz */ .monitorMode = kSCG_SysOscMonitorDisable, /* System OSC Clock Monitor is disabled */ .enableMode = kSCG_SoscEnable, /* System OSC Enable */ }; const scg_sys_clk_config_t g_sysClkConfig_BOARD_BootClockRUN = { .divSlow = (uint32_t)kSCG_SysClkDivBy4, /* Slow Clock Divider: divided by 4 */ .divBus = (uint32_t)kSCG_SysClkDivBy1, /* Bus Clock Divider: divided by 1 */ .divCore = (uint32_t)kSCG_SysClkDivBy1, /* Core Clock Divider: divided by 1 */ .src=(uint32_t)kSCG_SysClkSrcFirc, /* Fast IRC is selected as System Clock Source */ }; static const scg_firc_trim_config_t FircTrimConfig_BOARD_BootClockRUN = { .trimMode = kSCG_FircTrimUpdate, /* FIRC trim is enabled and trim value update is enabled */ .trimsrc=kSCG_FircTrimSrcSysOsc, /* Trim source is System OSC */ .trimDiv = 31U, /* Divided by 32 */ .trimCoar = 0U, /* Trim value, see Reference Manual for more information */ .trimFine = 0U, /* Trim value, see Reference Manual for more information */ }; const scg_firc_config_t g_scgFircConfig_BOARD_BootClockRUN = { .enableMode = kSCG_FircEnable, /* Fast IRC is enabled */ .range = kSCG_FircRange96M, /* 96 Mhz FIRC clock selected */ .trimConfig = &FircTrimConfig_BOARD_BootClockRUN, }; /* Unlock FIRC and SOSC control status registers */ CLOCK_UnlockFircControlStatusReg(); CLOCK_UnlockSysOscControlStatusReg(); /* Init FIRC */ CLOCK_CONFIG_FircSafeConfig(&g_scgFircConfig_BOARD_BootClockRUN); /* Set SCG to FIRC mode */ CLOCK_SetRunModeSysClkConfig(&g_sysClkConfig_BOARD_BootClockRUN); /* Wait for clock source switch finished */ do { CLOCK_GetCurSysClkConfig(&curConfig); } while (curConfig.src != g_sysClkConfig_BOARD_BootClockRUN.src); /* Initializes SOSC according to board configuration */ (void)CLOCK_InitSysOsc(&g_scgSysOscConfig_BOARD_BootClockRUN); /* Set the XTAL0 frequency based on board settings */ CLOCK_SetXtal0Freq(g_scgSysOscConfig_BOARD_BootClockRUN.freq); /* For 6 mbps baud rate requires FRO192M as FlexCAN source clock */ CLOCK_SetIpSrc(kCLOCK_Can0, kCLOCK_IpSrcFro192M); CLOCK_SetIpSrcDiv(kCLOCK_Can0, kSCG_SysClkDivBy1); The maximum supported baud rate for KW47 and MCXW72 devices is 6 Mbps. Although higher rates may be achievable on some SoCs, 6 Mbps is the highest baud rate supported by the device clock specifications.  For simplicity, the FlexCAN driver APIs can be used to configure the CAN FD baud rate, as shown in the following code snippet: #include "fsl_flexcan.h" #define EXAMPLE_CAN CAN0 #define USE_CANFD (1) #define RX_MESSAGE_BUFFER_NUM (0) #define TX_MESSAGE_BUFFER_NUM (1) #define BYTES_IN_MB kFLEXCAN_64BperMB /* For 6 Mbps use case. FRO192 must be selected as clock source */ #define EXAMPLE_CAN_CLK_FREQ CLOCK_GetFreq(kCLOCK_ScgFircClk) #define USE_IMPROVED_TIMING_CONFIG (1) flexcan_config_t flexcanConfig; /* Get FlexCAN module default Configuration. */ /* * flexcanConfig.clksrc=kFLEXCAN_ClkSrc0; * flexcanConfig.bitRate = 1000000U; * flexcanConfig.bitRateFD = 2000000U; * flexcanConfig.maxMbNum = 16; * flexcanConfig.enableLoopBack = false; * flexcanConfig.enableSelfWakeup = false; * flexcanConfig.enableIndividMask = false; * flexcanConfig.disableSelfReception = false; * flexcanConfig.enableListenOnlyMode = false; * flexcanConfig.enableDoze = false; */ FLEXCAN_GetDefaultConfig(&flexcanConfig); /* Manually override default CAN FD config to 1 Mbps for nominal rate and 6 Mbps for data rate */ flexcanConfig.bitRate = 1000000U; flexcanConfig.bitRateFD = 6000000U; #if (defined(USE_IMPROVED_TIMING_CONFIG) && USE_IMPROVED_TIMING_CONFIG) flexcan_timing_config_t timing_config; memset(&timing_config, 0, sizeof(flexcan_timing_config_t)); if (FLEXCAN_FDCalculateImprovedTimingValues(EXAMPLE_CAN, flexcanConfig.bitRate, flexcanConfig.bitRateFD, EXAMPLE_CAN_CLK_FREQ, &timing_config)) { /* Update the improved timing configuration*/ memcpy(&(flexcanConfig.timingConfig), &timing_config, sizeof(flexcan_timing_config_t)); } #endif FLEXCAN_FDInit(EXAMPLE_CAN, &flexcanConfig, EXAMPLE_CAN_CLK_FREQ, BYTES_IN_MB, true); Note: The maximum supported CAN baud rate for KW47 and MCXW72 devices is 2 Mbps. While higher rates may be achievable under certain conditions, operation above 2 Mbps is outside the supported specification and is not recommended for applications in the field. 

eIQ Neutron NPU Support in Zephyr Zephyr now supports the eIQ Neutron NPU on MCX N and i.MX RT700. This article will describe how to get Zephyr and use the eIQ Neutron NPU libraries and examples.  Some previous experience with eIQ Neutron NPU enablement is assumed, so ensure you're familiar with the eIQ Neutron SDK, converting models for eIQ Neutron NPU, and basic ML concepts by going through the MCX N or i.MX RT700  NPU bare-metal lab guides for VS Code before continuing on below.  Install Software Run the MCUXpresso Installer tool and install three key components: Zephyr Developer Arm GNU Toolchain Zephyr SDK LinkServer anthony_huereca_0-1782845821454.png Install LinkServer and add LinkServer to the PATH Install VS Code and MCUxpresso VS Code plugin Download Zephyr Open VSCode Go to the MCUXpresso for VSCode plugin and click on Import Repository Go to the Remote tab and select the Zephyr repository. Choose it a directory name and location to download the repository to, and then click on Import. anthony_huereca_1-1782845403033.png It will take approximately 30 minutes to download the repository. Near the end of the download there will be several prompts in the terminal asking to accept licenses. Type “y” to accept and hit enter. There will be about 10 of these prompts at the end. Open the MCUXpresso Venv Terminal which has a Python virtual environment with all the paths preconfigured that were installed by MCUXpresso Installer. anthony_huereca_2-1782845420922.png In the terminal that pops up, type “1” to select the default environment. Then navigate to the directory you downloaded Zephyr into Run the following commands to get TensorFlow: west config manifest.project-filter -- +tflite-micro west update Go into the zephyr subdirectory folder cd zephyr Now need to explicitly download the Pull Request (PR) that enables eIQ Neutron. This eventually won’t be necessary when Zephyr 4.5 is released in October, but until then will need to type the following In the command prompt to get it: git remote -v git remote add upstream https://github.com/zephyrproject-rtos/zephyr.git git remote -v   git stash git fetch upstream pull/108834/head:pr-108834 git checkout pr-108834 After this command you should see there’s now a folder at \ \zephyr\samples\boards\nxp\tflm_neutron with example source code. Compile and Run a Zephyr eIQ Neutron NPU example Compile the project with west:  For MCX N: west build -p auto -b frdm_mcxn947/mcxn947/cpu0 samples/boards/nxp/tflm_neutron   For RT700: west build -p auto -b mimxrt700_evk/mimxrt798s/cm33_cpu0 samples/boards/nxp/tflm_neutron Open TeraTerm or other serial terminal program, and connect to the virtual COM port that board enumerated as when you plugged in the USB cable. Use 115200 baud, 1 stop bit, no parity. Flash the resulting code with west flash The serial terminal should show the following: anthony_huereca_3-1782845441830.png Can debug with west debug  Run your own NPU accelerated ML model in Zephyr Make sure you've gone through the MCX N or i.MX RT700  hands-on labs so you're familiar with the enablement. The same steps for converting a model with the Neutron Compiler tool inside eIQ Neutron SDK, updating the eIQ Neutron libraries, modfiying the operator list, and adding a new model are relevant when using Zephyr, but the file locations will be Zephyr specific. Also note that the header file generated by the Neutron Compiler tool will need to be updated to match the header of the model.hpp file.  Also note that the README.rst file in the Zephyr Neutron example mentions using eIQ Toolkit but that information is outdated and been superseded by eIQ Neutron SDK.  eIQ Neutron example is at \zephyr\samples\boards\nxp\tflm_neutron Neutron libraries are at \modules\hal\nxp\zephyr\blobs\neutron\ Model data is at \zephyr\samples\boards\nxp\tflm_neutron\src\models\mcxn\model.hpp Labels file is at \zephyr\samples\boards\nxp\tflm_neutron\src\labels.h kTensorArenaSize variable is set in \zephyr\samples\boards\nxp\tflm_neutron\src\main_functions.cpp (line 40) and is set to 60KB by default OpResolver is set in \zephyr\samples\boards\nxp\tflm_neutron\src\main_functions.cpp (line 65) The model is selected in \zephyr\samples\boards\nxp\tflm_neutron\src\main_functions.cpp (line 11) Additional References: Blog post on west which Zephyr uses. Zephyr on FRDM-MCXN947 Zephyr on i.MX RT700 Zephyr TensorFlow Hands-On Training

How to Update eIQ Projects with the Latest eIQ Neutron SDK Libraries eIQ Neutron SDK is a new software package that includes the Neutron Compiler tool and eIQ Neutron libraries to run Neutron converted neural network models on devices that have an eIQ Neutron NPU like MCX N, i.MX RT700, or i.MX95 Previously the Neutron Compiler tool was part of eIQ Toolkit. However going forward, new versions of the Neutron Compiler tool will be released as part of the eIQ Neutron SDK. This change will allow for more frequent updates to provide better performance and additional operator support. The Neutron Compiler tool was previously named the Neutron Converter tool, but the name was changed in August 2026 with the release of eIQ Neutron SDK 3.2.1. The functionality is the same, just the name changed.  MCUXpresso SDK and Linux BSP use Neutron libraries as part of the eIQ examples included in those software releases. However to use the latest Neutron Compiler, an eIQ project will need to be updated to use the latest Neutron software libraries. This post walks through where to place the updated Neutron libraries and header files.  If the version of the Neutron Compiler tool that was used to convert a model does not match the Neutron libraries used by the eIQ project, then during inference you will see the following error(s) printed on the serial terminal and may get incorrect results: Microcode version mismatch Or Internal Neutron NPU driver error 281b in model prepare Or Incompatible Neutron NPU microcode and driver versions The version of the Neutron Compiler tool that was used to convert a model can be found by either viewing the converted model in Netron or by looking at the generated header file:   header.png netron.png Here is a table showing where you can find the matching version of the Neutron Compiler tool for the default Neutron libraries found in different versions of MCUXpresso SDK: MCUXpresso SDK Default Neutron Library Version in MCUXpresso SDK Default Compatible Neutron Compiler/Converter Can Be Found In 24.12 1.2.0+0x6f710a6d eIQ Toolkit 1.17 25.03 1.2.0+0X1b86b19d eIQ Toolkit 1.17 25.06 2.0.2 eIQ Toolkit 1.17 25.09 2.1.3 eIQ Toolkit 1.17 25.12 2.2.2 eIQ Neutron SDK 2.2.2 26.03 3.0.0 eIQ Neutron SDK 3.0.0 26.06 3.1.1 eIQ Neutron SDK 3.1.1 Manually Update SDK Libraries To Use Latest Version eIQ Neutron SDK 3.2.1 It is highly recommend to always use the latest Neutron Compiler tool and to update the libraries in your eIQ project to match the latest Neutron Compiler tool. The libraries can be updated by overwriting the original files. You may wish to make a backup first though as the default eIQ examples in that SDK will use models that were converted to match those original Neutron libraries. The Neutron file structure in eIQ Neutron SDK and MCUXpresso SDK are now the same so that the entire Neutron folder can be overwritten directly.  Updating Neutron Libraries in MCUXpresso SDK 25.12 and later: File Source Directory in eIQ Neutron SDK Target Directory in MCUXpresso SDK libNeutronDriver.a target\imxrt700\ rt700\cm33\ \middleware\eiq\neutron\rt700\cm33\ libNeutronFirmware.a target\imxrt700\ rt700\cm33\ \middleware\eiq\neutron\rt700\cm33\ NeutronDriver.h target\imxrt700\ driver\include\ \middleware\eiq\neutron\driver\include\ NeutronErrors.h target\imxrt700\ common\include\ \middleware\eiq\neutron\common\include\ Note: The target\imxrt700\driver\include\NeutronEnvConfig.h and the libraries in target\imxrt700\cmodel are used by the ExecuTorch inference engine and so are not needed for TFLM eIQ projects.  Note: In MCUXpresso SDK 26.03 there are two sets of Neutron libraries in imported projects. It's the files in the /middleware/eiq folder that need to be updated.  anthony_huereca_0-1776090421844.png Updating Neutron Libraries in MCUXpresso SDK 25.09 or before: File Source Directory in eIQ Neutron SDK Target Directory in MCUXpresso SDK libNeutronDriver.a target\imxrt700\ rt700\cm33\ \middleware\eiq\tensorflow-lite\third_party\neutron\rt700\ libNeutronFirmware.a target\imxrt700\ rt700\cm33\ \middleware\eiq\tensorflow-lite\third_party\neutron\rt700\ NeutronDriver.h target\imxrt700\ driver\include\ \middleware\eiq\tensorflow-lite\third_party\neutron\driver\include\ NeutronErrors.h target\imxrt700\ common\include\ \middleware\eiq\tensorflow-lite\third_party\neutron\common\include\ Updating Neutron Libraries for MCUXpresso SDK 2.16 or before: Replace the entire middleware\eiq directory from MCUXpresso SDK 26.03 into your project, and then the Neutron libraries can be updated per the instructions above. In these older MCUXpresso SDK releases there were additional eIQ changes beyond just the four files above, so the easiest method to update those older projects is just to replace the entire eIQ middleware directory.  Updating Neutron Libraries for i.MX devices: To update the neutron runtime on a target device, upload the files to their designated directories, as follows: File Target Directory NeutronFirmware.elf /lib/firmware libNeutronDriver.so /lib/ libneutron_delegate.so /lib/

eIQ Toolkit for MCU - Getting Started Labs The tools previously bundled as part of eIQ Toolkit are now released as standalone packages and eIQ Toolkit will no longer be updated after the eIQ Toolkit v1.17 in Q3 2025. Going forward the tools previously included in eIQ Toolkit can now be found at: eIQ Neutron SDK now contains the latest versions of the Neutron Compiler tool (previously called the Neutron Converter tool before Aug 2026) eIQ Time Series Studio can now be found in a standalone package eIQ Model Creator provides an option for vision based model creation eIQ AI Toolkit will provide model optimization functionality (Coming Soon) Netron provides TFLite model viewing functionality This article will remain up for existing users. --------- eIQ Toolkit enables machine learning development with an intuitive GUI (named eIQ Portal) and development workflow tools, along with command line host tool options as part of the eIQ ML software development environment. Developers can create, optimize, debug and export ML models, as well as import datasets and models, rapidly train and deploy neural network models and ML workloads. The eIQ Portal provides output TensorFlow Lite models that seamlessly feed into eIQ inference engines like TensorFlow Lite and TensorFlow Lite for Microcontrollers. Using a tool called Model Runner, eIQ Toolkit can also generate runtime insights to help optimize neural network architectures on i.MX RT and i.MX devices. These labs go over how to use eIQ Portal. It is recommended to do them in the following order: Data Import Lab Model Runner Lab The labs are written for using a FRDM-MCXN947 and i.MX RT1170-EVK, but other eIQ supported devices can be used as well.  MCX N i.MX RT1050 i.MX RT1060 i.MX RT1064 i.MX RT1160 i.MX RT1170 i.MX RT1180 i.MX RT500 i.MX RT600 For details on the Time Series Studio tool please see the Time Series Studio lab guides. For  i.MX RT

eIQ Toolkit for MCU - 入门实验室 eIQ Toolkit 使用直观的GUI（名为eIQ Portal）和开发工作流工具以及命令行主机工具选项（作为eIQ ML软件开发环境一部分）支持机器学习开发。 开发人员可以创建、优化、调试和导出ML模型，以及导入数据集和模型，快速训练并部署神经网络模型和ML工作负载。 eIQ Portal提供可直接集成到eIQ推理引擎（如TensorFlow Lite和TensorFlow Lite for Microcontrollers）的输出TensorFlow Lite模型。使用名为Model Runner的工具，eIQ Toolkit还可以生成运行时洞察，帮助优化i.MX RT和i.MX设备上的神经网络架构。 这些实验将介绍如何使用eIQ Portal。建议按照以下顺序进行： 数据导入实验室 Model Runner实验室 这些实验室为使用FRDM-MCXN947和i.MX RT1170-EVK而编写，但也可以使用其他支持eIQ的设备。 MCX N i.MX RT1050 i.MX RT1060 i.MX RT1064 i.MX RT1160 i.MX RT1170 i.MX RT1180 i.MX RT500 i.MX RT600 有关eIQ Toolkit中包含的Time Series Studio工具的详细信息，请参阅Time Series Studio实验指南。 为了 i.MX RT

eIQ Toolkit for MCU - 入門ラボ eIQ Toolkitを使用すると、直感的なGUI（eIQ Portalと呼ばれる）と開発ワークフロー・ツール、およびeIQ MLソフトウェア開発環境の一部としてのコマンド・ライン・ホスト・ツール・オプションを利用して、機械学習の開発を行うことができます。 開発者は、MLモデルの作成、最適化、デバッグ、エクスポートに加え、データセットやモデルをインポートし、ニューラル・ネットワーク・モデルとMLワークロードを迅速にトレーニングして展開できます。 eIQ ポータルは、TensorFlow Lite やマイクロコントローラ用TensorFlow LiteなどのeIQ推論エンジンにシームレスにフィードする出力TensorFlow Liteモデルを提供します。Model Runner というツールを使用することで、eIQ Toolkit は i.MX RT および i.MX デバイス上のニューラルネットワークアーキテクチャを最適化するための実行時インサイトを生成することができます。 これらのラボでは、eIQ Portal の使用方法について説明します。以下の順序で行うことをお勧めします。 データインポートラボ モデルランナーラボ ラボは、FRDM-MCXN947およびi.MX RT1170-EVKを使用することを想定して作成されていますが、他のeIQサポート・デバイスを使用することもできます。 MCX N i.MX RT1050 i.MX RT1060 i.MX RT1064 i.MX RT1160 i.MX RT1170 i.MX RT1180 i.MX RT500 i.MX RT600 eIQ Toolkitに含まれるTime Series Studioツールの詳細については、Time Series Studioラボ・ガイドをご覧ください。 ために i.MX RT

Vision AI/ML with i.MX RT700 The i.MX RT700 microcontroller family includes an eIQ Neutron N3-64 NPU for accelerating neural network models. The i.MX RT700 EVK can be combined with a camera and LCD screen to showcase running TinyML vision models on a microcontroller. It's recommended to also go through the basic i.MX RT700 NPU Lab to learn more about eIQ enablement on RT700. The rest of this post will cover using vision models with camera+LCD on i.MX RT700.  i.MX RT700 Camera Hardware Setup: The following hardware is used: i.MX RT700 EVK RK055HDMIPI4MA0 LCD panel Camera Options: USB Camera with USB A to micro-B converter OV7670 parallel camera (with optional wide-angle lens) The USB camera should be attached to the i.MX RT700 EVK on USB OTG port J40. anthony_huereca_0-1777502759149.png The parallel camera interface is available on J53 and uses FlexIO with eDMA to read in the camera data. AN14836 describes the details. Note that the links in that app note for the demo software do not work but the demo code is in the process of being posted on NXP’s Application Code Hub.  When inserting the parallel camera align it to the left most side, as shown in the image below: anthony_huereca_0-1782156759078.png anthony_huereca_0-1782154106527.png Directions for attaching the LCD panel to the J52 connector on the underside of the i.MX RT700 EVK can be found on this Community post.  Note that there are multiple names used for the LCD panel and all these part numbers refer to the exact same panel: RK055HDMIPI4MA0 RK055MHD091 RK055MHD091-CTG RK055MHD091A0-CTG i.MX RT700 Vision ML Examples: There are two vision AI/ML examples for i.MX RT700 available today: Object Detection (part of AN14718) Hand Gesture Recognition Both of these examples use a USB camera.  i.MX RT700 Vision MPP Examples:  The Media Processing Pipeline (MPP) interference examples in i.MX RT700 MCUXpresso SDK 26.06 and later support both parallel and USB camera interfaces. These SDK examples are only available for command line GCC and VS Code MCUXpresso SDK layouts. They are not available for MCUXpresso IDE, IAR, or Keil.  anthony_huereca_0-1782155634010.png A parallel camera is used by default in the RT700 MPP projects. A USB camera can be enabled by adding a USE_USB_CAMERA declaration in the project's CMakeLists.txt file by adding the following macro: mcux_add_macro(     CC "-DUSE_USB_CAMERA"     CX "-DUSE_USB_CAMERA" ) However it's important to note that the camera_usb_final_fr_app_view project is setup to use USB camera by default, but it only works with a very specific HM2131 camera. All other MPP demos can work with most generic USB cameras. 

Vision ML with the FRDM-MCXN947 The MCX N microcontroller family includes an eIQ Neutron N1-16 NPU for accelerating neural network models. The FRDM-MCXN947 development board can be combined with a camera and LCD screen to showcase running TinyML vision models on a microcontroller.   MCX N Camera Hardware Setup: The following hardware is used: MCX N FRDM Development Board - FRDM-MCXN947 OV7670 camera (with optional wide-angle lens) NXP LCD-PAR-S035  There are three small modifications needed for the FRDM-MCXN947 board for camera support. Without this modification the camera colors will be incorrect and tinted red.   Change SJ16, SJ26, and SJ27 found on the back of the Rev B board to connect pin 3 (the dashed side) so that it looks like the following:          anthony_huereca_0-1770329042521.png Then connect the camera and LCD to the FRDM-MCXN947: Plug in the OV7670 camera into J11. It should line up with the orange box.         anthony_huereca_1-1770329080269.png                   anthony_huereca_2-1770329086311.png Connect the LCD-PAR-S035 LCD into J12. It should be flush with the bottom so that the top 2 rows of pins are left hanging off the edge. Also note that on some LCD-PAR-S035 boards those top two rows of pins are not installed.          anthony_huereca_3-1770329095085.png It should look like the following when complete           anthony_huereca_4-1770329100729.png Also as the camera and Ethernet pins are shared, if you need to use the Ethernet+Camera at the same time please see this NXP Community post. MCX N Vision ML Examples: The NXP Application Code Hub contains several vision AI/ML examples: Face Detect Face Detect with Zephyr Multiple Person Detection  CIFAR10 Fashion MNIST There are also Multimedia Processing Pipeline (MPP) examples inside the MCX N MCUXpresso SDK that demonstrate more examples of using vision AI/ML on MCX N. These examples are only available for VSCode/GCC in the Repository-Layout SDK package. Note: It is recommended to use MCUXpresso SDK 25.09 for these examples. The MPP issues in the 25.12 and 26.03 MCUXpresso SDK releases should be fixed in the upcoming MCUXpresso SDK 26.06.  anthony_huereca_5-1770329951165.png MCX N ML Vision Lab: The attached eIQ Neutron NPU for MCX N Lab Guide - Face Detect.pdf lab document walks through the steps to download an example Face Detect ML project from the NXP Application Code Hub and use the eIQ Neutron Compiler tool to convert a model. It also describes how to update the eIQ and Neutron software libraries in an older MCUXpresso SDK project to work with the latest eIQ Neutron SDK libraries. It is recommended to go through the general MCX N NPU Lab Guide first and then do the attached Face Detect lab second.  The lab is also included below: 1  Lab Overview This document will demonstrate the acceleration provided by the eIQ Neutron NPU using the Multiple Face Detection demo for the FRDM-MCXN947 found on the NXP App Code Hub. The demo will run with the non-NPU optimized model and then the performance can be compared to the NPU optimized version of that same model. It also demonstrates how the NPU optimized version of the face detect model was generated. This lab is written for MCUXPresso IDE but the same basic steps can be used for VSCode or GCC. This lab will also cover how to update the Neutron NPU libraries in the project, as the original Face Detect example uses an older Neutron library version. It is highly recommended to complete the eIQ Neutron NPU for MCX N Lab Guide before starting this lab. 2  Software and Hardware Installation This section will cover the hardware and software needed for this lab. 2.1 Hardware The following hardware is required for this lab: MCX N FRDM Development Board - FRDM-MCXN947 OV7670 camera (with optional wide-angle lens) NXP LCD-PAR-S035 2.2 NXP Software Installation          Install MCUXpresso IDE v25.6 or later. Download the latest eIQ Neutron SDK Download and unzip the latest MCUXpresso SDK for FRDM-MCXN947 using MCUXpresso SDK builder Search for the FRDM-MCXN947 board anthony_huereca_0-1779252823521.png Then click on Others anthony_huereca_1-1779252835626.png On the SDK builder page, make sure to select the “eIQ” middleware and that the MCUXpresso IDE toolchain is selected. Then click on Build SDK.   anthony_huereca_2-1779252845567.png Then click on the Download button and accept the license agreement to download the zip file. anthony_huereca_3-1779252852536.png 3   Face Detection Example 3.1 Download Face Detect Demo from App Code Hub The code for this lab can be found on the NXP Application Code Hub hosted on Github, and we can use MCUXpresso IDE to directly import the Face Detection example from App Code Hub. Drag-and-drop the FRDM-MCXN947 SDK zip file into the Installed SDKs window, located on a tab at the bottom of the screen named “Installed SDKs”. You will get the following pop-up, so hit OK. anthony_huereca_4-1779252865811.png Once imported, the Installed SDK tab will look something like this:  anthony_huereca_5-1779252872648.png In the Quickstart Panel found in the lower left corner, click on Import from Application Code Hub.. anthony_huereca_6-1779252877943.png In the dialog box that pops up there are many filters available to filter for different devices and types of demos. But since the name of the demo we are interested in is already known, the search box will be faster. Select the AI/ML category and then type in “face detection” and then click on the “Multiple face detection on mcxn947” demo. Make sure you don’t accidently click on the “Multiple Person Detection” demo. anthony_huereca_7-1779252885931.png On the popup that comes up, click on GitHub link at the top. At that point the Next button at the bottom will become clickable so click on that. anthony_huereca_8-1779252891875.png The next screen displays the possible branches. In this case there is only main so just click on the Next button at the bottom to go with the default. anthony_huereca_9-1779252899673.png The next dialog box determines the location on your computer where the code will be downloaded to. You can leave it at the default location if desired or click on Browse to pick your own location. Then click on Next. anthony_huereca_10-1779252906645.png The next screen will download the code and ask about importing the project. Click on Next to go with the default Import existing Eclipse projects option. anthony_huereca_11-1779252913518.png Then finally on the last screen click on Finish to import the project into your MCUXPresso IDE workspace. anthony_huereca_12-1779252920739.png You may get the following warning due to the project being made on an older version of the SDK. Then hit OK to accept the using the newest version. anthony_huereca_13-1779252927267.png  15. It should look like the following when done: anthony_huereca_14-1779252934804.png 3.2 Convert Model The demo is already using a model that was converted to take advantage of the eIQ Neutron NPU. This purpose of this section of the lab is to teach new NXP users how that model was converted. Unzip the eIQ Neutron SDK package in a directory of your choosing.   Optionally add \eIQ_NeutronSDK_ \bin to your executable path so that the neutron-compiler utility can be directly called from the command line. Back in MCUXpresso IDE, find the location of the original non-converted model used for this demo by right clicking on the face_detect.tflite file in source/model/ and going to Utilities->Open directory browser here. anthony_huereca_15-1779252951720.png Copy the directory location as it will be used in the next step anthony_huereca_16-1779252958805.png Open a Windows Command prompt and navigate to the directory where the model was at from the previous step             anthony_huereca_17-1779252967083.png Use the Neutron Compiler to convert the Face Detection model: neutron-compiler --input face_detect.tflite --output face_npu.tflite --target mcxn94x anthony_huereca_18-1779252973705.png 3.3 Update eIQ Neutron Libraries The Face Detect ACH example uses an older version of the eIQ Neutron libraries, and so it needs to be updated to match the Neutron libraries in newest eIQ Neutron SDK since the model was converted with that version of the Neutron Compiler tool. In the frdmmcxn947_multi_face_detection project, right click on the eiq folder and go to Utilities->Open directory browser here anthony_huereca_19-1779252981696.png Overwrite the Neutron files from the eIQ Neutron SDK folder into your project to update the Neutron libraries to the latest version: File Name Source Directory in eIQ Neutron SDK Target Directory in MCUXpresso SDK libNeutronDriver.a target\mcxn94x\board\ eiq\neutron\mcxn\cm33 libNeutronFirmware.a target\mcxn94x\board\ eiq\neutron\mcxn\cm33 NeutronDriver.h target\mcxn94x\driver\include\ eiq\neutron\driver\include NeutronErrors.h target\mcxn94x\common\include\ eiq\neutron\common\include After the new Neutron libraries are copied over, clean the project to ensure the new libraries will be used anthony_huereca_20-1779252988773.png 3.4 Board modifcations There are some hardware modifications to the MCX FRDM board required for this demo since the camera pins are muxed with the Ethernet pins and the Ethernet functionality is the default. The board version can be determined by scanning the QR code on the back of the MCX FRDM board with your phone. Most people will have Rev B boards. anthony_huereca_21-1779252995826.png Rev A: Remove the R157, R158, and R159 resistors from the back of the Rev A board so that it looks like the following: anthony_huereca_22-1779253003945.png Rev B: Change SJ16, SJ26, and SJ27 found on the back of the Rev B board to connect pin 3 (the dashed side) so that it looks like the following: anthony_huereca_23-1779253007749.png 3.5 Connect the camera and LCD Plug in the OV7670 camera into J11. It should line up with the orange box. anthony_huereca_24-1779253014542.png anthony_huereca_25-1779253017946.png Connect the LCD-PAR-S035 LCD into J12. Note that some older LCD-PAR-S035 LCDs may have an extra set of pins soldered on, and in that case the extra 2 rows of pins should be hanging off the edge like in the photo below.             anthony_huereca_26-1779253024933.png It should look like the following when complete anthony_huereca_27-1779253031139.png 3.6 Run Models Now open up model_data.s by double clicking on it, and then modify line 43 to point to the original (non NPU converted) model file named face_detect.tflite. This particular project uses the .tflite file directly. anthony_huereca_28-1779253042408.png Build the project by clicking on the Build icon in the Quickstart Panel anthony_huereca_29-1779253048317.png Then download and run the project by clicking on the Debug icon in the Quickstart Panel anthony_huereca_30-1779253054552.png You should see the demo working with an inference time of 817ms printed on the LCD display. Note: The default camera on the OV7670 is not very wide angle so you have to hold it fairly far back. There are wide-angle lenses that can be purchased to make it easier to demonstrate. Note: After POR there may be some glitching on the camera due to the fact the camera is expecting 2.8V but the board is at 3.3V and the initial HSYNC signal was missed. Press the reset button (SW1) and it should fix any camera issue.  Now let’s use the Neutron optimized model by opening model_data.s again and this time selecting the NPU converted model face_npu.tflite anthony_huereca_31-1779253063971.png Recompile and reprogram the board. You’ll see it is significantly faster with a 22ms inference time, a 37x improvement! 4  Conclusion This lab demonstrated how the eIQ Neutron NPU on MCX N devices can significantly decrease inference time on quantized models and the steps to generate a NPU optimized model using the command line tools. Also explore the other App Code Hub ML examples available online. FRDM-Training MCXN NPU|ML

Ara240 Module Bring-Up on FRDM-IMX95-PRO Getting Started Video: (function() { var wrapper = document.getElementById('lia-vid-6403214335112w960h540r398'); var videoEl = wrapper ? wrapper.querySelector('video-js') : null; if (videoEl) { if (window.videojs) { window.videojs(videoEl).ready(function() { this.on('loadedmetadata', function() { this.el().querySelectorAll('.vjs-load-progress div[data-start]').forEach(function(bar) { bar.setAttribute('role', 'presentation'); bar.setAttribute('aria-hidden', 'true'); }); }); }); } }})(); (view in My Videos) This guide provides step-by-step instructions on how to verify successful communication and the runtime software environment to interface with the Ara240 module with the FRDM i.MX 95 Pro development board. Out of the Box: Get Familiar with the Ara240 Module Ara240 Module [Back view]Ara240 Module [Back view] Ara240 Module [Top view]Ara240 Module [Top view]         Connecting the M.2 Module This section explains how to connect Ara240, a discrete module, to the FRDM i.MX 95 Pro development board. The instructions in the FRDM i.MX 95 Pro Getting Start Guide will walk you through the boot-up process for the pre-loaded Embedded Linux image on the board and how to connect the USB debug cable. For additional details, see the official FRDM i.MX 95 Pro Development Board documentation. References: FRDM i.MX 95 Pro Quick Start Guide FRDM i.MX 95 Pro Development Board product page  FRDM i.MX 95 Pro Getting started page Getting Started with ARA2-M2-16G-GT Follow the steps below to connect the Ara240 module to the FRDM i.MX 95 Pro development board: Spoiler (Highlight to read) Important: Ensure the board is powered off before making any connections. Important: Ensure the board is powered off before making any connections. Insert the Ara240 module into the M.2 Key-M socket on the FRDM i.MX 95 Pro development board. Using the screw provided, secure the module. Connect the fan cable to the board’s fan header (refer to the FRDM i.MX 95 Pro board documentation for the exact header location). "How to connect two Ara240 devices?" The figure below illustrates the connection of Ara240 devices to the two M.2 Key-M slots on the FRDM i.MX 95 Pro development board. You can install one Ara240 device in either slot or connect two devices simultaneously by using both slots. Connect the Ara240 to the FRDM i.MX 95 Pro development board.Connect the Ara240 to the FRDM i.MX 95 Pro development board. Power on the Board Follow the instructions to power on (boot) the board found in the Getting Started with FRDM-IMX95-Pro. After powering on, verify that the fan and green LED indicators Ara240 module are on are on. Get the Software This section will walk you through the Ara240 Runtime software development kit (SDK), a streamlined subset of the Ara240 SDK designed for rapid enablement and execution on NXP platforms. The Runtime SDK simplifies installation and configuration, enabling developers to quickly deploy and run AI/ML workloads on the Ara240 module with minimal effort. Overview Refer to Ara240 software release notes for details on the Ara240 software development kit (SDK) The Getting Started page for Ara240 only outlines usage on specific i.MX development platforms For any other platforms please reach out to your NXP representative for guidance. Spoiler (Highlight to read) Q2'26 BSP (L6.18.20-2.0.0) onwards runtime environment for i.MX 8MP and i.MX 95 boards is packed with Linux BSP. Q2'26 BSP (L6.18.20-2.0.0) onwards runtime environment for i.MX 8MP and i.MX 95 boards is packed with Linux BSP.     Module Enumeration and Software Configuration This section provides instructions to verify proper installation of Ara240 module and configuration of the Ara240 Runtime SDK on the FRDM i.MX 95 Pro development board. Verify Device Detection Once the board has successfully booted, connect to the serial debug port to monitor system logs. To confirm that the Ara240 module is being detected by the board, run the following command: $ lspci | grep 1e58 Expected output: 0000:01:00.0 Processing accelerators: Device 1e58:0002 (rev 02) Enable Ara240 device For quick enablement, the Ara240 Runtime SDK starts at boot time. Refer to the Ara240 Runtime SDK documentation for detailed instructions and environment setup steps. Spoiler (Highlight to read) Q2'26 BSP (L6.18.20-2.0.0) onwards runtime environment for i.MX 8MP and i.MX 95 boards is packed with Linux BSP. Q2'26 BSP (L6.18.20-2.0.0) onwards runtime environment for i.MX 8MP and i.MX 95 boards is packed with Linux BSP.     Developer Experience This section provides an overview of Ara240 runtime software enablement using the FRDM i.MX 95 Pro development board. Verify Setup Environment Use the following guidance on how to connect required devices. For most of the demos, you would need a camera, keyboard, mouse, internet connection and a HDMI display monitor. Setup preparation for FRDM i.MX 95 Pro boardSetup preparation for FRDM i.MX 95 Pro board Spoiler (Highlight to read)  NOTE: You might need to use a USB hub to connect keyboard, mouse and camera at the same time.  NOTE: You might need to use a USB hub to connect keyboard, mouse and camera at the same time.   Runtime setup Description Runtime SDK delivers a complete runtime environment that enables AI/ML acceleration on the Ara240 module. To run demo applications, ensure that the Ara240 bring-up process has been successfully completed and the system is ready for demo evaluation. Refer to the Runtime SDK documentation for detailed guidance on: Verifying correct installation of the Runtime SDK. Checking and updating the Ara240 firmware version. Validating proxy service bring-up status. Executing benchmark tests on Ara240. Following these steps ensures that the module is properly initialized and ready for use. Ara240 supports the execution of CNNs, LLMs, VLMs, and agentic frameworks, enabling advanced AI workloads to run directly on Ara240. For comprehensive examples and end-to-end workflow guidance, please refer to the Ara SDK documentation page. Ara240 Demos Henceforth Q2'26 Linux BSP, GoPoint can be launched to explore preselected Ara240 demonstrations included in the NXP provided Linux Board Support Package. User Guide: GPNTUG: GoPoint for i.MX Applications Processors User Guide  FRDM-IMX9

Subject: Standalone Evaluation Software / GUI for MC33774A AFE (RD33774CNC3EVB) I am working with the RD33774CNC3EVB (MC33774A-based CMU) and the RD-K358BMU evaluation board. I would like to evaluate and validate the MC33774A AFE independently, without integrating the complete BMS system. My goal is to verify features such as: - Cell voltage measurements - Temperature measurements - Diagnostics and fault reporting - Passive cell balancing - Register configuration - Communication between the BMU and AFE I have the following questions: 1. Does NXP provide a standalone evaluation GUI or PC software for the MC33774A? 2. Is there a FreeMASTER project, demonstration GUI, or any other graphical tool that can be used to monitor and configure the MC33774A through the BMU? 3. Is there a reference application or example firmware that enables evaluation of the MC33774A with minimal software development? 4. Are there any applications describing the recommended setup for evaluating the MC33774A using only the BMU and CMU evaluation boards? My objective is to perform functional validation of the AFE before integrating it into a complete BMS system. Thank you for your support. RD33774CNC3EVB , MC33774 , MC33665A  Re: Subject: Standalone Evaluation Software / GUI for MC33774A AFE (RD33774CNC3EVB) Dear Sanket, 1. Does NXP provide a standalone evaluation GUI or PC software for the MC33774A? [A] Yes, there is an EvalGUI 7 for the MC33774A. Specifically to be used with RD33774ADSTEVB. The GUI is intended to be used with SPI interface for communication between MCU and SPI to TPL transceiver and then via TPL to the MC33774A. Please refer to the UM11816.  JozefKozon_0-1785399710998.png If you are asking if there is a GUI specifically for the RD33774CNC3EVB with populated MC33665A TPL to CAN transceiver for the communication with MCU via CAN interface, unfortunately, there isn't any.  2. Is there a FreeMASTER project, demonstration GUI, or any other graphical tool that can be used to monitor and configure the MC33774A through the BMU? [A] For the BMU and CMU boards you mentioned we have a whole software bundle. However you need an S32DS IDE. JozefKozon_6-1785400949053.png Please refer to this link. Included are Demo projects for the FreeMASTER.  JozefKozon_1-1785400007530.png Please refer to the Release Notes document on the right side. JozefKozon_2-1785400038979.png 3. Is there a reference application or example firmware that enables evaluation of the MC33774A with minimal software development? [A] See above what software is available for the EVBs you have. However, the two boards are not sufficient. You need your own battery pack, with minimally 4 Cells for each MC33774A, or we have BATT-18EMULATOR. Emulating 18 Cells for each MC33774A populated on the RD33774CNC3EVB.  Please refer to the UM11943.  JozefKozon_3-1785400370798.png JozefKozon_4-1785400486233.png 4. Are there any applications describing the recommended setup for evaluating the MC33774A using only the BMU and CMU evaluation boards? [A] Yes there is. However as mentioned above you need either a battery pack or the battery emulator. Please refer to the UM11943 and to this link. JozefKozon_5-1785400737734.png With Best Regards, Jozef Re: Subject: Standalone Evaluation Software / GUI for MC33774A AFE (RD33774CNC3EVB) Can we use RD33774CNT3EVB(which is TPL based) for standalone testing as the mentioned part number is not available with us but RD3374CNT3EVB id available along with the required setup  RD33774CNT3EVB 

PCA9615 I am writing to ask for help with the circuits at either end of dI2C communication - between two PCBs across a twisted wire bundle (DSDAP & DSDAM; DSCLP &  DSCLM; two GND; and two 5V lines). Leading up to this I decided to test Gemini so I regretably relied on AI to generate the parts of the two PCBs that related to the dI2C comms. Attached are the parts of the schematics associated with the dI2C. Unsuprisingly there is no comms between the boards, but my laziness and I have to say stupidity (leason learnt) has cost me a lot of time. I finally referred to the datasheet and the user manual for the demo board and one obvious difference is that there are 600 Ohm resistors between the positive lines (DSCLP and DSDAP) and VDD(B), the same from the negative lines (DSCLM and DSDAM) and VSS, and 120 Ohms between the respective positive and negative lines which apparently result in 100 Ohms between the positive and negative lines (I know that 1/600 + 1/120 = 1/600 + 5/600 = 100, but I can't see it electrically- maybe because I'm a mechanical engineer ??). Is the error (maybe one of a number of errors) caused by not having what may be considered a 600 Ohm pull up resistor, a 600 Ohm pull down resistor and a 120 Ohm resistor between the respective pair of wries (characteristic impedance of a 28 AWG twisted wire pair is about 100 Ohms cabling used in internal data links and USB/Ethernet configurations and 78 Ω to 95 Ω for standard spacing configurations using PVC or FEP insulated wires), but instead a simplified and likely erroneous version of just a single 100 Ohm resitor at either end of the connecting wire on the dI2C side of the PCA9615?  That is one significant difference between what AI gave me and what I see in Figs 1, 7, 8 and 9 of the datasheet. Another difference is that AI suggested different capacitor arrangements for the two PCBs whereas there's only one type of arrangement on the demo board (which I assume gets used on both sides of the dI2C connecting line). Further, there appears to be two capacitors for each of the VDDA pin and the VDDB pin - both ceramic capacitors (although my first thought was that the two yellow capacitors would have been tantalum type). Can I use the capacitor arrangement provided in the demo user manual and ignore what AI provided and shown in the attached? Another issue is that on the master side (on which I am using a 3.3V microcontroller) originally Ai instructed that the enable pin be conencted to the 5V line, but after having had the boards made, the lack of any function across the two boards in part prompted the AI to determined that the enable pin on the master side should have been connected to the 3.3V line (VDD(A) on the master board was connected to the 3.3V line). It then requested that all all supply to the enable pin on the master PCB be cut completely as a test. Can you please advise what supply, if any all, should be channeled to the EN pin? I will not be hot swapping any electrical hardware during test or final operation. I am considering implementing the above changes, but would really appreciate your help before I proceed further with costly boards. Re: PCA9615 Just a further thing regarding the capacitors, only decoupling capacitors were suggested for both VDDA and VDDB pins on the master PCB. Decoupling capacitors were also suggested for the slave PCB, but two additional capacitors were also suggested for the VDDB pin on slave PCB.  Re: PCA9615 Hello! Thank you for the detailed explanation. Please note that NXP provides an evaluation board for the PCA9615 family that can be used as a reference design for your implementation. We strongly recommend comparing your schematic against the PCA9615 evaluation board and its associated user manual, as the design includes the recommended differential I²C termination network, biasing resistors, decoupling capacitors, and EN pin connections that have been validated by NXP. Using the evaluation board schematic as a baseline is often the best approach when designing a custom PCA9615-based system, as it minimizes the risk of configuration or layout issues and follows the recommendations provided in the datasheet and application documentation. We suggest reviewing the evaluation board schematic and updating your design accordingly before committing to another PCB revision. https://www.nxp.com/products/interfaces/ic-spi-i3c-interface-devices/ic-i3c-bus-repeaters-buffers-and-extenders/pca9616pw-demo-board:OM13523UL Hope this helps!

FRDM-IMX95: No Serial Output when Booting from SD Card (Pre-installed eMMC Boot Works Perfectly Hello NXP Community, I am mechanical and electrical engineering background, and this is my first time diving deep into complex System-on-Chips (SoCs) and embedded Operating Systems. For my project, I am using the FRDM-IMX95 development board. My ultimate goal is to run two operating systems in parallel using an IPC (Inter-Process Communication) framework. The board arrived with a pre-installed Linux image on the internal eMMC. This works flawlessly out of the box, and I get full serial output logs in my terminal monitor program. Now, I am trying to follow the official Getting Started Guide to flash the standard Linux BSP image onto a microSD card using UUU (Universal Update Utility) on a Windows host machine. According to the Windows command prompt, the UUU flashing process completes with a "SUCCESS" status. I used the following standard command layout: ".\uuu.exe -b sd_all imx-boot-imx95-15x15-lpddr4x-frdm-sd.bin-flash_all imx-image-full-imx95evk.wic" The Problem: After successful flashing, I turn off the board and configure the physical boot switches for SD Boot Mode by setting SW1 [1:2] to 11 (ON / ON). When I power the board back on, the serial monitor remains completely blank. There is absolutely no text output or hardware initialization visible. 1. Do I have a fundamental misunderstanding of how the boot chain works here? According to the i.MX Linux User's Guide, the .wic image contains all four essential pieces, including the bootloader image (U-Boot). Shouldn't I at least see the initial U-Boot SPL sequence appearing on my serial monitor, since the basic hardware configuration blocks should be read from the card? Any insights, common pitfalls for beginners on this specific FRDM variant, or hidden switch requirements would be highly appreciated! Best regards FRDM-Training Re: FRDM-IMX95: No Serial Output when Booting from SD Card (Pre-installed eMMC Boot Works Perfectly Hello,  I'm testing on my side to share the exact steps for you, I will update soon.  Re: FRDM-IMX95: No Serial Output when Booting from SD Card (Pre-installed eMMC Boot Works Perfectly Thank you for looking into this and testing it on your end! I appreciate the help and look forward to your update. Re: FRDM-IMX95: No Serial Output when Booting from SD Card (Pre-installed eMMC Boot Works Perfectly You have the issue because you are trying to flash to the SD card with the uuu tool, it is made to flash the emmc, if you want to flash the sd card you have to perform the following command in a linux host machine.  $ sudo dd if= .wic of=/dev/sdx bs=1M && sync To identify the device node assigned to the SD/MMC card, carry out the following command: $ cat /proc/partitions major minor #blocks name 8 0 78125000 sda 8 1 75095811 sda1 8 2 1 sda2 8 5 3028221 sda5 8 32 488386584 sdc 8 33 488386552 sdc1 8 16 3921920 sdb 8 18 3905535 sdb1

S32k344 design studio driver example code Hi Team  I wanted to run basic example codes on S32k344.  I have installed  S32 Design Studio for S32 Platform Version: 3.6.0 Build id: 241128 I am unable to find any diver examples in . I even with S32k extension and update to update s32k3xx package but the installation fails every time. It is stuck at 70%. Please let me know if you require any other information and help with basic examples. Regards Gopal Re: S32k344 design studio driver example code Hi @rathi_tg  To get started, we recommend using the latest version of the tools available, which is currently S32 Design Studio 3.6.10. There is no need to install it as a separate instance, as it can be installed as an update to your existing installation. Detailed instructions for this process can be found in the S32 Design Studio 3.6.10 RFP Installation Guide, which is available on the same download page as the S32DS installer. Regarding examples for S32K3 devices, these are included as part of the RTD packages. A good reference is the video How To Download, Install and Configure the RTD 5.0.0 with S32 Design Studio 3.6.0, which explains in detail what components need to be downloaded, how to install them, and how to create a project based on example. Although the video was created for RTD 5.0.0, the procedure is similar for newer RTD releases. Note: The latest RTD release available for S32K3 devices is RTD 7.0.1. Additionally, you may find useful examples and application projects in NXP's Application Code Hub, which contains a variety of ready-to-use examples for different devices and use cases. BR, VaneB Re: S32k344 design studio driver example code Hi   I have successfully imported the driver files and i have imported "Siul2_Dio_Ip_Example_S32K344" project. i have run the mex and updated the code. the code is built without any error. I have S32k344-WB with me which when powered on has a default switch and led program.  When I flash my built file the progress bar shows 100% but  i am unable to see any changes in the board behavior it is still executing the old code.  Regards  Gopal  Re: S32k344 design studio driver example code Hi @rathi_tg  How did you determine that the application is running old code? Also, please note that the example projects are tested with specific boards, which are listed in the description.txt file included with each example. Because different boards can have different hardware configurations, please verify that the pin assignments and configurations match your target board. You may need to update some of the pin settings accordingly to ensure the example works correctly on your hardware. Re: S32k344 design studio driver example code Hi @Valval  The issue got resolved i did not install the debug package  . Regards  Gopal

How Can I Watch All Live Events? Hi everyone, I’m a student and I’m trying to find a simple and reliable way to watch live events, sports, news, and other live programs online without getting confused by too many different websites and apps. I’ve heard people mention IPTVGREAT, but I’m not looking to promote any service. I just want to understand my options and find something that is safe, affordable, and easy for a student to use. If you have experience with watching live content online, could you please share some advice? I’d especially appreciate recommendations for legal and reliable options, free services, or affordable platforms that work well on a laptop or phone. Thanks to anyone who can help. I’m just trying to find a practical solution without spending too much as a student.