ARROW-17421: [C++] CUDA on Windows fails to build

[assignUser]

No description provided.

[assignUser]

@pitrou This built on my win 10 machine for vcpkg (microsoft/vcpkg#26187) but I am unsure if it has any negative implications. Please have a look.

[pitrou]

@assignUser Did you also run the tests?

[assignUser]

No I just ran vcpkg install arrow[cuda]:x64-windows-static. I'll setup a proper C++ env to run them.

[pitrou]

In any case, the fix looks fine (assuming it compiles and tests).

[github-actions]

https://issues.apache.org/jira/browse/ARROW-17421

[github-actions]

⚠️ Ticket has not been started in JIRA, please click 'Start Progress'.

[assignUser]

@pitrou The cuda tests didn't build, it doesn't sound related though?

  Building Custom Rule C:/repos/17421-cuda-windows/cpp/src/arrow/gpu/CMakeLists.txt
  cuda_test.cc
cuda_test.obj : error LNK2019: unresolved external symbol "class arrow::Result<unsigned char *> __cdecl arrow::cuda::G
etHostAddress(unsigned __int64)" (?GetHostAddress@cuda@arrow@@YA?AV?$Result@PEAE@2@_K@Z) referenced in function "priva
te: virtual void __cdecl arrow::cuda::TestCudaHostBuffer_AllocateGlobal_Test::TestBody(void)" (?TestBody@TestCudaHostB 
uffer_AllocateGlobal_Test@cuda@arrow@@EEAAXXZ) [C:\repos\17421-cuda-windows\cpp\build\src\arrow\gpu\arrow-cuda-test.vc 
xproj]
cuda_test.obj : error LNK2019: unresolved external symbol "class arrow::Status __cdecl arrow::cuda::internal::StatusFr 
omCuda(enum cudaError_enum,char const *)" (?StatusFromCuda@internal@cuda@arrow@@YA?AVStatus@3@W4cudaError_enum@@PEBD@Z 
) referenced in function "public: virtual void __cdecl arrow::cuda::TestCudaBase::TearDown(void)" (?TearDown@TestCudaB 
ase@cuda@arrow@@UEAAXXZ) [C:\repos\17421-cuda-windows\cpp\build\src\arrow\gpu\arrow-cuda-test.vcxproj]
C:\repos\17421-cuda-windows\cpp\build\release\Release\arrow-cuda-test.exe : fatal error LNK1120: 2 unresolved external 
s [C:\repos\17421-cuda-windows\cpp\build\src\arrow\gpu\arrow-cuda-test.vcxproj]

[pitrou]

@assignUser It seems ARROW_EXPORT is missing on a bunch of APIs:

arrow/cpp/src/arrow/gpu/cuda_memory.h

Lines 252 to 257 in a270afc

	/// Low-level: get a device address through which the CPU data be accessed.
	Result<uintptr_t> GetDeviceAddress(const uint8_t* cpu_data,
	const std::shared_ptr<CudaContext>& ctx);
	/// Low-level: get a CPU address through which the device data be accessed.
	Result<uint8_t*> GetHostAddress(uintptr_t device_ptr);

arrow/cpp/src/arrow/gpu/cuda_internal.h

Lines 34 to 36 in a270afc

	std::string CudaErrorDescription(CUresult err);
	Status StatusFromCuda(CUresult res, const char* function_name = nullptr);

[assignUser]

Thanks, that fixed it: [==========] 17 tests from 7 test suites ran. (430 ms total) 🥳

[pitrou]

+1, thank you @assignUser

[pitrou]

Looks like AppVeyor build failure would be fixed by #13869

[ursabot]

Benchmark runs are scheduled for baseline = 3a59bc0 and contender = 7ecfcf0. 7ecfcf0 is a master commit associated with this PR. Results will be available as each benchmark for each run completes.
Conbench compare runs links:
[Finished ⬇️0.0% ⬆️0.0%] ec2-t3-xlarge-us-east-2
[Failed ⬇️0.37% ⬆️0.0%] test-mac-arm
[Failed ⬇️0.0% ⬆️0.0%] ursa-i9-9960x
[Finished ⬇️0.43% ⬆️0.0%] ursa-thinkcentre-m75q
Buildkite builds:
[Finished] 7ecfcf03 ec2-t3-xlarge-us-east-2
[Finished] 7ecfcf03 test-mac-arm
[Failed] 7ecfcf03 ursa-i9-9960x
[Finished] 7ecfcf03 ursa-thinkcentre-m75q
[Finished] 3a59bc02 ec2-t3-xlarge-us-east-2
[Failed] 3a59bc02 test-mac-arm
[Failed] 3a59bc02 ursa-i9-9960x
[Finished] 3a59bc02 ursa-thinkcentre-m75q
Supported benchmarks:
ec2-t3-xlarge-us-east-2: Supported benchmark langs: Python, R. Runs only benchmarks with cloud = True
test-mac-arm: Supported benchmark langs: C++, Python, R
ursa-i9-9960x: Supported benchmark langs: Python, R, JavaScript
ursa-thinkcentre-m75q: Supported benchmark langs: C++, Java

[ursabot]

['Python', 'R'] benchmarks have high level of regressions.
ursa-i9-9960x

[wesm]

Having to use shared_ptr for the PIMPL is weird, IIRC this is often caused by not having an explicit destructor?