1 | initial version |
On windows yes. I just compiled a debug version with ninja and Visual Studio 2019 and confirmed its working by running
"%openCvBuild%\install\x64\vc15\bin\opencv_perf_cudaarithm.exe" --gtest_filter=Sz_Type_Flags_GEMM.GEMM/29
from this guide for building 4.1.0 with the following output
[----------]
[ INFO ] Implementation variant: cuda.
[----------]
[----------]
[ GPU INFO ] Run test suite on GeForce RTX 2080 GPU.
[----------]
Time compensation is 0
[----------]
[ GPU INFO ] Run on OS Windows x64.
[----------]
*** CUDA Device Query (Runtime API) version (CUDART static linking) ***
Device count: 1
Device 0: "GeForce RTX 2080"
CUDA Driver Version / Runtime Version 10.20 / 10.20
CUDA Capability Major/Minor version number: 7.5
Total amount of global memory: 8192 MBytes (8589934592 bytes)
GPU Clock Speed: 1.59 GHz
...
deviceQuery, CUDA Driver = CUDART, CUDA Driver Version = 10.20, CUDA Runtime Version = 10.20, NumDevs = 1
TEST: Skip tests with tags: 'mem_6gb', 'verylong', 'debug_verylong'
CTEST_FULL_OUTPUT
OpenCV version: 4.2.0-dev
OpenCV VCS version: 4.2.0-1-g89d3f95a8e
Build type: Debug
Compiler: C:/Program Files (x86)/Microsoft Visual Studio/2019/Community/VC/Tools/MSVC/14.23.28105/bin/Hostx64/x64/cl.exe (ver 19.23.28106.4)
Parallel framework: tbb
CPU features: SSE SSE2 SSE3 *SSE4.1 *SSE4.2 *FP16 *AVX *AVX2 *AVX512-SKX?
Intel(R) IPP version: ippIP AVX2 (l9) 2019.0.0 Gold (-) Jul 26 2018
....
Note: Google Test filter = Sz_Type_Flags_GEMM.GEMM/29
[==========] Running 1 test from 1 test case.
[----------] Global test environment set-up.
[----------] 1 test from Sz_Type_Flags_GEMM
[ RUN ] Sz_Type_Flags_GEMM.GEMM/29, where GetParam() = (1024x1024, 32FC2, 0|cv::GEMM_1_T)
[ PERFSTAT ] (samples=13 mean=2.03 median=2.03 min=1.95 stddev=0.04 (2.0%))
[ OK ] Sz_Type_Flags_GEMM.GEMM/29 (409 ms)
[----------] 1 test from Sz_Type_Flags_GEMM (411 ms total)
[----------] Global test environment tear-down
[==========] 1 test from 1 test case ran. (415 ms total)
[ PASSED ] 1 test.
2 | No.2 Revision |
On windows yes. I just compiled a debug version with ninja and Visual Studio 2019 and confirmed its working by running
"%openCvBuild%\install\x64\vc15\bin\opencv_perf_cudaarithm.exe" "%openCvBuild%\install\x64\vc16\bin\opencv_perf_cudaarithm.exe" --gtest_filter=Sz_Type_Flags_GEMM.GEMM/29
from this guide for building 4.1.0 4.2.0 with the following output
[----------]
[ INFO ] Implementation variant: cuda.
[----------]
[----------]
[ GPU INFO ] Run test suite on GeForce RTX 2080 GPU.
[----------]
Time compensation is 0
[----------]
[ GPU INFO ] Run on OS Windows x64.
[----------]
*** CUDA Device Query (Runtime API) version (CUDART static linking) ***
Device count: 1
Device 0: "GeForce RTX 2080"
CUDA Driver Version / Runtime Version 10.20 / 10.20
CUDA Capability Major/Minor version number: 7.5
Total amount of global memory: 8192 MBytes (8589934592 bytes)
GPU Clock Speed: 1.59 GHz
...
deviceQuery, CUDA Driver = CUDART, CUDA Driver Version = 10.20, CUDA Runtime Version = 10.20, NumDevs = 1
TEST: Skip tests with tags: 'mem_6gb', 'verylong', 'debug_verylong'
CTEST_FULL_OUTPUT
OpenCV version: 4.2.0-dev
OpenCV VCS version: 4.2.0-1-g89d3f95a8e
Build type: Debug
Compiler: C:/Program Files (x86)/Microsoft Visual Studio/2019/Community/VC/Tools/MSVC/14.23.28105/bin/Hostx64/x64/cl.exe (ver 19.23.28106.4)
Parallel framework: tbb
CPU features: SSE SSE2 SSE3 *SSE4.1 *SSE4.2 *FP16 *AVX *AVX2 *AVX512-SKX?
Intel(R) IPP version: ippIP AVX2 (l9) 2019.0.0 Gold (-) Jul 26 2018
....
Note: Google Test filter = Sz_Type_Flags_GEMM.GEMM/29
[==========] Running 1 test from 1 test case.
[----------] Global test environment set-up.
[----------] 1 test from Sz_Type_Flags_GEMM
[ RUN ] Sz_Type_Flags_GEMM.GEMM/29, where GetParam() = (1024x1024, 32FC2, 0|cv::GEMM_1_T)
[ PERFSTAT ] (samples=13 mean=2.03 median=2.03 min=1.95 stddev=0.04 (2.0%))
[ OK ] Sz_Type_Flags_GEMM.GEMM/29 (409 ms)
[----------] 1 test from Sz_Type_Flags_GEMM (411 ms total)
[----------] Global test environment tear-down
[==========] 1 test from 1 test case ran. (415 ms total)
[ PASSED ] 1 test.