Voxl2 Docker (Ubuntu 22) with OpenCL/Adreno
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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(
--privilegedmode 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-icdMaybe we can figure out what lib is still missing so that
pocl-opencl-icddoes not have to be installed.. At least the issue was the a missing library, not a mapped deviceFor 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: 3I 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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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 -
hi @eric ,
Nice! very clean.
Did you use
dpkg-repackto create debs of installed packages, such as:apt-get install dpkg-repack dpkg-repack qti-adrenoCool trick!
I will test this out and add to our docs.
Alex
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@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!
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@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
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@Alex-Kushleyev Awesome! Thanks again for all your help with this!
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@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 -
@Peter-Milani , it looks like Qualcomm CPU device is not supported by OpenCL library from Qualcomm.
clinfomay be confused, but installing and runningclinfonatively on voxl2 does not return any platforms - the opencl libraries that may get installed byaptare most likely not compatible with the VOXL2 GPU.Alex
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@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 2.1but after installing:
apt install -y -qq pocl-opencl-icd; -
@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
