Which tools exist for analysis of Qualcomm DSP Hexagon crash postmortem files (CODERAM.BIN, DATARAM.BIN) ?
TRACE32 do not support Data.LOAD.CORE command for Hexagon (according to Lauterbach support).
I have relevant ELF file.
Use the Crashman Tool from
<platform_BSP_folder>/adsp_proc/crashman/
Related
I've created a basic image with buildroot (buildroot-2021.02.1), containing some software and also selected the RPI firmware in order to use the camera and some Raspberry Pi tools: Target packages --> Hardware handling --> Firmware --> ([x] rpi-firmware) --> Firmware to boot as mentioned here.
But the tools raspistill, vcgencmd, ... are not included. The question is how to include them and why are they not included?
At some point in time it must have been working, see: RaspberryPi camera with buildroot
More details:
In the logs of buildroot the following lines show up:
>>> rpi-firmware d016a6eb01c8c7326a89cb42809fed2a21525de5 Installing to target
comm: /home/ich/br/buildroot/output/build/rpi-firmware-d016a6eb01c8c7326a89cb42809fed2a21525de5/.files-list.before: No such file or directory
comm: /home/ich/br/buildroot/output/build/rpi-firmware-d016a6eb01c8c7326a89cb42809fed2a21525de5/.files-list-staging.before: No such file or directory
comm: /home/ich/br/buildroot/output/build/rpi-firmware-d016a6eb01c8c7326a89cb42809fed2a21525de5/.files-list-host.before: No such file or directory
and inside this package the binaries are existing. They are downloaded from http://sources.buildroot.net/rpi-firmware/ where the tars contain the actual tools. But they are not copied into the final image by buildroot but only downloaded. Maybe because some files-list.txt file(s) are missing, as pointed out by the error message. Maybe those files are whitelisting the files to copy. But I could not find documentation about this.
For 64-bit builds the binaries in the (then manually downloaded) tar file could not be executed, because they are 32-bit executables: firmware-d016a6eb01c8c7326a89cb42809fed2a21525de5/opt/vc/bin/vcgencmd: ELF 32-bit LSB executable, ARM, EABI5 version 1 (SYSV), dynamically linked, interpreter /lib/ld-linux.so.3, for GNU/Linux 3.1.9, not stripped; on a 32-bit build with buildroot it also does not work, because the shared libraries are missing, even though the full structure from the archive has been placed under /opt/vc/{bin|lib|...} like on a standard RPI image.
I'm unsure how to proceed with the problem, diagnose it and fix it.
EDIT: maybe this are two different problems; I read the linked SO question once again and compared the files fixup.dat and start.elf (which contain the RPI hardware stuff to make the tools work) in the boot.vfat of the built image with the images in buildroot/output/build/rpi-firmware-d016a6eb01c8c7326a89cb42809fed2a21525de5/boot and the files fixup_x.dat and start_x.elf are taken from there. So is in accordance to the mentioned SO question. And at no place it is indicated that the tools for the Raspberry Pi are compiled. They are only inside this tar archive. Maybe one needs to compile them extra and this package is not designed to integrate those tools.
I figured out the solution and this might be useful for future reference, so I put the solution here.
One have to differentiate between:
the "firmware" (that is the mentioned tar from the question), which is turned on with BR2_PACKAGE_RPI_FIRMWARE=y in buildroot. This causes then that the start.elf and fixup.dat contain the correct data from this tar. The fact that the tars also contain the desired binaries is only "coincidence"
the desired applications are packaged as "userland" (see here) and if one finds the # BR2_PACKAGE_RPI_USERLAND is not set line in .config in the buildroot project's root directory and replaces this line by BR2_PACKAGE_RPI_USERLAND=y the applications (vcgencmd, raspistill, ...) are being built and included into the final image (I could not find the location in make menuconfig however, but this is no problem, if you directly modify the vars)
Therefore, the question is answered. But: you might run into some issues ;-) :
Question 1: I get a "Segmentation fault" when running raspistill
For raspistill -o i.jpg you might get out:
mmal: mmal_vc_shm_init: could not initialize vc shared memory service
mmal: mmal_vc_component_create: failed to initialise shm for 'vc.camera_info' (7:EIO)
mmal: mmal_component_create_core: could not create component 'vc.camera_info' (7)
mmal: Failed to create camera_info component
Segmentation fault
(with an empty image file), see here for details.
Answer: this is related to /dev/vcsm (or /dev/vcsm-csa) missing which is used for camera control / video decoding "stuff". Symlinking to /dev/vc-mem as stated somewhere around the net does not help.
Solution: I was using the latest BR with Kernel 5.10.x (buildroot-2021.02.1 and simply "dowgraded" to buildroot-2020.02.1, rebuilt it and /dev/vcsm appears and everything works fine.
Question 2: I want to do it in docker containers
Answer: No problem. I used balenalib/rpi-raspbian:latest (as suggested here) and it worked flawlessly by running docker run --privileged --device=/dev/vchiq --rm -it balenalib/rpi-raspbian:latest. For this only the proper devices and the support is needed. So the package BR2_PACKAGE_RPI_USERLAND=y could be completely omitted.
Question 3: Does it work with 64-bit?
Answer: No. I tried out the recent version (raspberrypi3_64_defconfig) of buildroot and the version from Feb 2020 as mentioned and for both /dev/vcsm (or /dev/vcsm-csa) is missing. Linux cpi64 4.19.97-v8 #1 SMP PREEMPT Sat Apr 17 14:13:11 CEST 2021 aarch64 GNU/Linux
I download some mexw64. type files with some Matlab .m files. I want to ask how can I open them and investigate the code and algorithm through them?
Is it possible to convert them to the .m file?
(the windows in my laptop is 64 bit)
Unfortunately not, unless you can contact the author of the MEX file.
MEX files are Matlab executable files. A MEX file is first written in C/C++/Fortran, and then compiled to a binary file with extension .mexw64 (Windows), .mexmaci64 (MacOS), or .mexa64 (Linux). The extension is chosen by the author, based on whether he/she intends the file to be used on Windows, Mac, or Linux.
See the documentation for more information, and the Matlab Q&A site for possible indirect solutions.
I'm using Yocto project to build a linux kernel image following these steps:
https://www.at91.com/linux4sam/bin/view/Linux4SAM/Sama5d27Som1EKMainPage
For some reasons I just want to reduce my Image size so I can flash it on QSPI 8 Mega octet memory. I have tried to reduce the size of my rootFS, I have removed some packages that I found in .manifest file and some Distro features. But I did not find how can I modify the kernel size which size is fixed ( 4.2 Mega octet ).
I think that when I can remove some drivers that I don't need the kernel size will be reduced.
I just want to know how can I find what drivers are built in my image and where can I find them ? and later how can I delete the ones that I don't need ?
Thank you.
if you check the .config file that was generated for your BSP, it will show what drivers (and other things) were built into your kernel (check for the 'y' on all the options).
Such file should be somewhere in:
tmp/work//linux-yocto//linux-*-build/.config
Sorry that I can't give you the exact location, but it literally depends on what BSP/MACHINE you are building for.
Also, if you want to modify such configuration, you can call:
$ bitbake -c menuconfig virtual/kernel
that will bring up the menuconfig ncurses interface, in which you can not only see what is installed but also modify what you need.
This question is related to another question I asked here:
Error reading image using jpeg_read from Matlab's jpeg toolbox
I've been trying to compile the jpeg toolbox under Windows 7 (using the commands Shai provided in the answer to the question I posted), but I get the following error:
jpeg_read.c(52) : fatal error C1083: Cannot open include file: 'jerror.h': No such file or directory
which I believe happened because I haven't built libjpeg. I tried to build libjpeg6b like jpegtoolbox's README says, but I couldn't find a clear guide on how to do it on Windows with visual studio 2010 (and libjpeg's install document doesn't help much), so I ended building libjpeg8d.
My question is if there's any way to use libjpeg8d to compile the jpeg toolbox. I've tried running the command:
mex -I<IJGPATH> jpeg_read.c <LIBJPEG>
with IJGPATH being my libjpeg8d installation folder and LIBJPEG being the path to the jpeg.lib file, inside IJGPATH/Release, but I still get the same missing jerror.h error as before.
Thanks in advance.
Jpeg toolbox contains Matlab routines for manipulating JPEG files. While Matlab's built-in IMREAD and IMWRITE functions provide basic conversion between JPEG files and image arrays, they do not provide access to the details of the JPEG image, such as the JPEG coefficients or the quantization tables.
The routines in this package provide additional functionality for directly accessing the contents of JPEG files from Matlab, including the Discrete Cosine Transform (DCT) coefficients, quantization tables, Huffman coding tables, color space information, and comment markers. The toolbox can be added to Matlab to use the functions.
First check whether the following are installed in your system.
1.Microsoft windows sdk7
2.Microsoft visual c++ 2010 express
if they are not installed, Download and install them in the order specified.
Note: Before installing windows sdk, uninstall any redistributalbe packages of visual c++ 2010. Else windows sdk produces problem during installation and the install fails. During installation dont forget to check the 'x64 Libraries' for 64bit OS and 'x86 Libraries' for 32bit OS, under Windows Headers and Libraries. This allows to use compiler tools for 64 bit operating systems. Once it overs, install visual c++. These tools are free and available at microsoft website. Both online and offline installers are available.
Now comes the real integration process
Step 1: Download the jpeg toolbox and extract it to a separate folder (eg. jpeg)
Download jpeg toolbox
Step 2: Download jpeg source files and extract it to a separate folder (eg.jpegsrc). In the folder jpeg-6b which is in jpegsrc, rename jconfig.vc to jconfig.h and makefile.vc to makefile
Download jpegsrc file
Step 3: From start->All programs-> Microsoft windows sdk , open the command prompt. This opens the 'windows x64 debug environment'. Navigate to the jpeg-6b folder which is inside the jpegsrc folder which is extracted at step 2. Run the command 'nmake clean all' without quotes. This creates the libjpeg.lib file in the same folder.
Step 4: Now open the matlab and choose the workfolder as jpeg, created in step 1.
Now in the command windows run the following commands,
mex -I jpeg_read.c
mex -I jpeg_write.c
Replace with the path to the IJG jpeg-6b directory created in step 2, and
with the full path to the IJG code library file (libjpeg.lib).
To use the jpeg_read and jpeg_write functions copy jpeg_read.mexw64 and jpeg_write.mexw64 files created above to your work directory. Dont uninstall visual c++ compiler or it wont work.
If you are trying to work in Windows, you need to rename jerror.vc to jerror.h
Also, when you mex the files, you need to edit the jpeg_read.c and jpeg_write.c from include to include "jerror.h"
Hey there,
I need to get started to Cuda in Matlab. As I need additional functions than provided from matlab, I need to write my own c++ code, e.g. I want to run my program on 1..N GPU-processors and compare the results to calculate the speedup, which is not supported by Matlab itself (as Matlab always optimizes itself to use all processors).
Now I wonder how to get started best. I already read a lot of papers, but I still wonder for example, what those files are all about:
.cu
.cubin
.ptx
.mex
So which way do I need to go? Writing my code to a .cu file and than compiling it (which tool to use?
My computer is:
Q9550 with GTX460,
Win7 x64,
Matlab R2010b x64,
Visual Express C++ 2008 (free -> 32bit version),
Cuda Toolkit 3.2 (64bit),
Latest Nvidia Driver and GPU Programming SDK 3.2.16_win_64
How to get on? When I try to open one of the examples out of the GPU Programming SDK, e.g. the file vectorAdd_vc90.vcproj ouf ot C:\ProgramData\NVIDIA Corporation\NVIDIA GPU Computing SDK 3.2\C\src\vectorAdd
I get
"The following XML parsing-error occured:
File: C:\ProgramData\NVIDIA Corporation\NVIDIA GPU Computing SDK 3.2\C\src\vectorAdd\vectorAdd_vc90.vcproj
Row: 22
Column: 4
Fehlermeldung:
The user build-file "C:\Program Files (x86)\Microsoft Visual Studio 9.0\VC\VCProjectDefaults\NvCudaRuntimeApi.rules" wasnt found or couldn't be loaded
The file "C:\ProgramData\NVIDIA Corporation\NVIDIA GPU Computing SDK 3.2\C\src\vectorAdd\vectorAdd_vc90.vcproj" couldn't be loaded"
When I just open the vectorAdd.cu I don't find any way to compile it to run it in Matlab. Perhaps it would also be possible to just work completely without Visual Studio, so that I write my code in Notepad++ for example and compile it myself?
Thanks a lot in advance guys!
If you have access to Parallel Computing Toolbox, you can use the GPU directly using GPUArrays. You can also more easily integrate your own hand-written CUDA code using the parallel.gpu.CUDAKernel object
If the parallel toolbox isn't available, you can still use the mexFunction capability to use the GPU's
http://www.mathworks.com.au/help/distcomp/create-and-run-mex-files-containing-cuda-code.html
I dont think this is available for earlier versions than 2013a. In this case, you can write the mexfunction entry point and include the cuda function calls to pass the memory to and from the device
http://developer.download.nvidia.com/compute/cuda/4_2/rel/toolkit/docs/online/