There is GPU SDK for i.MX6D/Q/DL/S: IMX_GPU_SDK.  This is to share the experience when compiling the example code from the SDK with Linux BSP release: L3.0.35_1.1.0_121218 and  L3.0.35_4.0.0_130424 . Minimal profile is using and have been verified on both i.MX6Q SDP and i.MX6DL SDP. To start: Please make sure “gpu-viv-bin-mx6q” has been selected in the Package list and compiled to your rootfs. After finished the compilation of the rootfs, you should find some newly added libraries for GLES1.0, GLES2.0, OpenVG and EGL in <ltib>/rootfs/usr/lib However, you should find libOpenVG.so is actually copied from libOepnVG_3D.so: vmuser@ubuntu:~/ltib_src/ltib/rootfs/usr/lib$ ls -al libOpen* -rwxr-xr-x 1 root root 115999 2013-06-06 18:31 libOpenCL.so -rwxr-xr-x 1 root root 515174 2013-06-06 18:31 libOpenVG_355.so -rwxr-xr-x 1 root root 272156 2013-06-06 18:31 libOpenVG_3D.so -rwxr-xr-x 1 root root 272156 2013-06-06 18:31 libOpenVG.so So, in this way, i.MX6D/Q will no use libOpenVG_355.so in the build. Also, if you run NFS, the libOpenVG.so will change to symbolic link:           For example, run on i.MX6Q SDP, it will link to /usr/lib/libOpenVG_355.so                          For example, run on i.MX6DL SDP, it will link to /usr/lib/libOpenVG_3D.so                Then, when you compile the OpenVG example code, it is becoming very confusing.  Thus, it needs to pay attention when doing the compilation.  For example, delete the symbolic link and make copy of the corresponding library: For i.MX6D/Q, please do this: $ sudo /bin/rm libOpenVG.so $ sudo cp libOpenVG_355.so libOpenVG.so For i.MX6S/DL, please do this: $ sudo /bin/rm libOpenVG.so $ sudo cp libOpenVG_3D.so libOpenVG.so To compile the sample code in the GPU SDK, you could refer to iMXGraphicsSDK_OpenGLES2.0.pdf or iMXGraphicsSDK_OpenGLES1.1.pdf in ~/gpu_sdk_v1.00.tar/Documentation/Tutorials to set up the cross compilation environment; which is assuming the LTIB and the rootfs is ready. $ export ROOTFS=/home/vmuser/ltib_src/ltib/rootfs $ export CROSS_COMPILE=/opt/freescale/usr/local/gcc-4.6.2-glibc-2.13-linaro-multilib-2011.12/fsl-linaro-toolchain/bin/arm-none-linux-gnueabi- For OpenVG: $ cd ~/gpu_sdk_v1.00/Samples/OpenVG $ make -f Makefile.fbdev clean $ make -f Makefile.fbdev $ make -f Makefile.fbdev install The executable will then be copied to this directory: ~/gpu_sdk_v1.00/Samples/OpenVG/bin/OpenVG_fbdev For GLES2.0 $ cd ~/gpu_sdk_v1.00/Samples/ GLES2.0 $ make -f Makefile.fbdev clean $ make -f Makefile.fbdev $ make -f Makefile.fbdev install The executable will then be copied to this directory: ~/gpu_sdk_v1.00/Samples/ GLES2.0/bin/GLES20_fbdev For GLES1.1, please modify the Makefile.fbdev to remove the compilation of example codes "18_VertexBufferObjects" and "19_Beizer" that are not exist. Then, $ cd ~/gpu_sdk_v1.00/Samples/ GLES1.1 $ make -f Makefile.fbdev clean $ make -f Makefile.fbdev $ make -f Makefile.fbdev install The executable will then be copied to this directory: ~/gpu_sdk_v1.00/Samples/ GLES1.1/bin/GLES11_fbdev Finally, you could copy the executable to the rootfs and test on i.MX6Q SDP/SDB or i.MX6DL SDP board. NOTE: the newly added makefiles.tgz contains Makefile.x11 hacked from GLES2.0 example code to make OpenVG to compile and run on Ubuntu 11.10 rootfs.

Linphone is an internet phone or Voice Over IP phone (VoIP). With Linphone you can communicate freely with people over the internet, with voice, video, and text instant messaging. Linphone makes use of the SIP protocol, an open standard for internet telephony. You can use Linphone with any SIP VoIP operator, including our free SIP audio/video service. Linphone is free software (or open-source), you can download and redistribute it freely. Linphone is available for desktop computers: Linux, Windows, Mac OSX, and for mobile phones: Android, iPhone, Blackberry. Linphone-android is a good example to show the integration of Java code based on Android SDK with native CODEC, network protocols. Not like XBMC-Android that is almost total c++/c project. Perform the following steps to build a linphone-android project: 1. git clone git://git.linphone.org/linphone-android.git --recursive 2. sudo apt-get install autoconf automake libtool pkg-config 3. "cd" to the root of "git clone" : cd /home/user/linphne-android // wherver git'ed linphone-android is 4. export PATH=/home/user/android-ndk:$PATH //wherever your android-ndk, android-sdk tools, and platform-tools, and ANT are stored in.             For example on my PC.      export PATH=/home/alanz/android-ndk-r8d:/home/alanz/android-sdk-linux/tools:/home/alanz/android-sdk-linux/platform-     tools:/home/alanz/bin/apache-ant-1.8.4/bin:$PATH             Note: PATH contains the ndk, sdk, and ant. 5. Make sure the network is working, then execute "./prepare_sources.sh" at the linphone-android root 6. Then, execute "/home/alanz/android-ndk-r8d/ndk-build", it will take a while to be finished 7. Modify Makefile as following example, modify it accordingly.      NDK_PATH=/home/alanz/android-ndk-r8d      SDK_PATH=/home/alanz/android-sdk-linux/tools      SDK_PLATFORM_TOOLS_PATH=/home/alanz/android-sdk-linux/platform-tools      .....................      generate-libs:           $(NDK_PATH)/ndk-build ....... (remove -j$(NUMCPUS) by the end of this command line) 8. execute "make", after finish, the apk file can be found under bin/ subdirectory.

ccache is a C compiler cache. ccache can save a large amount of compilation time on recurring builds and builds restarted from a clean repository after make clean or git clean. It is well suited for e.g. u-boot and Linux compilation. Caching the host compiler Caching "native" builds is easily done by adding in the beginning of your $PATH a special directory, which contains links to ccache to override the usual compiler. On e.g. Debian this directory is readily available as /usr/lib/ccache, So you can do:   $ export PATH="/usr/lib/ccache:$PATH" Typical links found in this folder are:   c++ -> ../../bin/ccache   cc -> ../../bin/ccache   g++ -> ../../bin/ccache   gcc -> ../../bin/ccache etc... Caching the cross compiler Caching cross-compiled builds can be done in the same way as native builds, provided you create links of the form e.g. arm-linux-gnueabihf-gcc pointing to ccache. But there is an even more convenient way for those projects, which rely on a $CROSS_COMPILE environment variable (as is the case for e.g. u-boot and Linux). You can prefix the cross compiler with ccache there in e.g. the following way:   $ export CROSS_COMPILE="ccache arm-linux-gnueabihf-" Monitoring efficiency Now that your builds are cached, you might want to see how much is "spared" with this technique. ccache -s will tell you all sorts of statistics, such as:   cache directory                     /home/vstehle/.ccache   cache hit (direct)                 10852   cache hit (preprocessed)            3225   cache miss                         19000   called for link                    33267   called for preprocessing            9463   compile failed                         3   preprocessor error                     1   couldn't find the compiler           117   unsupported source language          921   unsupported compiler option         2167   no input file                      31681   files in cache                     51694   cache size                           1.3 Gbytes   max cache size                       4.0 Gbytes Here you see a somewhat typical 50%/50% hit/miss ratio. Enjoy! See Also ccache is usually supported natively by build systems, such as Buildroot or Yocto.

The i.MX Android N7.1.1_1.0.0 release is now available on Web Site (i.MX6 BSP Updates and Releases -> Android).   Files available: # Name Description 1 android_N7.1.1_1.0.0_docs.tar.gz i.MX Android N7.1.1_1.0.0 BSP Documentation 2 android_N7.1.1_1.0.0_source.tar.gz Source Code of Android N7.1.1_1.0.0 BSP (4.1 kernel) for i.MX 6QuadPlus, i.MX 6Quad, i.MX 6DualPlus, i.MX 6Dual, i.MX 6DualLite, i.MX 6Solo  i.MX 6Sololite, i.MX6SX and i.MX7D 3 android_N7.1.1_1.0.0_image_6dqpsabreauto.tar.gz Binary Demo Files of Android N7.1.1_1.0.0 BSP - SABRE for Automotive Infotainment based on i.MX 6QuadPlus, i.MX 6Quad, and i.MX 6DualLite 4 android_N7.1.1_1.0.0_image_6dqpsabresd.tar.gz Binary Demo Files of Android N7.1.1_1.0.0 BSP - SABRE Platform and SABRE Board based on i.MX 6QuadPlus, i.MX 6Quad and i.MX 6DualLite. 5 android_N7.1.1_1.0.0_image_6slevk.tar.gz Binary Demo Files of Android N7.1.1_1.0.0 BSP - i.MX 6Sololite evaluation kit. 6 android_N7.1.1_1.0.0_image_6sxsabresd.tar.gz Binary Demo Files of Android N7.1.1_1.0.0 BSP - SABRE Board based on i.MX 6SoloX 7 android_N7.1.1_1.0.0_image_6sxsabreauto.tar.gz Binary Demo Files of Android N7.1.1_1.0.0 BSP - SABRE for Automotive infotainment based on i.MX 6SoloX 8 android_N7.1.1_1.0.0_image_7dsabresd.tar.gz Binary Demo Files of Android N7.1.1_1.0.0 BSP - SABRE Board based on i.MX 7Dual 9 android_N7.1.1_1.0.0_tools.tar.gz Manufacturing Toolkit and VivanteVTK for N7.1.1_1.0.0   Supported Hardware SoC/Boards: MX 6Quad, i.MX 6QuadPlus, and i.MX 6DualLite SABRE-SD board and platform MX 6Quad, i.MX 6QuadPlus, and i.MX 6DualLite SABRE-AI board and platform MX 6SoloLite EVK platform MX 6SoloX SABRE-SD board and platforms MX 6SoloX SABRE-AI board and platforms MX 7Dual SABRE-SD board and platform   Changes: Compared to the M6.0.1_2.1.0 release, this release has the following major changes: Upgraded the Android platform version to Android 7.1. Upgraded the U-Boot and Linux Kernel Code base from the L4.1.15_1.0.0 release to the L4.1.15_1.2.0-ga release. Added support for the i.MX 7Dual SABRE-SD board. Upgraded the GPU driver from 5.0.11p8 to 6.2.0.p2.   Feature: For features please consult the release notes.   Known issues For known issues and more details please consult the Release Notes.

Some Chinese customers using i.MX series SoC maybe encounter some issues when they download android , u-boot & kernel source code by 'git' command, the following steps will show customer how to get them: 1. Getting repo --No.1 methord # cd ~ # mkdir myandroid # mkdir bin # cd bin # git clone git://aosp.tuna.tsinghua.edu.cn/android/git-repo.git/ <if git failed, use : git clone https://aosp.tuna.tsinghua.edu.cn/android/git-repo.git/> # cd git-repo # cp ./repo ../ --No.2 methord # cd ~ # mkdir bin # curl https://storage.googleapis.com/git-repo-downloads/repo > ~/bin/repo # chmod a+x ~/bin/repo [Note]Customers can select one of above to get "repo" 2. Modifying repo File Open ~/bin/repo file with 'gedit' and Change google address From        REPO_URL = 'https://gerrit.googlesource.com/git-repo' To        REPO_URL = 'git://aosp.tuna.tsinghua.edu.cn/android/git-repo'        like following: ## repo default configuration ## REPO_URL = 'git://aosp.tuna.tsinghua.edu.cn/android/git-repo' REPO_REV = 'stable' 3、Setting email address # cd ~/myandroid # git config --global user.email "weidong.sun@nxp.com" # git config --global user.name "weidong.sun" [ Email & Name should be yours] 4、Getting manifest # ~/bin/repo init -u https://aosp.tuna.tsinghua.edu.cn/android/platform/manifest -b android-5.1.1_r1 # cd ~/myandroid/.repo # gedit manifest.xml        Then change the value of fetch to " git://aosp.tuna.tsinghua.edu.cn/android/ ", like following: <manifest>   <remote name="aosp"            fetch="git://aosp.tuna.tsinghua.edu.cn/android/" />   <default revision="refs/tags/android-5.1.1_r1" ...... [Note] android-5.1.1_r1 is version of branch,customer can change it to another. 5、# ~/bin/repo sync          [Note] During runing repo sync, maybe errors will occur like the following: ...... * [new tag]         studio-1.4 -> studio-1.4 error: Exited sync due to fetch errors          Then 'repo sync' exits. But don't worry about it, continue to run the command please ! " ~/bin/repo sync", downloading source code will be continous. 6、Getting Cross Compiler # cd ~/myandroid/prebuilts/gcc/linux-x86/arm # git clone https://aosp.tuna.tsinghua.edu.cn/android/platform/prebuilts/gcc/linux-x86/arm/arm-eabi-4.6 # cd arm-eabi-4.6 # git checkout android-4.4.3_r1 7、Getting linux kernel source code        Probably, customer can't normally get linux kernel by using "git clone" command, she can download it directly from the following weblink:        http://git.freescale.com/git/cgit.cgi/imx/linux-2.6-imx.git/        At first, create a temperary directory, then download kernel into the directory. see following steps: # cd ~ /Downloads # mkdir linux-kernel   Atfer downloading l5.1.1_2.1.0-ga.tar.gz, use 'tar zxvf l5.1.1_2.1.0-ga.tar.gz' command to decompress it.        Then you can find a subdirectory name " l5.1.1_2.1.0-ga" is created, linux source code is in the directory, we should copy all files in the directory to ~/myandroid/kernel_imx/ # cd ~/myandroid # mkdir kernel_imx # cd kernel_imx # cp -a ~ /Downloads/linux-kernel/l5.1.1_2.1.0-ga ./ 8、Getting uboot source code               Probably, customer can't normally get linux kernel by using "git clone" command, she can download it directly from the following weblink:       http://git.freescale.com/git/cgit.cgi/imx/uboot-imx.git/        We can use similar way to that of linux kernel to get u-boot source code: # cd ~ /Downloads # mkdir u-boot        Download l5.1.1_2.1.0-ga.tar.gz file, and save it in ~ /Downloads/ u-boot, then decompress it, then u-boot source code will be in ~ /Downloads/ u-boot / l5.1.1_2.1.0-ga/, we should copy all file in the path to ~/myandroid/bootable/bootloader/uboot-imx/ # cd ~/myandroid/bootable/bootloader # mkdir uboot-imx # cd uboot-imx # cp -a ~ /Downloads/u-boot/l5.1.1_2.1.0-ga/* ./ 9、Patch android BSP source code        android_L5.1.1_2.1.0_consolidated-ga_core_source.gz is the name of patch. Run following command to patch android. # copy android_L5.1.1_2.1.0_consolidated-ga_core_source.gz /opt/ # tar zxvf android_L5.1.1_2.1.0_consolidated-ga_core_source.gz # cd /opt/ android_L5.1.1_2.1.0_consolidated-ga_core_source/code/ # tar zxvf L5.1.1_2.1.0_consolidated-ga.tar.gz # cd ~/myandroid # source /opt/ android_L5.1.1_2.1.0_consolidated-ga_core_source/code/ L5.1.1_2.1.0_consolidated-ga/ and_patch.sh # help # c_patch /opt/ android_L5.1.1_2.1.0_consolidated-ga_core_source/code/ L5.1.1_2.1.0_consolidated-ga/ imx_L5.1.1_2.1.0-ga        If everything is OK, the following logs will display on console:               **************************************************************        Success: Now you can build the Android code for FSL i.MX platform               ************************************************************** 10、Patch Freescale extended feathures code        Please refer to chapter 3.3 of Android_User's_Guide.pdf to patch another 2 files:        (1) android_L5.1.1_2.1.0_consolidated-ga_omxplayer_source.gz        (2) android_L5.1.1_2.1.0_consolidated-ga_wfdsink_source.gz [Note]       As for other steps, such as compiling etc, please refer to Android_User's_Guide.pdf that released by NXP. TICS team Weidong Sun 04/01/2016

Inside IPU there are two block where color space conversion can be made: IC (Image Converter) and DP (Display processor). On Linux, the CSC parameters are located at IPU (IC and DP) drivers, linux/drivers/mxc/ipu3 folder. All negative coefficients are represented using two's complement. Linux Image Converter driver: The parameters are set on function _init_csc: http://git.freescale.com/git/cgit.cgi/imx/linux-2.6-imx.git/tree/drivers/mxc/ipu3/ipu_ic.c?h=imx_3.14.28_1.0.0_ga static void _init_csc(struct ipu_soc *ipu, uint8_t ic_task, ipu_color_space_t in_format, ipu_color_space_t out_format, int csc_index) { /* * Y = 0.257 * R + 0.504 * G + 0.098 * B + 16; * U = -0.148 * R - 0.291 * G + 0.439 * B + 128; * V = 0.439 * R - 0.368 * G - 0.071 * B + 128; */ static const uint32_t rgb2ycbcr_coeff[4][3] = { {0x0042, 0x0081, 0x0019}, {0x01DA, 0x01B6, 0x0070}, {0x0070, 0x01A2, 0x01EE}, {0x0040, 0x0200, 0x0200}, /* A0, A1, A2 */ }; /* transparent RGB->RGB matrix for combining */ static const uint32_t rgb2rgb_coeff[4][3] = { {0x0080, 0x0000, 0x0000}, {0x0000, 0x0080, 0x0000}, {0x0000, 0x0000, 0x0080}, {0x0000, 0x0000, 0x0000}, /* A0, A1, A2 */ }; /* R = (1.164 * (Y - 16)) + (1.596 * (Cr - 128));   G = (1.164 * (Y - 16)) - (0.392 * (Cb - 128)) - (0.813 * (Cr - 128));   B = (1.164 * (Y - 16)) + (2.017 * (Cb - 128); */ static const uint32_t ycbcr2rgb_coeff[4][3] = { {149, 0, 204}, {149, 462, 408}, {149, 255, 0}, {8192 - 446, 266, 8192 - 554}, /* A0, A1, A2 */ }; ‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍ Linux Display Processor driver: The parameters are set on constants (rgb2ycbcr_coeff and ycbcr2rgb_coeff): http://git.freescale.com/git/cgit.cgi/imx/linux-2.6-imx.git/tree/drivers/mxc/ipu3/ipu_disp.c?h=imx_3.14.28_1.0.0_ga /* Y = R * 1.200 + G * 2.343 + B * .453 + 0.250;   U = R * -.672 + G * -1.328 + B * 2.000 + 512.250.;   V = R * 2.000 + G * -1.672 + B * -.328 + 512.250.;*/ static const int rgb2ycbcr_coeff[5][3] = { {0x4D, 0x96, 0x1D}, {-0x2B, -0x55, 0x80}, {0x80, -0x6B, -0x15}, {0x0000, 0x0200, 0x0200}, /* B0, B1, B2 */ {0x2, 0x2, 0x2}, /* S0, S1, S2 */ }; /* R = (1.164 * (Y - 16)) + (1.596 * (Cr - 128));   G = (1.164 * (Y - 16)) - (0.392 * (Cb - 128)) - (0.813 * (Cr - 128));   B = (1.164 * (Y - 16)) + (2.017 * (Cb - 128); */ static const int ycbcr2rgb_coeff[5][3] = { {0x095, 0x000, 0x0CC}, {0x095, 0x3CE, 0x398}, {0x095, 0x0FF, 0x000}, {0x3E42, 0x010A, 0x3DD6}, /*B0,B1,B2 */ {0x1, 0x1, 0x1}, /*S0,S1,S2 */ };‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍

The following document contains a list of document, questions and discussions that are relevant in the community based on amount of views. If you are having a problem, doubt or getting started in i.MX processors, you should check the following links to see if your doubt is in there. Yocto Project Freescale Yocto Project main page‌ Yocto Training - HOME‌ i.MX Yocto Project: Frequently Asked Questions‌ Useful bitbake commands‌ Yocto Project Package Management - smart  How to add a new layer and a new recipe in Yocto  Setting up the Eclipse IDE for Yocto Application Development Guide to the .sdcard format  Yocto NFS &amp; TFTP boot  YOCTO project clean  Yocto with a package manager (ex: apt-get)  Yocto Setting the Default Ethernet address and disable DHCP on boot.  i.MX x Building QT for i.MX6  i.MX6/7 DDR Stress Test Tool V3.00  i.MX6DQSDL DDR3 Script Aid  Installing Ubuntu Rootfs on NXP i.MX6 boards  iMX6DQ MAX9286 MIPI CSI2 720P camera surround view solution for Linux BSP i.MX Design&amp;Tool Lists  Simple GPIO Example - quandry  i.MX6 GStreamer-imx Plugins - Tutorial &amp; Example Pipelines  Streaming USB Webcam over Network  Step-by-step: How to setup TI Wilink (WL18xx) with iMX6 Linux 3.10.53  Linux / Kernel Copying Files Between Windows and Linux using PuTTY  Building Linux Kernel  Patch to support uboot logo keep from uboot to kernel for NXP Linux and Android BSP (HDMI, LCD and LVDS)  load kernel from SD card in U-boot  Changing the Kernel configuration for i.MX6 SABRE  Android  The Android Booting process  What is inside the init.rc and what is it used for.  Others How to use qtmultimedia(QML) with Gstreamer 1.0

The i.MX 6 D/Q/DL/S/SL Linux 3.10.17_1.0.0 GA release is now available on www.freescale.com Files available Name Description L3.10.17_1.0.0_LINUX_DOCS i.MX 6 D/Q/DL/S/SL Linux 3.10.17_1.0.0 GA BSP documentation. y L3.10.17_1.0.0_iMX6QDLS_Bundle i.MX 6 D/Q/DL/S  Linux 3.10.17_1.0.0 GA BSP Binary Demo Files L3.10.17_1.0.0_iMX6SL_Bundle i.MX 6 SL  Linux 3.10.17_1.0.0 GA BSP Binary Demo Files i.MX_6_Vivante_VDK_150_Tools Vivante VTK 1.5 Codec for the i.MX 6 D/Q/DL/S/SL Linux 3.10.17_1.0.0 GA BSP    y L3.10.17_1.0.0_AACP_CODECS AAC Plus Codec for the i.MX 6 D/Q/DL/S/SL Linux 3.10.17_1.0.0 GA BSP y IMX_6_MFG_L3.10.17_1.0.0_TOOL Manufacturing Tool and Documentation for Linux 3.10.17_1.0.0 GA BSP y Target HW boards o   i.MX6DL  SABRE SD board o   i.MX6Q  SABRE SD board o   i.MX6DQ SABRE AI board o   i.MX6DL SABRE AI board o   i.MX6SL EVK board New  Features o   Main BSP New Features on MX6DQ, MX6DL and MX6SL from L3.10.9_1.0.0 GA: SD3.0 reset USB HSIC HWRNG security feature on MX6SL VIIM OTP Fuse in uboot Battery charge LED U-boot USB mass storage support USB Camera on host mode X backend: Adaptive HDMI display support backed by XRandR Main Codec New Features on MX6DQ, MX6DL and MX6SL from L3.10.17_1.0.0 Beta: Bug fix Main Codec New Features on MX6DQ, MX6DL and MX6SL from L3.10.17_1.0.0 Beta: Bug fix Other features not supported found during testing: UART: only support some baud rates like 9600, 115200, can't support high to 4000000 Known issues For known issues and limitations please consult the release notes located in the BSP documentation package.

The Linux L4.9.88_2.0.0 Rocko, i.MX7ULP Linux/SDK2.4 RFP(GA) release files are now available. Linux on IMX_SW web page, Overview -> BSP Updates and Releases ->Linux L4.9.88_2.0.0 SDK on https://mcuxpresso.nxp.com/ web page.   Files available: Linux:  # Name Description 1 imx-yocto-L4.9.88_2.0.0.tar.gz L4.9.88_2.0.0 for Linux BSP Documentation. Includes Release Notes, User Guide. 2 L4.9.88_2.0.0_images_MX6QPDLSOLOX.tar.gz i.MX 6QuadPlus, i.MX 6Quad, i.MX 6DualPlus, i.MX 6Dual, i.MX 6DualLite, i.MX 6Solo, i.MX 6Solox Linux Binary Demo Files 3 L4.9.88_2.0.0_images_MX6SLEVK.tar.gz i.MX 6Sololite EVK Linux Binary Demo Files 4 L4.9.88_2.0.0_images_MX6UL7D.tar.gz i.MX 6UltraLite EVK, 7Dual SABRESD, 6ULL EVK Linux Binary Demo Files 5 L4.9.88_2.0.0_images_MX6SLLEVK.tar.gz i.MX 6SLL EVK Linux Binary Demo Files 6 L4.9.88_2.0.0_images_MX8MQ.tar.gz i.MX 8MQuad EVK Linux Binary Demo files 7 L4.9.88_images_MX7ULPEVK.tar.gz i.MX 7ULP EVK Linux Binary Demo Files  8 L4.9.88_2.0.0-ga_mfg-tools.tar.gz Manufacturing Toolkit for Linux L4.9.88_2.0.0 iMX6,7 BSP 9 L4.9.88_2.0.0_mfg-tool_MX8MQ.tar.gz Manufacturing Toolkit for Linux L4.9.88_2.0.0 i.MX8MQ BSP 10 imx-aacpcodec-4.3.5.tar.gz Linux AAC Plus Codec for L4.9.88_2.0.0   SDK:   On https://mcuxpresso.nxp.com/, click the Select Development Board to customize the SDK based on your configuration then download the SDK package.    Target board: i.MX 6QuadPlus SABRE-SD Board and Platform i.MX 6QuadPlus SABRE-AI Board i.MX 6Quad SABRE-SD Board and Platform i.MX 6DualLite SABRE-SD Board i.MX 6Quad SABRE-AI Board i.MX 6DualLite SABRE-AI Board i.MX 6SoloLite EVK Board i.MX 6SoloX SABRE-SD Board i.MX 6SoloX SABRE-AI Board i.MX 7Dual SABRE-SD Board i.MX 6UltraLite EVK Board i.MX 6ULL EVK Board i.MX 6SLL EVK Board i.MX 7ULP EVK Board i.MX 8MQ EVK Board   What’s New/Features: Please consult the Release Notes.   Known issues For known issues and more details please consult the Release Notes.   More information on changes of Yocto, see: README: https://source.codeaurora.org/external/imx/imx-manifest/tree/README?h=imx-linux-rocko ChangeLog: https://source.codeaurora.org/external/imx/imx-manifest/tree/ChangeLog?h=imx-linux-rocko

Requirements: Host machine with Ubuntu 14.04 UDOO Quad/Dual Board uSD card with at least 8 GB Download documentation and install latest Official Udoobuntu OS (at the moment of writing: UDOObuntu 2.1.2), https://www.udoo.org/downloads/   Overview: This document describes how to install and test Keras (Open source neural network library) and Theano (numerical computation library for python ) for deep learning library usage on i.MX6QD UDOO board.  Installation: $ sudo apt-get update && sudo apt-get upgrade update your date system: e.g. $ sudo date -s “07/08/2017 12:00” First satisfy the run-time and build time dependencies: $ sudo apt-get install python-software-properties software-properties-common make unzip zlib1g-dev git pkg-config autoconf automake libtool curl  python-pip python-numpy libblas-dev liblapack-dev python-dev libatlas-base-dev gfortran libhdf5-serial-dev libhdf5-dev python-setuptools libyaml-dev libpython2.7-dev $ sudo easy_install scipy The last step is installing scipy through pip, and can take several hours. Theano First, we have a few more dependencies to get: $sudo pip install scikit-learn $sudo pip install pillow $sudo pip install h5py With these dependencies met, we can install a stable Theano release from the git source: $ git clone https://github.com/Theano/Theano $ cd Theano Numpy 1.9 cause conflicts with armv7, so we need to change the setup.py configuration: $ sudo nano setup.py Remove line    #       install_requires=['numpy>=1.9.1', 'scipy>=0.14', 'six>=1.9.0'], And add setup_requires=["numpy"], install_requires=["numpy"], Then install it: $ sudo python setup.py install Keras The installation can occur with the command: (this could take a lot of time!!!) $ cd .. $ git clone https://github.com/fchollet/keras.git $ cd keras $ sudo python setup.py install $ LC_ALL=C $sudo pip install --upgrade keras After Keras is installed, you will want to edit the Keras configuration file ~/.keras/keras.json to use Theano instead of the default TensorFlow backend. If it isn't there, you can create it. This requires changing two lines. The first change is: "image_dim_ordering": "tf"  --> "image_dim_ordering": "th" and the second: "backend": "tensorflow" --> "backend": "theano" (The final file should look like the example below) sudo nano ~/.keras/keras.json {     "image_dim_ordering": "th",     "epsilon": 1e-07,     "floatx": "float32",     "image_data_format": "channels_last",     "backend": "theano" } You can also define the environment variable KERAS_BACKEND and this will override what is defined in your config file : $ KERAS_BACKEND=theano python -c "from keras import backend" Testing Quick test: udooer@udoo:~$ python Python 2.7.6 (default, Oct 26 2016, 20:46:32) [GCC 4.8.4] on linux2 Type "help", "copyright", "credits" or "license" for more information. >>> import keras Using Theano backend. >>>  Test 2: Be aware this test take some time (~1hr on udoo dual): $ curl -sSL -k https://github.com/fchollet/keras/raw/master/examples/mnist_mlp.py | python Output: For demonstration, deep-learning-models repository provided by pyimagesearch and from fchollet git, and also have three Keras models (VGG16, VGG19, and ResNet50) online — these networks are pre-trained on the ImageNet dataset, meaning that they can recognize 1,000 common object classes out-of-the-box. $ cd keras $ git clone https://github.com/fchollet/deep-learning-models $ Cd deep-learning-models $ ls -l Notice how we have four Python files. The resnet50.py , vgg16.py , and vgg19.py  files correspond to their respective network architecture definitions. The imagenet_utils  file, as the name suggests, contains a couple helper functions that allow us to prepare images for classification as well as obtain the final class label predictions from the network Classify ImageNet classes with ResNet50 ResNet50 model, with weights pre-trained on ImageNet. This model is available for both the Theano and TensorFlow backend, and can be built both with "channels_first" data format (channels, height, width) or "channels_last" data format (height, width, channels). The default input size for this model is 224x224. We are now ready to write some Python code to classify image contents utilizing  convolutional Neural Networks (CNNs) pre-trained on the ImageNet dataset. For udoo Quad/Dual use ResNet50 due to avoid space conflict. Also we are going to use ImageNet (http://image-net.org/) that is an image database organized according to the WordNet hierarchy, in which each node of the hierarchy is depicted by hundreds and thousands of images. from keras.applications.resnet50 import ResNet50 from keras.preprocessing import image from keras.applications.resnet50 import preprocess_input, decode_predictions import numpy as np   model = ResNet50(weights='imagenet')   #for this sample I download the image from: http://i.imgur.com/wpxMwsR.jpg  img_path = 'elephant.jpg' img = image.load_img(img_path, target_size=(224, 224)) x = image.img_to_array(img) x = np.expand_dims(x, axis=0) x = preprocess_input(x)   preds = model.predict(x) # decode the results into a list of tuples (class, description, probability) # (one such list for each sample in the batch) print('Predicted:', decode_predictions(preds, top=3)[0]) Save the file an run it. Results for elephant image: Top prediction was 0.8890 for African Elephant Testing with this image: http://i.imgur.com/4FIOwAN.jpg Results: Top prediction was: 0.7799 for golden_retriever. Now your Udoo is ready to use Keras and Theano as Deep Learning libraries, next time we are going to show some usage example for image classification models with OpenCV. References: GitHub - fchollet/keras: Deep Learning library for Python. Runs on TensorFlow, Theano, or CNTK.  GitHub - Theano/Theano: Theano is a Python library that allows you to define, optimize, and evaluate mathematical expres…  GitHub - fchollet/deep-learning-models: Keras code and weights files for popular deep learning models.  Installing Keras for deep learning - PyImageSearch 

The i.MX 6 Android 13.4.1.03 patch release is now available on www.freescale.com IMX6_R13.4103_ANDROID_LDO_PATCH This patch release is based on the i.MX6 Android R13.4.1 release. The purpose of this patch release is to manage the LDO and PMIC ramp-up time correctly.

The i.MX Android N7.1.2_2.0.0 GA release is now available on IMX_SW page.   Files available: # Name Description 1 android_N7.1.2_2.0.0_docs.tar.gz i.MX Android N7.1.2_2.0.0 BSP Documentation 2 android_N7.1.2_2.0.0_source.tar.gz Source Code of Android N7.1.2_2.0.0 BSP (4.1 kernel) for i.MX 6QuadPlus, i.MX 6Quad, i.MX 6DualPlus, i.MX 6Dual, i.MX 6DualLite, i.MX 6Solo i.MX 6Sololite, i.MX6SX and i.MX7D 3 android_N7.1.2_2.0.0_image_6dqpsabreauto.tar.gz Binary Demo Files of Android N7.1.2_2.0.0 BSP - SABRE for Automotive Infotainment based on i.MX 6QuadPlus, i.MX 6Quad, and i.MX 6DualLite 4 android_N7.1.2_2.0.0_image_6dqpsabresd.tar.gz Binary Demo Files of Android N7.1.2_2.0.0 BSP - SABRE Platform and SABRE Board based on i.MX 6QuadPlus, i.MX 6Quad and i.MX 6DualLite. 5 android_N7.1.2_2.0.0_image_6slevk.tar.gz Binary Demo Files of Android N7.1.2_2.0.0 BSP - i.MX 6Sololite evaluation kit. 6 android_N7.1.2_2.0.0_image_6sxsabresd.tar.gz Binary Demo Files of Android N7.1.2_2.0.0 BSP - SABRE Board based on i.MX 6SoloX 7 android_N7.1.2_2.0.0_image_6sxsabreauto.tar.gz Binary Demo Files of Android N7.1.2_2.0.0 BSP - SABRE for Automotive infotainment based on i.MX 6SoloX 8 android_N7.1.2_2.0.0_image_7dsabresd.tar.gz Binary Demo Files of Android N7.1.2_2.0.0 BSP - SABRE Board based on i.MX 7Dual 9 fsl_aacp_dec.tar.gz AAC Plus Codec for N7.1.2_2.0.0 10 android_N7.1.2_2.0.0_tools.tar.gz Manufacturing Toolkit and VivanteVTK for N7.1.2_2.0.0   Supported Hardware SoC/Boards: i.MX 6Quad, i.MX 6QuadPlus, and i.MX 6DualLite SABRE-SD board and platform i.MX 6Quad, i.MX 6QuadPlus, and i.MX 6DualLite SABRE-AI board and platform i.MX 6SoloLite EVK platform i.MX 6SoloX SABRE-SD board and platforms i.MX 6SoloX SABRE-AI board and platforms i.MX 7Dual SABRE-SD board and platform   Changes: Compared to the N7.1.1_1.0.0 release, this release has the following major changes: Upgraded the Android code base from android-7.1.1_r13 to android-7.1.2_r9. Upgraded U-Boot from v2015.04 to v2017.03. Upgraded the kernel from v4.1.15 to v4.9.17. Upgraded the GPU driver from 6.2.0.p2 to 6.2.2.p1. Upgraded the Wi-Fi BCMDHD release version to 1.141.100.6. Refine the Gralloc and HWC HAL. Enable the GPT partition to replace the MBR partition.   Feature: For features please consult the release notes.   Known issues For known issues and more details please consult the Release Notes.

Hi All, The new Android JB4.3_1.1.0-GA release is now available on www.freescale.com ·         Files available           Name Description IMX6_JB43_110_ANDROID_DOCS i.MX   6Quad, i.MX 6Dual, i.MX 6DualLite, i.MX 6Solo and i.MX 6Sololite Android   jb4.3_1.1.0 BSP Documentation. Includes Release Notes, User's Guide, QSG and   FAQ Sheet. IMX6_JB43_110_ANDROID_SOURCE_BSP i.MX   6Quad, i.MX 6Dual, i.MX 6DualLite, i.MX 6Solo and i.MX 6Sololite Android   jb4.3_1.1.0 BSP, Documentation and Source Code for BSP and Codecs. IMX6_JB43_110_ANDROID_DEMO_BSP i.MX   6Quad, i.MX 6Dual, i.MX 6DualLite, i.MX 6Solo and i.MX 6Sololite Android   jb4.3_1.1.0  BSP Binary Demo Files IMX6_JB43_110_AACP_CODEC_CODA AAC   Plus Codec for i.MX 6Quad, i.MX 6Dual, i.MX 6DualLite, i.MX 6Solo and i.MX   6Sololite Android jb4.3_1.1.0 ·         Target HW boards o   i.MX6DL  SABRE SD board o   i.MX6Q  SABRE SD board o   i.MX6DQ SABRE AI board o   i.MX6DL SABRE AI board o   i.MX6SL EVK board ·         Release Description i.MX Android jb4.3_1.1.0 release includes all necessary codes, documents and tools to assist users in building and running Android 4.3 on the i.MX 6Quad, i.MX 6DualLite and i.MX6SoloLite hardware board from the scratch. The prebuilt images are also included for a quick trial on Freescale i.MX 6Quad and i.MX 6DualLite SABRE-SD Board and Platform, i.MX 6Quad and i.MX 6DualLite SABRE-AI Board and Platforms and i.MX6SoloLite EVK Board and Platforms. This release includes all Freescale porting and enhancements based on Android open source code. Most of deliveries in this release are provided in source code with the exception of some proprietary modules/libraries from third parties. ·         What's in this release         Android Source Code Patch All   Freescale i.MX specific patches (apply to Google Android repo)   to enable Android on i.MX based boards. For example Hardware   Abstraction Layer implementation, hardware codec acceleration,   etc. Packed in   android_jb4.3_1.1.0-ga_source.tar.gz Documents The   following documents are included in android_jb4.3_1.1.0-ga_docs.tar.gz: ●   i.MX Android jb4.3_1.1.0-ga Quick Start: A   manual explains how to run android on i.MX board by using prebuilt images. ●   i.MX Android jb4.3_1.1.0-ga User Guide: A   detailed manual for this release package. ●   i.MX Android jb4.3_1.1.0-ga FAQ: A document lists   “Frequently Asked Questions”. ●   i.MX Android Codec Release Notes: A   document to describes the Freescale Codec Package ●   i.MX Android Wi-FI Display Sink API Introduction A   document to describes how to use i.MX Android Wi-Fi Display Sink API ●   i.MX6 G2D API User Guide document to introduce how to use i.MX6 G2D API for   2D BLT usage ●   i.MX Android jb4.3_1.1.0-ga Release Note A   document to introduce the key updates and known issues in this release. Tools Tools   in android_jb4.3_1.1.0-ga_tools.tar.gz ●  MFGTool. Manufacturing tools for i.MX platform ●  USB tethering windows .inf driver configure file.tool/tetherxp.inf Prebuilt Images You   can test Android on i.MX with prebuilt image on i.MX board before building   any code. ● android_jb4.3_1.1.0-ga_image_6qsabresd.tar.gz: Prebuilt   images for the SABRE-SD board. ●  android_jb4.3_1.1.0-ga_image_6qsabreauto.tar.gz: Prebuilt   images for the SABRE-AI board. ●  android_jb4.3_1.1.0-ga_image_6slevk.tar.gz: Prebuilt images for the 6SL   SABRE-AI board. All   prebuilt images are in another package. See "i.MX Android jb4.3_1.1.0-ga   Quick Start" and "i.MX Android jb4.3_1.1.0-ga User Guide" to   understand which image should be used in which case. ·         Known issues For known issues and limitations please consult the release notes

Most common issues with bringup and memory stability come down to memory/system setup during startup phase of i.MX device.   This Python script allows you to dump IVT/DCD tables and data from a i.MX binary (either generated as result of build process or a simple dump of SD/NOR/NAND... content) and analyze them in an easier way. Should work with i.MX 6 and i.MX53 binaries.   Parser for i.MX 6 will also try to print out register values it recognizes, and also parse specific register fields, helping to analyze the data faster. This can be extended if needed to other registers/values.   imxbin.py works with Python3.x and imxbin_2x.py with Python 2.x, so choose appropriate version.   Vladan

    Xenomai is real-time framework, which can run seamlessly side-by-side Linux as a co-kernel system, or natively over mainline Linux kernels (with or without PREEMPT-RT patch). The dual kernel nicknamed Cobalt, is a significant rework of the Xenomai 2.x system. Cobalt implements the RTDM specification for interfacing with real-time device drivers. The native linux version, an enhanced implementation of the experimental Xenomai/SOLO work, is called Mercury. In this environment, only a standalone implementation of the RTDM specification in a kernel module is required, for interfacing the RTDM-compliant device drivers with the native kernel. You can get more detailed information from Home · Wiki · xenomai / xenomai · GitLab       I have ported xenomai 3.1 to i.MX Yocto 4.19.35-1.1.0, and currently support ARMv7 and tested on imx6ulevk/imx6ull14x14evk/imx6qpsabresd/imx6dlsabresd/imx6sxsabresdimx6slevk boards. I also did stress test by tool stress-ng on some boards.      You need to git clone https://gitee.com/zxd2021-imx/xenomai-arm.git, and git checkout Linux-4.19.35-1.1.0. (which inlcudes all patches and bb file) and add the following variable in conf/local.conf before build xenomai by command bitake xenomai.  XENOMAI_KERNEL_MODE = "cobalt"  PREFERRED_VERSION_linux-imx = "4.19-${XENOMAI_KERNEL_MODE}" IMAGE_INSTALL_append += " xenomai" DISTRO_FEATURES_remove = "optee" or XENOMAI_KERNEL_MODE = "mercury" PREFERRED_VERSION_linux-imx = "4.19-${XENOMAI_KERNEL_MODE}" IMAGE_INSTALL_append += " xenomai" DISTRO_FEATURES_remove = "optee" If XENOMAI_KERNEL_MODE = "cobalt", you can build dual kernel version. And If XENOMAI_KERNEL_MODE = "mercury", it is single kernel with PREEMPT-RT patch. The following is test result by the command (/usr/xenomai/demo/cyclictest -p 50 -t 5 -m -n -i 1000 😞 //Mecury on 6ULL with stress-ng --cpu 4 --io 2 --vm 1 --vm-bytes 128M --metrics-brief policy: fifo: loadavg: 6.08 2.17 0.81 8/101 534 T: 0 (  530) P:99 I:1000 C:  74474 Min:     23 Act:  235 Avg:   77 Max:    8278 T: 1 (  531) P:99 I:1500 C:  49482 Min:     24 Act:   32 Avg:   56 Max:    8277 T: 2 (  532) P:99 I:2000 C:  36805 Min:     24 Act:   38 Avg:   79 Max:    8170 T: 3 (  533) P:99 I:2500 C:  29333 Min:     25 Act:   41 Avg:   54 Max:    7069 T: 4 (  534) P:99 I:3000 C:  24344 Min:     24 Act:   51 Avg:   60 Max:    7193   //Cobalt on 6ULL with stress-ng --cpu 4 --io 2 --vm 1 --vm-bytes 128M --metrics-brief policy: fifo: loadavg: 7.02 6.50 4.01 8/100 660 T: 0 (  652) P:50 I:1000 C: 560348 Min:      1 Act:   10 Avg:   15 Max:      71 T: 1 (  653) P:50 I:1500 C: 373556 Min:      1 Act:    9 Avg:   17 Max:      78 T: 2 (  654) P:50 I:2000 C: 280157 Min:      2 Act:   14 Avg:   20 Max:      64 T: 3 (  655) P:50 I:2500 C: 224120 Min:      1 Act:   12 Avg:   15 Max:      57 T: 4 (  656) P:50 I:3000 C: 186765 Min:      1 Act:   31 Avg:   19 Max:      53   //Cobalt on 6qp with stress-ng --cpu 4 --io 2 --vm 1 --vm-bytes 512M --metrics-brief policy: fifo: loadavg: 8.11 7.44 4.45 8/156 1057 T: 0 (  917) P:50 I:1000 C: 686106 Min:      0 Act:    3 Avg:    5 Max:      53 T: 1 (  918) P:50 I:1500 C: 457395 Min:      0 Act:    3 Avg:    5 Max:      49 T: 2 (  919) P:50 I:2000 C: 342866 Min:      0 Act:    2 Avg:    4 Max:      43 T: 3 (  920) P:50 I:2500 C: 274425 Min:      0 Act:    3 Avg:    5 Max:      58 T: 4 (  921) P:50 I:3000 C: 228682 Min:      0 Act:    2 Avg:    6 Max:      46   //Cobalt on 6dl with stress-ng --cpu 2 --io 2 --vm 1 --vm-bytes 256M --metrics-brief policy: fifo: loadavg: 3.35 4.15 2.47 1/122 850 T: 0 (  729) P:50 I:1000 C: 608088 Min:      0 Act:    1 Avg:    3 Max:      34 T: 1 (  730) P:50 I:1500 C: 405389 Min:      0 Act:    0 Avg:    4 Max:      38 T: 2 (  731) P:50 I:2000 C: 304039 Min:      0 Act:    1 Avg:    4 Max:      45 T: 3 (  732) P:50 I:2500 C: 243225 Min:      0 Act:    0 Avg:    4 Max:      49 T: 4 (  733) P:50 I:3000 C: 202683 Min:      0 Act:    0 Avg:    5 Max:      38   //Cobalt on 6SX stress-ng --cpu 4 --io 2 --vm 1 --vm-bytes 512M  --metrics-brief policy: fifo: loadavg: 7.51 7.19 6.66 8/123 670 T: 0 (  598) P:50 I:1000 C:2314339 Min:      0 Act:    3 Avg:    8 Max:      60 T: 1 (  599) P:50 I:1500 C:1542873 Min:      0 Act:   15 Avg:    8 Max:      72 T: 2 (  600) P:50 I:2000 C:1157152 Min:      0 Act:    4 Avg:    9 Max:      55 T: 3 (  601) P:50 I:2500 C: 925721 Min:      0 Act:    5 Avg:    9 Max:      57 T: 4 (  602) P:50 I:3000 C: 771434 Min:      0 Act:    6 Avg:    6 Max:      41   //Cobalt on 6Solo lite stress-ng --cpu 4 --io 2 --vm 1 --vm-bytes 512M  --metrics-brief policy: fifo: loadavg: 7.01 7.04 6.93 8/104 598 T: 0 (  571) P:50 I:1000 C:3639967 Min:      0 Act:    9 Avg:    7 Max:      60 T: 1 (  572) P:50 I:1500 C:2426642 Min:      0 Act:    9 Avg:   11 Max:      66 T: 2 (  573) P:50 I:2000 C:1819980 Min:      0 Act:   11 Avg:   10 Max:      57 T: 3 (  574) P:50 I:2500 C:1455983 Min:      0 Act:   12 Avg:   10 Max:      56 T: 4 (  575) P:50 I:3000 C:1213316 Min:      0 Act:    7 Avg:    9 Max:      43   //Cobalt on 7d with stress-ng --cpu 2 --io 2 --vm 1 --vm-bytes 256M --metrics-brief policy: fifo: loadavg: 5.03 5.11 5.15 6/107 683 T: 0 (  626) P:50 I:1000 C:6842938 Min:      0 Act:    1 Avg:    2 Max:      63 T: 1 (  627) P:50 I:1500 C:4561953 Min:      0 Act:    4 Avg:    2 Max:      66 T: 2 (  628) P:50 I:2000 C:3421461 Min:      0 Act:    0 Avg:    2 Max:      69 T: 3 (  629) P:50 I:2500 C:2737166 Min:      0 Act:    3 Avg:    2 Max:      71 T: 4 (  630) P:50 I:3000 C:2280969 Min:      0 Act:    2 Avg:    1 Max:      33   //////////////////////////////////////// Update for Yocto L5.10.52 2.1.0  /////////////////////////////////////////////////////////// New release for Yocto release L5.10.52 2.1.0. You need to git clone https://gitee.com/zxd2021-imx/xenomai-arm and git checkout xenomai-5.10.52-2.1.0. Updating: 1, Upgrade Xenomai to v3.2 2, Enable Dovetail instead of ipipe. Copy xenomai-arm to <Yocto folder>/sources/meta-imx/meta-bsp/recipes-kernel, and add the following variable in conf/local.conf before build Image with xenomai enable by command bitake imx-image-multimedia. XENOMAI_KERNEL_MODE = "cobalt" IMAGE_INSTALL_append += " xenomai" or XENOMAI_KERNEL_MODE = "mercury" IMAGE_INSTALL_append += " xenomai" Notice: If XENOMAI_KERNEL_MODE = "cobalt", you can build dual kernel version. And If XENOMAI_KERNEL_MODE = "mercury", it is single kernel with PREEMPT-RT patch. //////////////////////////////////////// Update for Yocto L5.15.71 2.2.0  /////////////////////////////////////////////////////////// New release for Yocto release L5.15.71 2.2.0. You need to git clone https://gitee.com/zxd2021-imx/xenomai-arm and git checkout xenomai-5.15.71-2.2.0. Updating: 1, Upgrade Xenomai to v3.2.2 Copy xenomai-arm to <Yocto folder>/sources/meta-imx/meta-bsp/recipes-kernel, and add the following variable in conf/local.conf before build Image with xenomai enable by command bitake imx-image-multimedia. XENOMAI_KERNEL_MODE = "cobalt" IMAGE_INSTALL:append += " xenomai" or XENOMAI_KERNEL_MODE = "mercury" IMAGE_INSTALL:append += " xenomai" Notice: If XENOMAI_KERNEL_MODE = "cobalt", you can build dual kernel version. And If XENOMAI_KERNEL_MODE = "mercury", it is single kernel with PREEMPT-RT patch.   ///////// Later update for Later Yocto release, please refer to the following community post //////////// 移植实时Linux方案Xenomai到i.MX ARM64平台 (Enable real-time Linux Xenomai on i.MX ARM64 Platform)   

This patch release is target for LPDDR2 ( dual channels in interleave mode ) support on i.MX6DL platform. Two patches are prepared to modify u-boot and kernel in order to have correct DRAM init sequence, 400MHz & 24MHz frequency switching and suspend/resume support. The patches are not fully verified. It is provided as reference for customer to enable their i.MX6DL board with LPDDR2. Customization and Testing is needed by customer. We need to remind some points here: MMDC_MDCFG3LP in 24MHz need to increase the margin ( 0x40222 -> 0x80555 ) in order to pass the OS frequency switch stress test. We are identifying the reason but this workaround is working fine and included to the patch. Code changes in kernel is prepared so that it is compatible to DDR3. In other words, the DDR type will be detected and a correct handling will be done for LPDDR2 and DDR3. In LPDDR2 system, we can't put SDQ pin into LPM during suspend. Otherwise, the system cannot resume. Dual channels in fix mapping mode is not recommended to use.

These questions and answers are about interrupt generation at a dedicated (configurable) video output port. The i.MX6D manual (Rev. 0) Image Processing Unit (IPU) chapter mentions: Every DI has 10 timing generator counters. The IPU Interrupt Generator has 10 DI0 counters (1...10) and just 2 DI1 counters (3 & 😎 as interrupt sources. The Interrupt Control Register lists 11 DI0 counters (0...10) Q1. Are the DI timing-generator counters linked to the counters in the interrupt controller, or are they different counters? A1. Yes, the DI timing generator counters are linked to the counters in the interrupt controller. Q2. Why are there 11 counters listed in the interrupt controller, but just 10 counters in the timing generator? A2. There is disp_clk_en_pre in the interrupt controller. Thus the 11 counters: 10 timing generator counters and 1 disp clock generator counter. Q3. Is configurable timing feasible for DI0 by using the timing generator counters? A3. Yes, using the 10 internal timing counters you can generate various timing relationships. In addition, you can detect any of the interrupt counters. For example, if you use counter 8, then you can detect the interrupt associated with counter 8. Q4. Explain the impact of the DI1 counter access of only channels 3 and 8. A4. DI1 also has 10 timing generator counters and 1 disp clock generator counter, which you can use to generate desired waveforms. This is similar to DI0. The difference is only 2 of the 10 counters (plus another disp_clk) are connected to the interrupt controller for DI1. Therefore, there is a restriction for detection. If you use counter 7, read out the counter 7 interrupt of DI1 is not possible. However, 2 channels should be sufficient. These interrupts are usually used to indicate a frame start or a frame end. We usually use counter 3 to represent Vsync. So normally we only use counter 3 interrupt. DI1 has only 3 accesses because this covers the anticipated use case and the desire was to restrict register size. The extra counters facilitate flexible DI1 timing generation.

Freescale's PF0100 PMIC should have VDDIO power tied to the same supply as the associated I2C supply on MX6. There is a momentary on-chip sneak path on power-up if VDDIO is wired per the i.MX6 SABRE-AI automotive development platform. As a result, I2C power rail P3V3_DELAYED rises prematurely due to backfeed from P3V3 through the I2C port. Note that on SABRE-AI, P3V3 powers up before P3V3_DELAYED. Existing SABRE-AI design: PF0100 VDDIO is wired to P3V3. Corrective action for mass production: Wire PF0100 VDDIO to P3V3_DELAYED; same supply as the associated I2C supplies on MX6 (NVCC_EIM0 and NVCC_GPIO). Laboratory results attached.

Q: Q&A: Where to find IBIS Models on the web? A: In the first figure (FSL driving 100 ohm), the processor is DC coupled to a transmission line and terminated at the far end with a 100-ohm resistor. The results look pretty normal for this. In the other figure, the processor is dc coupled to a transmission line, then ac coupled to another transmission line segment (0.1u) with 50-ohm resistors to ground, and then drives the inputs of an HCSL clock buffer. The results are pretty un remarkable. The top red signal in the trace is one of the IMX6 clock outputs, the first green signal is the other clock output, and the last green signal (from top to bottom that is) is the differential signal seen by the clock buffer. The customer is concerned about the asymmetrical drive of the processor. It looks like LVDS clock outputs do not like to be AC coupled. This simulation resembles the way the clock is handled in the Smart Device schematics where the clock is AC coupled to the reference clock inputs on the PCIE connector. The ibis files were downloaded from the web (21x21_imx6q, consumer variant). So a few updates: I had the customer download the latest duallite IBIS models. Previously they were apparently using the quad/dual models. They are going to update HyperLynx and are going to run a simulation and let me know if they still see the same issue. He said he's using "linesim". Meanwhile he noticed a different problem with the duallite/solo IBIS models. Although the datasheet says LVDDR3 (1.35V) is supported, there is no model for DDR3_L either as input or output. The same model existed in the quad/dual models. Do you know why this option is not in the duallite IBIS models? Thanks! A ctm of mine would like to get the IBIS model with LVDDR3 support on the i.MX6 DL. For mx6-duallite IBIS models for DDR3L memory (1.35V). It'd be great if the models matched the quad version. Please find the new updated IBIS file in website. http://www.freescale.com/webapp/sps/site/prod_summary.jsp?code=i.MX6DL&nodeId=018rH3ZrDRB24A&fpsp=1&tab=Design_Tools_Tab

Hello everyone, We have recently migrated our Source code from CAF (Codeaurora) to Github, so i.MX NXP old recipes/manifest that point to Codeaurora eventually will be modified so it points correctly to Github to avoid any issues while fetching using Yocto. Also, all repo init commands for old releases should be changed from: $ repo init -u https://source.codeaurora.org/external/imx/imx-manifest -b <branch name> [ -m <release manifest>] To: $ repo init -u https://github.com/nxp-imx/imx-manifest -b <branch name> [ -m <release manifest>] This will also apply to all source code that was stored in Codeaurora, the new repository for all i.MX NXP source code is: https://github.com/nxp-imx For any issues regarding this, please create a community thread and/or a support ticket. Regards, Aldo.