cudev: Add __shfl_down implementation for long long and unsigned long for CUDA Tookit < 9.0

[cudawarped]

Draft fix for #3962.

Support for __shfl_down on long long was not introduced until CUDA Toolkit 9.0. I don't know if this is just software support or if hardware support was added as well. Its a long shot but it may be the reason that the tests are failing on Compute Capbability 5.3 devices.

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[troelsy]

Hi, I thought I would chime in as it relates to my recent PR. The company I work for uses Jetson TX2 with CC=6.2, CUDA Toolkit 10.2 and everything seems to work, so I took a look at it. It looks like all devices that support warp shuffle (CC≥3.0) will support shuffle with long long as long as the CUDA Toolkit ≥ 9.0.

To the question about if it is implemented in software or hardware, I think warp shuffle are always done 32 bit at a time because the registers are limited to 32 bit. It will just be two shuffles for 64 bit types. The PTX also indicate this in Compiler Explorer: https://godbolt.org/z/nxdYcqoWe. If the PTX view doesn't show, try opening a new compiler window.

I think the if-statement should be changed to check the CUDA Toolkit version instead. The current code will change the behavior on Jetson TX2 even though it should be supported. Does OpenCV specify a minimum version of CUDA Toolkit?

[cudawarped]

@troelsy The flag was just a test to try and fix the crash on CC 5.3 devices. Do you have access to CUDA toolkit < 9.0 to test whether _shufl_down compiles or not on CUDA toolkit < 9.0? Godbolt doesn't have NVCC <= 9.1.85.

[troelsy]

TX2 should be able to run CUDA Toolkit 8.0, but my department doesn't have access to the firmware, so I can't try it out

[cudawarped]

@asmorkalov Do you have a machine with CUDA Toolkit < 9.0 on it to check this?

[asmorkalov]

No, unfortunately. I want to deploy something with desktop PC, but after the 4.12 release. It's almost ready.

[cudawarped]

Would you like me to kill this PR or change the #define from __CUDA_ARCH__ < 700 to __CUDACC_VER_MAJOR__ < 9?

[asmorkalov]

@cudawarped Is it ready for merge?

[cudawarped]

@asmorkalov 👍