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    Voxl2 Docker (Ubuntu 22) with OpenCL/Adreno

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    • Eric KatzfeyE
      Eric Katzfey ModalAI Team @eric
      last edited by

      @eric Yes, I did put that together based on some Qualcomm example code for VOXL. Not really sure how to do something similar on VOXL 2 but I'll ask around the office to see if anyone has some ideas on how to get that going.

      E 1 Reply Last reply Reply Quote 1
      • E
        eric @Eric Katzfey
        last edited by

        @Eric-Katzfey Really appreciate it! Thanks so much

        Alex KushleyevA 1 Reply Last reply Reply Quote 0
        • Alex KushleyevA
          Alex Kushleyev ModalAI Team @eric
          last edited by

          @eric I will try it out, please give me a few days.

          Alex

          Alex KushleyevA 1 Reply Last reply Reply Quote 1
          • Alex KushleyevA
            Alex Kushleyev ModalAI Team @Alex Kushleyev
            last edited by

            Quick update, I did some testing and tried searching documentation and could not get it to work. There are posts online asking Qualcomm whether this is possible, but there is no response there.

            I know this would be a useful feature and I will try again next week. I want to see how this worked on VOXL1 and perhaps I am missing something.

            In my test, I am also just doing a simple device query and it works on the host VOXL2 but not inside docker, tried mapping various .so libraries and devices to the docker container and no luck yet.

            Alex

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              eric @Alex Kushleyev
              last edited by

              @Alex-Kushleyev That aligns pretty well with my own experience so far. Thanks again for looking into this!

              Alex KushleyevA 1 Reply Last reply Reply Quote 0
              • Alex KushleyevA
                Alex Kushleyev ModalAI Team @eric
                last edited by

                @eric I was able to get the GPU device query inside ubuntu 22.04 docker working using the following steps. It is possible that we can reduce the number of mapped devices and libraries to the docker container, but i am just going to give you this information right now so you can test. I will try to clean this up a bit later. I only tried the device query for now, but i figured i would let you know that there is progress..

                #run docker
                docker run -it --rm --privileged --device=/dev/kgsl-3d0 --device=/dev/ion -v /proc:/proc -v /firmware/image:/firmware/image -v /lib/firmware:/lib/firmware -v /sys/class:/sys/class -v /sys/bus:/sys/bus -v /sys/devices:/sys/devices -v /data:/data -v /usr/lib/liblog.so.0:/usr/lib/liblog.so.0 -v /usr/lib/libOpenCL.so:/usr/lib/libOpenCL.so -v /usr/lib/libcutils.so.0:/usr/lib/libcutils.so.0 -v /usr/lib/libllvm-qcom.so:/usr/lib/libllvm-qcom.so -v /usr/lib/libion.so.0.0.0:/usr/lib/libion.so.0.0.0 -v /usr/lib/libsync.so.0.0.0:/usr/lib/libsync.so.0.0.0 -v /usr/lib/libgsl.so:/usr/lib/libgsl.so -v /usr/lib/libCB.so:/usr/lib/libCB.so -v /usr/lib/aarch64-linux-gnu/libglib-2.0.so.0.5600.4:/usr/lib/aarch64-linux-gnu/libglib-2.0.so.0.5600.4 -v `pwd`:/opt/code -w /opt/code arm64v8/ubuntu:22.04 bash
                
                apt-get update
                apt install --no-install-recommends -y pocl-opencl-icd
                

                then run your test app to query the device..

                E 1 Reply Last reply Reply Quote 1
                • E
                  eric @Alex Kushleyev
                  last edited by

                  @Alex-Kushleyev 🙇

                  Alex KushleyevA 1 Reply Last reply Reply Quote 0
                  • Alex KushleyevA
                    Alex Kushleyev ModalAI Team @eric
                    last edited by Alex Kushleyev

                    OK, a little more clean-up, it seems this is the minimal set of libraries /devices needed:

                    docker run -it --rm --privileged \
                    	-v /usr/lib/libOpenCL.so:/usr/lib/libOpenCL.so \
                    	-v /usr/lib/libCB.so:/usr/lib/libCB.so \
                    	-v /usr/lib/libgsl.so:/usr/lib/libgsl.so \
                    	-v /usr/lib/liblog.so.0:/usr/lib/liblog.so.0 \
                    	-v /usr/lib/libcutils.so.0:/usr/lib/libcutils.so.0 \
                    	-v /usr/lib/libsync.so.0.0.0:/usr/lib/libsync.so.0.0.0 \
                    	-v /usr/lib/libion.so.0.0.0:/usr/lib/libion.so.0.0.0 \
                    	-v /usr/lib/libllvm-qcom.so:/usr/lib/libllvm-qcom.so \
                    	-v /usr/lib/aarch64-linux-gnu/libglib-2.0.so.0.5600.4:/usr/lib/aarch64-linux-gnu/libglib-2.0.so.0.5600.4 \
                    	-v `pwd`:/opt/code -w /opt/code \
                    	arm64v8/ubuntu:22.04 bash
                    

                    (--privileged mode maps all the needed devices to the docker container)

                    Then install some more packages (not sure if this can be reduced, not clear exactly what is missing):

                    apt-get update
                    apt install --no-install-recommends -y pocl-opencl-icd
                    

                    Maybe we can figure out what lib is still missing so that pocl-opencl-icd does not have to be installed.. At least the issue was the a missing library, not a mapped device

                    For testing, I used a device query script from here:

                    root@733a6d4d5fdb:/opt/code# ./simple_query 
                    1. Device: QUALCOMM Adreno(TM)
                     1.1 Hardware version: OpenCL 2.0 Adreno(TM) 650
                     1.2 Software version: OpenCL 2.0 QUALCOMM build: commit # changeid # Date: 11/10/21 Wed Local Branch:  Remote Branch:  Compiler E031.37.12.01
                     1.3 OpenCL C version: OpenCL C 2.0 Adreno(TM) 650
                     1.4 Parallel compute units: 3
                    

                    I also verified that a simple matrix multiplication app also worked (not provided here)

                    @eric , can you please let me know if this works for you?

                    Alex

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                    • E
                      eric @Alex Kushleyev
                      last edited by

                      @Alex-Kushleyev

                      OMG IT WORKS!!

                      I was able to extract all these libraries from the host and directly install them inside the docker, and now the pcol-opencl-icd installation isn't needed.

                      This is really important for us, since it allows us to build external dependencies that rely on OpenCL in our pipeline directly without bind mounts (outside the host environment).

                      Really, really appreciate all your help!

                      FROM arm64v8/ubuntu:22.04
                      
                      # Install necessary dependencies
                      RUN apt-get update && \
                          apt-get install -y \
                          cmake \
                          build-essential \
                          libglib2.0-0
                      
                      # Copy Adreno GPU dependencies
                      # - libcutils0_0-r1_arm64.deb
                      # - libsync_1.0-r1_arm64.deb
                      # - qti-libion_0-r1_arm64.deb
                      # - liblog0_1.0-r1_arm64.deb
                      # - qti-adreno_1.0-r0_arm64.deb
                      COPY dep /root/dep
                      
                      # Create required directory for qti-adreno install
                      RUN mkdir /usr/include/KHR && dpkg -i /root/dep/*.deb 
                      
                      # Copy and build test script
                      COPY ./hellocl /root/hellocl
                      RUN cd /root/hellocl && mkdir build && cd build && cmake .. && make
                      
                      CMD ["bash"]
                      
                      voxl2:~/opencl$ docker run -it --rm --privileged opencl:latest ./root/hellocl/build/hellocl
                      Platform Information:
                      Platform Name: QUALCOMM Snapdragon(TM)
                      Platform Vendor: QUALCOMM
                      Platform Version: OpenCL 2.0 QUALCOMM build: commit # changeid # Date: 11/10/21 Wed Local Branch:  Remote Branch: 
                      Platform Profile: FULL_PROFILE
                      Platform Extensions:  
                      ------------------------------------
                      Device Information:
                      Device Name: QUALCOMM Adreno(TM)
                      Device Vendor: QUALCOMM
                      Driver Version: OpenCL 2.0 QUALCOMM build: commit # changeid # Date: 11/10/21 Wed Local Branch:  Remote Branch:  Compiler E031.37.12.01
                      Device Version: OpenCL 2.0 Adreno(TM) 650
                      Device OpenCL C Version: OpenCL C 2.0 Adreno(TM) 650
                      Device Max Compute Units: 3
                      This should be three: 3
                      
                      Alex KushleyevA 1 Reply Last reply Reply Quote 0
                      • Alex KushleyevA
                        Alex Kushleyev ModalAI Team @eric
                        last edited by

                        hi @eric ,

                        Nice! very clean.

                        Did you use dpkg-repack to create debs of installed packages, such as:

                        apt-get install dpkg-repack
                        dpkg-repack qti-adreno
                        

                        Cool trick!

                        I will test this out and add to our docs.

                        Alex

                        E 1 Reply Last reply Reply Quote 0
                        • E
                          eric @Alex Kushleyev
                          last edited by eric

                          @Alex-Kushleyev Yes, dpkg -S <file path> to figure out which debs installed which libraries (ie, dpkg -S /usr/lib/libOpenCL.so), apt-cache show to see the source (ubuntu ppa vs modalai), then dpkg-repack to repack the modalai debs.

                          Thanks again!

                          Alex KushleyevA 1 Reply Last reply Reply Quote 0
                          • Alex KushleyevA
                            Alex Kushleyev ModalAI Team @eric
                            last edited by

                            @eric , thanks again for your input on this, i have posted a complete tutorial how to enable OpenCL in Docker on VOXL2 : https://docs.modalai.com/voxl-2-opencl-in-docker/

                            Alex

                            E 1 Reply Last reply Reply Quote 0
                            • E
                              eric @Alex Kushleyev
                              last edited by

                              @Alex-Kushleyev Awesome! Thanks again for all your help with this!

                              Peter MilaniP 1 Reply Last reply Reply Quote 0
                              • Peter MilaniP
                                Peter Milani @eric
                                last edited by

                                @Alex-Kushleyev @eric I've implemented your solution and get the same result.

                                I did get a bit confused as running clinfo only returned a single device of type CPU and without the name "Adreno".

                                However I added to your test script a query on the device_type and it returned GPU so I guess its only finding the GPU. I would have expected it to return a few more devices as the [Qualcomm OpenCL guide] (https://docs.qualcomm.com/bundle/publicresource/80-NB295-11_REV_C_Qualcomm_Snapdragon_Mobile_Platform_Opencl_General_Programming_and_Optimization.pdf) suggests that the dsp and CPU could have been returned as well, so I'm not sure what is happening there. I didn't have to link devices only shared the volumes to the relevant libraries. I would have expected the CPU to be returned a a matter of course as that is what happens with the intel implementation.

                                My additional lines to the script (given for info is):

                                  cl_device_type device_type;
                                  clGetDeviceInfo(devices[j], CL_DEVICE_TYPE, sizeof(cl_device_type), &device_type, NULL);
                                  printf("Device type: ");
                                  if (device_type & CL_DEVICE_TYPE_CPU)
                                      printf("CPU ");
                                  if (device_type & CL_DEVICE_TYPE_GPU)
                                      printf("GPU ");
                                  if (device_type & CL_DEVICE_TYPE_ACCELERATOR)
                                      printf("ACCELERATOR ");
                                  if (device_type & CL_DEVICE_TYPE_DEFAULT)
                                      printf("DEFAULT ");
                                  printf("\n");
                                
                                

                                Which returns

                                OpenCL platform count: 1
                                OpenCL device count: 1
                                1. Device: QUALCOMM Adreno(TM)
                                 1.1 Hardware version: OpenCL 2.0 Adreno(TM) 650
                                Device type: GPU 
                                 1.2 Software version: OpenCL 2.0 QUALCOMM build: commit # changeid # Date: 11/10/21 Wed Local Branch:  Remote Branch:  Compiler E031.37.12.01
                                 1.3 OpenCL C version: OpenCL C 2.0 Adreno(TM) 650
                                 1.4 Parallel compute units: 3
                                
                                
                                Alex KushleyevA 1 Reply Last reply Reply Quote 0
                                • Alex KushleyevA
                                  Alex Kushleyev ModalAI Team @Peter Milani
                                  last edited by

                                  @Peter-Milani , it looks like Qualcomm CPU device is not supported by OpenCL library from Qualcomm.

                                  clinfo may be confused, but installing and running clinfo natively on voxl2 does not return any platforms - the opencl libraries that may get installed by apt are most likely not compatible with the VOXL2 GPU.

                                  Alex

                                  Peter MilaniP 1 Reply Last reply Reply Quote 0
                                  • Peter MilaniP
                                    Peter Milani @Alex Kushleyev
                                    last edited by

                                    @Alex-Kushleyev I was able to get the following when running opencl within the docker instance:

                                     clinfo
                                    Number of platforms                               1
                                      Platform Name                                   Portable Computing Language
                                      Platform Vendor                                 The pocl project
                                      Platform Version                                OpenCL 1.2 pocl 1.4, None+Asserts, LLVM 9.0.1, RELOC, SLEEF, POCL_DEBUG
                                      Platform Profile                                FULL_PROFILE
                                      Platform Extensions                             cl_khr_icd
                                      Platform Extensions function suffix             POCL
                                    
                                      Platform Name                                   Portable Computing Language
                                    Number of devices                                 1
                                      Device Name                                     pthread-0x805
                                      Device Vendor                                   Qualcomm
                                      Device Vendor ID                                0x13b5
                                      Device Version                                  OpenCL 1.2 pocl HSTR: pthread-aarch64-unknown-linux-gnu-GENERIC
                                      Driver Version                                  1.4
                                      Device OpenCL C Version                         OpenCL C 1.2 pocl
                                      Device Type                                     CPU
                                      Device Profile                                  FULL_PROFILE
                                      Device Available                                Yes
                                      Compiler Available                              Yes
                                      Linker Available                                Yes
                                      Max compute units                               8
                                      Max clock frequency                             1804MHz
                                      Device Partition                                (core)
                                        Max number of sub-devices                     8
                                        Supported partition types                     equally, by counts
                                        Supported affinity domains                    (n/a)
                                      Max work item dimensions                        3
                                      Max work item sizes                             4096x4096x4096
                                      Max work group size                             4096
                                      Preferred work group size multiple              8
                                      Preferred / native vector sizes                 
                                        char                                                16 / 16      
                                        short                                                8 / 8       
                                        int                                                  4 / 4       
                                        long                                                 2 / 2       
                                        half                                                 0 / 0        (n/a)
                                        float                                                4 / 4       
                                        double                                               2 / 2        (cl_khr_fp64)
                                      Half-precision Floating-point support           (n/a)
                                      Single-precision Floating-point support         (core)
                                        Denormals                                     No
                                        Infinity and NANs                             Yes
                                        Round to nearest                              Yes
                                        Round to zero                                 No
                                        Round to infinity                             No
                                        IEEE754-2008 fused multiply-add               No
                                        Support is emulated in software               No
                                        Correctly-rounded divide and sqrt operations  No
                                      Double-precision Floating-point support         (cl_khr_fp64)
                                        Denormals                                     Yes
                                        Infinity and NANs                             Yes
                                        Round to nearest                              Yes
                                        Round to zero                                 Yes
                                        Round to infinity                             Yes
                                        IEEE754-2008 fused multiply-add               Yes
                                        Support is emulated in software               No
                                      Address bits                                    64, Little-Endian
                                      Global memory size                              5896568832 (5.492GiB)
                                      Error Correction support                        No
                                      Max memory allocation                           2147483648 (2GiB)
                                      Unified memory for Host and Device              Yes
                                      Minimum alignment for any data type             128 bytes
                                      Alignment of base address                       1024 bits (128 bytes)
                                      Global Memory cache type                        None
                                      Image support                                   Yes
                                        Max number of samplers per kernel             16
                                        Max size for 1D images from buffer            134217728 pixels
                                        Max 1D or 2D image array size                 2048 images
                                        Max 2D image size                             8192x8192 pixels
                                        Max 3D image size                             2048x2048x2048 pixels
                                        Max number of read image args                 128
                                        Max number of write image args                128
                                      Local memory type                               Global
                                      Local memory size                               33554432 (32MiB)
                                      Max number of constant args                     8
                                      Max constant buffer size                        33554432 (32MiB)
                                      Max size of kernel argument                     1024
                                      Queue properties                                
                                        Out-of-order execution                        Yes
                                        Profiling                                     Yes
                                      Prefer user sync for interop                    Yes
                                      Profiling timer resolution                      1ns
                                      Execution capabilities                          
                                        Run OpenCL kernels                            Yes
                                        Run native kernels                            Yes
                                      printf() buffer size                            16777216 (16MiB)
                                      Built-in kernels                                (n/a)
                                      Device Extensions                               cl_khr_byte_addressable_store cl_khr_global_int32_base_atomics cl_khr_global_int32_extended_atomics cl_khr_local_int32_base_atomics cl_khr_local_int32_extended_atomics cl_khr_3d_image_writes cl_khr_fp64
                                    
                                    NULL platform behavior
                                      clGetPlatformInfo(NULL, CL_PLATFORM_NAME, ...)  Portable Computing Language
                                      clGetDeviceIDs(NULL, CL_DEVICE_TYPE_ALL, ...)   Success [POCL]
                                      clCreateContext(NULL, ...) [default]            Success [POCL]
                                      clCreateContextFromType(NULL, CL_DEVICE_TYPE_DEFAULT)  Success (1)
                                        Platform Name                                 Portable Computing Language
                                        Device Name                                   pthread-0x805
                                      clCreateContextFromType(NULL, CL_DEVICE_TYPE_CPU)  Success (1)
                                        Platform Name                                 Portable Computing Language
                                        Device Name                                   pthread-0x805
                                      clCreateContextFromType(NULL, CL_DEVICE_TYPE_GPU)  No devices found in platform
                                      clCreateContextFromType(NULL, CL_DEVICE_TYPE_ACCELERATOR)  No devices found in platform
                                      clCreateContextFromType(NULL, CL_DEVICE_TYPE_CUSTOM)  No devices found in platform
                                      clCreateContextFromType(NULL, CL_DEVICE_TYPE_ALL)  Success (1)
                                        Platform Name                                 Portable Computing Language
                                        Device Name                                   pthread-0x805
                                    
                                    ICD loader properties
                                      ICD loader Name                                 OpenCL ICD Loader
                                      ICD loader Vendor                               OCL Icd free software
                                      ICD loader Version                              2.2.11
                                      ICD loader Profile                              OpenCL 2.1
                                    
                                    

                                    but after installing:

                                    apt install -y -qq pocl-opencl-icd;
                                    
                                    Alex KushleyevA 1 Reply Last reply Reply Quote 0
                                    • Alex KushleyevA
                                      Alex Kushleyev ModalAI Team @Peter Milani
                                      last edited by

                                      @Peter-Milani , I see. this looks like a generic implementation of OpenCL for ARM from 3rd party (not Qualcomm), and i think it also overwrites the proprietary opencl libraries, disabling the GPU opencl support. However, you could make two separate docker images, one for each use case (cpu and gpu)

                                      Alex

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