Roux
Reputation: 57
Using OpenCV with OpenCL on Intel UHD Graphics 630 along with nvidia GPU
I currently have a program running all the time using my Nvidia GPU. I would like to run another one aside, which would use OpenCV with OpenCL. I use Ubuntu 18.04 and my processor is an Intel i7-9750H (with UHD Graphics 630).
I run this C++ code to detect the available devices:
#include <opencv4/opencv2/opencv.hpp>
#include <opencv4/opencv2/core/ocl.hpp>
int main()
{
cv::ocl::setUseOpenCL(true);
if (!cv::ocl::haveOpenCL())
{
std::cout << "OpenCL is not available..." << std::endl;
//return;
}
cv::ocl::Context context;
if (!context.create(cv::ocl::Device::TYPE_ALL))
{
std::cout << "Failed creating the context..." << std::endl;
//return;
}
std::cout << context.ndevices() << " GPU devices are detected." << std::endl; //This bit provides an overview of the OpenCL devices you have in your computer
for (int i = 0; i < context.ndevices(); i++)
{
cv::ocl::Device device = context.device(i);
std::cout << "name: " << device.name() << std::endl;
std::cout << "available: " << device.available() << std::endl;
std::cout << "imageSupport: " << device.imageSupport() << std::endl;
std::cout << "OpenCL_C_Version: " << device.OpenCL_C_Version() << std::endl;
std::cout << std::endl;
}
return 0;
}
When I run this code, I get the following output:
1 GPU devices are detected.
name: GeForce RTX 2060
available: 1
imageSupport: 1
OpenCL_C_Version: OpenCL C 1.2
So the issue is that my integrated intel GPU isn't detected.
I installed ocl-icd-opencl-dev and "Compute runtime" (NEO) : https://github.com/intel/compute-runtime but it didn't change anything.
Here's the ouput of clinfo:
Number of platforms 3
Platform Name NVIDIA CUDA
Platform Vendor NVIDIA Corporation
Platform Version OpenCL 1.2 CUDA 11.0.228
Platform Profile FULL_PROFILE
Platform Extensions 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_fp64 cl_khr_byte_addressable_store cl_khr_icd cl_khr_gl_sharing cl_nv_compiler_options cl_nv_device_attribute_query cl_nv_pragma_unroll cl_nv_copy_opts cl_nv_create_buffer cl_khr_int64_base_atomics cl_khr_int64_extended_atomics
Platform Extensions function suffix NV
Platform Name Intel(R) OpenCL HD Graphics
Platform Vendor Intel(R) Corporation
Platform Version OpenCL 3.0
Platform Profile FULL_PROFILE
Platform Extensions cl_khr_byte_addressable_store cl_khr_fp16 cl_khr_global_int32_base_atomics cl_khr_global_int32_extended_atomics cl_khr_icd cl_khr_local_int32_base_atomics cl_khr_local_int32_extended_atomics cl_intel_subgroups cl_intel_required_subgroup_size cl_intel_subgroups_short cl_khr_spir cl_intel_accelerator cl_intel_driver_diagnostics cl_khr_priority_hints cl_khr_throttle_hints cl_khr_create_command_queue cl_intel_subgroups_char cl_intel_subgroups_long cl_khr_il_program cl_intel_mem_force_host_memory cl_khr_subgroup_extended_types cl_khr_subgroup_non_uniform_vote cl_khr_subgroup_ballot cl_khr_subgroup_non_uniform_arithmetic cl_khr_subgroup_shuffle cl_khr_subgroup_shuffle_relative cl_khr_subgroup_clustered_reduce cl_khr_fp64 cl_khr_subgroups cl_intel_spirv_device_side_avc_motion_estimation cl_intel_spirv_media_block_io cl_intel_spirv_subgroups cl_khr_spirv_no_integer_wrap_decoration cl_intel_unified_shared_memory_preview cl_khr_mipmap_image cl_khr_mipmap_image_writes cl_intel_planar_yuv cl_intel_packed_yuv cl_intel_motion_estimation cl_intel_device_side_avc_motion_estimation cl_intel_advanced_motion_estimation cl_khr_int64_base_atomics cl_khr_int64_extended_atomics cl_khr_image2d_from_buffer cl_khr_depth_images cl_intel_media_block_io cl_khr_3d_image_writes cl_intel_va_api_media_sharing
Platform Host timer resolution 1ns
Platform Extensions function suffix INTEL
Platform Name Intel(R) CPU Runtime for OpenCL(TM) Applications
Platform Vendor Intel(R) Corporation
Platform Version OpenCL 2.1 LINUX
Platform Profile FULL_PROFILE
Platform Extensions cl_khr_icd 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_byte_addressable_store cl_khr_depth_images cl_khr_3d_image_writes cl_intel_exec_by_local_thread cl_khr_spir cl_khr_fp64 cl_khr_image2d_from_buffer cl_intel_vec_len_hint
Platform Host timer resolution 1ns
Platform Extensions function suffix INTEL
Platform Name NVIDIA CUDA
Number of devices 1
Device Name GeForce RTX 2060
Device Vendor NVIDIA Corporation
Device Vendor ID 0x10de
Device Version OpenCL 1.2 CUDA
Driver Version 450.80.02
Device OpenCL C Version OpenCL C 1.2
Device Type GPU
Device Topology (NV) PCI-E, 01:00.0
Device Profile FULL_PROFILE
Device Available Yes
Compiler Available Yes
Linker Available Yes
Max compute units 30
Max clock frequency 1200MHz
Compute Capability (NV) 7.5
Device Partition (core)
Max number of sub-devices 1
Supported partition types None
Max work item dimensions 3
Max work item sizes 1024x1024x64
Max work group size 1024
Preferred work group size multiple 32
Warp size (NV) 32
Preferred / native vector sizes
char 1 / 1
short 1 / 1
int 1 / 1
long 1 / 1
half 0 / 0 (n/a)
float 1 / 1
double 1 / 1 (cl_khr_fp64)
Half-precision Floating-point support (n/a)
Single-precision Floating-point support (core)
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
Correctly-rounded divide and sqrt operations Yes
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 6222839808 (5.795GiB)
Error Correction support No
Max memory allocation 1555709952 (1.449GiB)
Unified memory for Host and Device No
Integrated memory (NV) No
Minimum alignment for any data type 128 bytes
Alignment of base address 4096 bits (512 bytes)
Global Memory cache type Read/Write
Global Memory cache size 983040 (960KiB)
Global Memory cache line size 128 bytes
Image support Yes
Max number of samplers per kernel 32
Max size for 1D images from buffer 268435456 pixels
Max 1D or 2D image array size 2048 images
Max 2D image size 32768x32768 pixels
Max 3D image size 16384x16384x16384 pixels
Max number of read image args 256
Max number of write image args 32
Local memory type Local
Local memory size 49152 (48KiB)
Registers per block (NV) 65536
Max number of constant args 9
Max constant buffer size 65536 (64KiB)
Max size of kernel argument 4352 (4.25KiB)
Queue properties
Out-of-order execution Yes
Profiling Yes
Prefer user sync for interop No
Profiling timer resolution 1000ns
Execution capabilities
Run OpenCL kernels Yes
Run native kernels No
Kernel execution timeout (NV) Yes
Concurrent copy and kernel execution (NV) Yes
Number of async copy engines 3
printf() buffer size 1048576 (1024KiB)
Built-in kernels
Device Extensions 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_fp64 cl_khr_byte_addressable_store cl_khr_icd cl_khr_gl_sharing cl_nv_compiler_options cl_nv_device_attribute_query cl_nv_pragma_unroll cl_nv_copy_opts cl_nv_create_buffer cl_khr_int64_base_atomics cl_khr_int64_extended_atomics
Platform Name Intel(R) OpenCL HD Graphics
Number of devices 1
Device Name Intel(R) Gen9 HD Graphics NEO
Device Vendor Intel(R) Corporation
Device Vendor ID 0x8086
Device Version OpenCL 3.0 NEO
Driver Version 20.41.18123
Device OpenCL C Version OpenCL C 3.0
Device Type GPU
Device Profile FULL_PROFILE
Device Available Yes
Compiler Available Yes
Linker Available Yes
Max compute units 24
Max clock frequency 1150MHz
Device Partition (core)
Max number of sub-devices 0
Supported partition types None
Max work item dimensions 3
Max work item sizes 256x256x256
Max work group size 256
Preferred work group size multiple 32
Max sub-groups per work group 32
Sub-group sizes (Intel) 8, 16, 32
Preferred / native vector sizes
char 16 / 16
short 8 / 8
int 4 / 4
long 1 / 1
half 8 / 8 (cl_khr_fp16)
float 1 / 1
double 1 / 1 (cl_khr_fp64)
Half-precision Floating-point support (cl_khr_fp16)
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
Single-precision Floating-point support (core)
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
Correctly-rounded divide and sqrt operations Yes
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 20044763136 (18.67GiB)
Error Correction support No
Max memory allocation 4294959104 (4GiB)
Unified memory for Host and Device Yes
Shared Virtual Memory (SVM) capabilities (core)
Coarse-grained buffer sharing Yes
Fine-grained buffer sharing No
Fine-grained system sharing No
Atomics No
Minimum alignment for any data type 128 bytes
Alignment of base address 1024 bits (128 bytes)
Preferred alignment for atomics
SVM 64 bytes
Global 64 bytes
Local 64 bytes
Max size for global variable 65536 (64KiB)
Preferred total size of global vars 4294959104 (4GiB)
Global Memory cache type Read/Write
Global Memory cache size 524288 (512KiB)
Global Memory cache line size 64 bytes
Image support Yes
Max number of samplers per kernel 16
Max size for 1D images from buffer 268434944 pixels
Max 1D or 2D image array size 2048 images
Base address alignment for 2D image buffers 4 bytes
Pitch alignment for 2D image buffers 4 pixels
Max 2D image size 16384x16384 pixels
Max planar YUV image size 16384x16352 pixels
Max 3D image size 16384x16384x2048 pixels
Max number of read image args 128
Max number of write image args 128
Max number of read/write image args 128
Max number of pipe args 16
Max active pipe reservations 1
Max pipe packet size 1024
Local memory type Local
Local memory size 65536 (64KiB)
Max number of constant args 8
Max constant buffer size 4294959104 (4GiB)
Max size of kernel argument 2048 (2KiB)
Queue properties (on host)
Out-of-order execution Yes
Profiling Yes
Queue properties (on device)
Out-of-order execution Yes
Profiling Yes
Preferred size 131072 (128KiB)
Max size 67108864 (64MiB)
Max queues on device 1
Max events on device 1024
Prefer user sync for interop Yes
Profiling timer resolution 83ns
Execution capabilities
Run OpenCL kernels Yes
Run native kernels No
Sub-group independent forward progress Yes
IL version SPIR-V_1.2
SPIR versions 1.2
printf() buffer size 4194304 (4MiB)
Built-in kernels block_motion_estimate_intel;block_advanced_motion_estimate_check_intel;block_advanced_motion_estimate_bidirectional_check_intel;
Motion Estimation accelerator version (Intel) 2
Device-side AVC Motion Estimation version 1
Supports texture sampler use Yes
Supports preemption No
Device Extensions cl_khr_byte_addressable_store cl_khr_fp16 cl_khr_global_int32_base_atomics cl_khr_global_int32_extended_atomics cl_khr_icd cl_khr_local_int32_base_atomics cl_khr_local_int32_extended_atomics cl_intel_subgroups cl_intel_required_subgroup_size cl_intel_subgroups_short cl_khr_spir cl_intel_accelerator cl_intel_driver_diagnostics cl_khr_priority_hints cl_khr_throttle_hints cl_khr_create_command_queue cl_intel_subgroups_char cl_intel_subgroups_long cl_khr_il_program cl_intel_mem_force_host_memory cl_khr_subgroup_extended_types cl_khr_subgroup_non_uniform_vote cl_khr_subgroup_ballot cl_khr_subgroup_non_uniform_arithmetic cl_khr_subgroup_shuffle cl_khr_subgroup_shuffle_relative cl_khr_subgroup_clustered_reduce cl_khr_fp64 cl_khr_subgroups cl_intel_spirv_device_side_avc_motion_estimation cl_intel_spirv_media_block_io cl_intel_spirv_subgroups cl_khr_spirv_no_integer_wrap_decoration cl_intel_unified_shared_memory_preview cl_khr_mipmap_image cl_khr_mipmap_image_writes cl_intel_planar_yuv cl_intel_packed_yuv cl_intel_motion_estimation cl_intel_device_side_avc_motion_estimation cl_intel_advanced_motion_estimation cl_khr_int64_base_atomics cl_khr_int64_extended_atomics cl_khr_image2d_from_buffer cl_khr_depth_images cl_intel_media_block_io cl_khr_3d_image_writes cl_intel_va_api_media_sharing
Platform Name Intel(R) CPU Runtime for OpenCL(TM) Applications
Number of devices 1
Device Name Intel(R) Core(TM) i7-9750H CPU @ 2.60GHz
Device Vendor Intel(R) Corporation
Device Vendor ID 0x8086
Device Version OpenCL 2.1 (Build 0)
Driver Version 18.1.0.0920
Device OpenCL C Version OpenCL C 2.0
Device Type CPU
Device Profile FULL_PROFILE
Device Available Yes
Compiler Available Yes
Linker Available Yes
Max compute units 12
Max clock frequency 2600MHz
Device Partition (core)
Max number of sub-devices 12
Supported partition types by counts, equally, by names (Intel)
Max work item dimensions 3
Max work item sizes 8192x8192x8192
Max work group size 8192
Preferred work group size multiple 128
Max sub-groups per work group 1
Preferred / native vector sizes
char 1 / 32
short 1 / 16
int 1 / 8
long 1 / 4
half 0 / 0 (n/a)
float 1 / 8
double 1 / 4 (cl_khr_fp64)
Half-precision Floating-point support (n/a)
Single-precision Floating-point support (core)
Denormals Yes
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 25055956992 (23.34GiB)
Error Correction support No
Max memory allocation 6263989248 (5.834GiB)
Unified memory for Host and Device Yes
Shared Virtual Memory (SVM) capabilities (core)
Coarse-grained buffer sharing Yes
Fine-grained buffer sharing Yes
Fine-grained system sharing Yes
Atomics Yes
Minimum alignment for any data type 128 bytes
Alignment of base address 1024 bits (128 bytes)
Preferred alignment for atomics
SVM 64 bytes
Global 64 bytes
Local 0 bytes
Max size for global variable 65536 (64KiB)
Preferred total size of global vars 65536 (64KiB)
Global Memory cache type Read/Write
Global Memory cache size 262144 (256KiB)
Global Memory cache line size 64 bytes
Image support Yes
Max number of samplers per kernel 480
Max size for 1D images from buffer 391499328 pixels
Max 1D or 2D image array size 2048 images
Base address alignment for 2D image buffers 64 bytes
Pitch alignment for 2D image buffers 64 pixels
Max 2D image size 16384x16384 pixels
Max 3D image size 2048x2048x2048 pixels
Max number of read image args 480
Max number of write image args 480
Max number of read/write image args 480
Max number of pipe args 16
Max active pipe reservations 21845
Max pipe packet size 1024
Local memory type Global
Local memory size 32768 (32KiB)
Max number of constant args 480
Max constant buffer size 131072 (128KiB)
Max size of kernel argument 3840 (3.75KiB)
Queue properties (on host)
Out-of-order execution Yes
Profiling Yes
Local thread execution (Intel) Yes
Queue properties (on device)
Out-of-order execution Yes
Profiling Yes
Preferred size 4294967295 (4GiB)
Max size 4294967295 (4GiB)
Max queues on device 4294967295
Max events on device 4294967295
Prefer user sync for interop No
Profiling timer resolution 1ns
Execution capabilities
Run OpenCL kernels Yes
Run native kernels Yes
Sub-group independent forward progress No
IL version SPIR-V_1.0
SPIR versions 1.2
printf() buffer size 1048576 (1024KiB)
Built-in kernels
Device Extensions cl_khr_icd 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_byte_addressable_store cl_khr_depth_images cl_khr_3d_image_writes cl_intel_exec_by_local_thread cl_khr_spir cl_khr_fp64 cl_khr_image2d_from_buffer cl_intel_vec_len_hint
NULL platform behavior
clGetPlatformInfo(NULL, CL_PLATFORM_NAME, ...) No platform
clGetDeviceIDs(NULL, CL_DEVICE_TYPE_ALL, ...) No platform
clCreateContext(NULL, ...) [default] No platform
clCreateContext(NULL, ...) [other] Success [NV]
clCreateContextFromType(NULL, CL_DEVICE_TYPE_DEFAULT) No platform
clCreateContextFromType(NULL, CL_DEVICE_TYPE_CPU) No devices found in platform
clCreateContextFromType(NULL, CL_DEVICE_TYPE_GPU) No platform
clCreateContextFromType(NULL, CL_DEVICE_TYPE_ACCELERATOR) No devices found in platform
clCreateContextFromType(NULL, CL_DEVICE_TYPE_CUSTOM) Invalid device type for platform
clCreateContextFromType(NULL, CL_DEVICE_TYPE_ALL) No platform
NOTE: your OpenCL library only supports OpenCL 2.0,
but some installed platforms support OpenCL 3.0.
Programs using 3.0 features may crash
or behave unexepectedly
I guess my question is:
- Is it possible to run one code on my Nvidia GPU and another one on my Intel UHD Graphics ?
- If it is, why can't I see Intel UHD Graphics in my C++ code's output ?
Upvotes: 2
Views: 7884
Answers (2)
jack4388
Reputation: 21
I also try some ways...I find out that we should first build opencv with the intel opencl support(the nvidia opencl support is included when build with cuda),so we have to install the intel opencl sdk.Then set an envionment variable OPENCV_OPENCL_DEVICE=Intel:GPU:1(for dual GPU platform like laptop,0 usually stand for the discrete GPU and 1 stand for the Integrated GPU).The envionment variable layout is like:
// Layout: <Platform>:<CPU|GPU|ACCELERATOR|nothing=GPU/CPU>:<deviceName>
// Sample: AMD:GPU:
// Sample: AMD:GPU:Tahiti
// Sample: :GPU|CPU: = '' = ':' = '::'
From modules\core\src\ocl.cpp function:parseOpenCLDeviceConfiguration
Upvotes: 0
noma
Reputation: 1229
This is a somewhat messy situation. There is a difference between using multiple OpenCL devices from a single platform and different platforms.
Question 2: Each OpenCL implementation/SDK/Runtime you install will show up as a platform. The context class of OpenCV is bound to a single platform and can only work with the corresponding devices. The constructor only allows to specify a device type, so it probably queries OpenCL and uses the first platform with that device type (or just the first). That's why OpenCV only shows the Nvidia device.
Question 1: Creating another context reflecting the Intel platform would be possible by using the OpenCL API directly and then calling OpenCV's fromHandle() or fromDevice() functions to create the OpenCV Context object (the clinfo source is an example for the required code). But, using different platforms means linking to different OpenCL libraries (indirectly at runtime through the compile-time linked libOpenCL). I.e. memory objects, etc. cannot be shared between the different contexts, so practical usability is rather limited unless you have independent problems that you'd like to compute in parallel on both devices.
Bonus:
Your clinfo output shows 3 platforms (Nvidia OpenCL 1.2, Intel GPU OpenCL 3.0, Intel CPU OpenCL 2.1), and you see the warning:
NOTE: your OpenCL library only supports OpenCL 2.0,
but some installed platforms support OpenCL 3.0.
Programs using 3.0 features may crash
or behave unexepectedly
With 3 OpenCL implementations installed, you will end up with one /usr/lib/libOpenCL.so in your system, while every implementation installed this file, possibly overwriting an existing one. So you end up with the one of the last installed OpenCL implementation, which is not necessarily a problem, but can be with the 3 different major versions. The libOpenCL.so is just a shallow loader (ICD loader in OpenCL terms) that looks into /etc/OpenCL/vendors where there is a *.icd (installable client driver) file for every installed OpenCL implementation. These are simple text files containing the actual OpenCL library (i.e. platform) of a certain vendor, which will be loaded at runtime.
You are probably using the libOpenCL.so for the Intel GPU SDK which has OpenCL 3.0 support. Depending on the libOpenCL.so, or loader, you end up using, the platform order might be different, and you could end up having a different platform/device in your application. If you wanted to force your application to use another platform without fiddling with the OpenCL API directly, you could also work around the loader at link time, by not linking against /usr/lib/libOpenCL.so, but the library listed in the *.icd* file directly. An application linked like that will only show that one corresponding platform and its devices. So by directly linking to the Intel GPU library, your application will use that one instead of the Nvidia GPU. The binary won't be suited for packaging though.
Upvotes: 2
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