CUDA Compilers

CUDA_Compilers.md

In general, check the crt/host_config.h file to find out which versions are supported. Sometimes it is possible to hack the requirements there to get some newer versions working, too :)

Thrust version can be found in $CUDA_ROOT/include/thrust/version.h.

Download Archives: https://developer.nvidia.com/cuda-toolkit-archive

Release notes for CUDA Toolkit (CTK):

• latest: https://docs.nvidia.com/cuda/cuda-toolkit-release-notes/index.html
• archive: https://docs.nvidia.com/cuda/archive/
• 11.8.0: https://docs.nvidia.com/cuda/archive/11.8.0/
• 11.7.2: https://docs.nvidia.com/cuda/archive/11.7.1
• ...
• 11.5.1: https://docs.nvidia.com/cuda/archive/11.5.1/
• 11.4.2: https://docs.nvidia.com/cuda/archive/11.4.2/
• 11.4.1: https://docs.nvidia.com/cuda/archive/11.4.1/
• 11.4.0: https://docs.nvidia.com/cuda/archive/11.4.0/
• 11.3: https://docs.nvidia.com/cuda/archive/11.3.0/index.html
• 11.2: https://docs.nvidia.com/cuda/archive/11.2.2/index.html
• 11.1: https://docs.nvidia.com/cuda/archive/11.1.1/index.html
• 11.0: https://docs.nvidia.com/cuda/archive/11.0/cuda-toolkit-release-notes/index.html
• 10.2: https://developer.download.nvidia.com/compute/cuda/10.2/Prod/docs/sidebar/CUDA_Toolkit_Release_Notes.pdf
• 10.1: https://developer.download.nvidia.com/compute/cuda/10.1/Prod/docs/sidebar/CUDA_Toolkit_Release_Notes.pdf
• 10.0: https://developer.download.nvidia.com/compute/cuda/10.0/Prod/docs/sidebar/CUDA_Toolkit_Release_Notes.pdf
• 9.2: https://developer.download.nvidia.com/compute/cuda/9.2/Prod/docs/sidebar/CUDA_Toolkit_Release_Notes.pdf
• 9.1: https://developer.download.nvidia.com/compute/cuda/9.1/Prod/docs/sidebar/CUDA_Toolkit_Release_Notes.pdf
• 9.0: https://developer.download.nvidia.com/compute/cuda/9.0/Prod/docs/sidebar/CUDA_Toolkit_Release_Notes.pdf
• 8.0: https://developer.nvidia.com/compute/cuda/8.0/Prod2/docs/sidebar/CUDA_Toolkit_Release_Notes-pdf
• 7.5: http://developer.download.nvidia.com/compute/cuda/7.5/Prod/docs/sidebar/CUDA_Toolkit_Release_Notes.pdf
• 7.0: http://developer.download.nvidia.com/compute/cuda/7_0/Prod/doc/CUDA_Toolkit_Release_Notes.pdf
• 6.5: http://developer.download.nvidia.com/compute/cuda/6_5/rel/docs/CUDA_Toolkit_Release_Notes.pdf
• 6.0: http://developer.download.nvidia.com/compute/cuda/6_0/rel/docs/CUDA_Toolkit_Release_Notes.pdf
• 5.5: http://developer.download.nvidia.com/compute/cuda/5_5/rel/docs/CUDA_Toolkit_Release_Notes.pdf

Version notes Nvidia HPC SDK:

• https://docs.nvidia.com/hpc-sdk/hpc-sdk-release-notes/index.html

Compatibility Guarantees

Quote:

• CUDA 10.0: First introduced in CUDA 10, the CUDA Forward Compatible Upgrade is designed to allow users to get access to new CUDA features and run applications built with new CUDA releases on systems with older installations of the NVIDIA datacenter GPU driver.
• CUDA 11.1: First introduced in CUDA 11.1, CUDA Enhanced Compatibility provides two benefits:
  • By leveraging semantic versioning across components in the CUDA Toolkit, an application can be built for one CUDA minor release (such as 11.1) and work across all future minor releases within the major family (such as 11.x).
  • CUDA has relaxed the minimum driver version check and thus no longer requires a driver upgrade with minor releases of the CUDA Toolkit.
• CUDA 12.4: Starting in CUDA 12.4, the NVIDIA driver installation on Linux will be opt-in. The goal is to improve user experience for a wide range of use cases such as installing the open module flavor driver. The cuda-runtime dependency and therefore the cuda-drivers (NVIDIA driver) dependency will be removed from the top-level cuda meta-package. Effectively, the cuda and cuda-toolkit meta-packages will be equivalent in CUDA 12.4.

nvcc

Latest, officical Compiler requirements: http://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html

CUDA version	SM Arch	g++	icpc	pgc++	xlC	MSVC	clang++	Linux driver	thrust	note
1.0	1.0-1.1	?	?	?
1.1	1.0-1.1	?	?	?
2.0	1.0-1.1	?	?	?
2.1	1.0-1.3	?	?	?
2.3.1	1.0-1.3	?	?	?
3.0	1.0-2.0	?	?	?
3.1	1.0-2.0	?	?	?
3.2	1.0-2.1	?	11.1	?
4.0	1.0-2.1	<=4.4	11.1	?
4.1	1.0-2.1	<=4.5	11.1	?
4.2	1.0-2.1	<=4.6	11.1	?
5.0	1.0-3.?	<=4.6	11.1	?				?	1.5.3
5.5	1.0-3.?	<=4.8	12.1	?				?	1.7.0	C++11 on host side supported; ICC fixed to build 20110811
6.0	1.0-5.0	<=4.8	13.1	?				331.62	1.7.1
6.5	1.1-5.X	<=4.8	14.0	?		?		?	1.7.2	experimenal device side C++11 support; including this version, <thrust/sort.h> skrews up __CUDA_ARCH__ (must be undefined on host); deprecation of SM 11-13 (10 removed)
7.0.17 (RC)	s. below	<=4.9	15.0	>=14.9	13.1.1	?		346.29	1.8.0	first official PGI support, first xlc string found; powerpc64 w. little endian supported
7.0.27	2.0-5.X	<=4.9	15.0	>=14.9	13.1.1	2010-13		346.46	1.8.1	official C++11 support on device side
7.5		<=4.9	15.0	15.4	13.1	2010-13	3.5-3.6	352.41?	1.8.2	clang (host) on linux supported, __CUDACC_VER__ macros added
7.5.18	2.0-5.X	<=4.9	15.0	15.4	13.1	2010-13		352.39	1.8.2
8.0.44	2.0-6.X	<=5.3	15.0(.4)-16.0	16(.3)+	13.1(.2)	2012-15	3.8-3.9	367.48	1.8.3-patch2	sm_60 (pascal) support added
8.0.61	2.0-6.X	<=5.3	15.0(.4)-17.0	16(.3)+	13.1(.2)	2012-15	3.8-3.9	375.26	1.8.3-patch2	nvcc 8 is incompatible with std::tuple in gcc 5.4+
9.0.69 (RC)	3.0-7.0	<=5.5 (<=6)	15.0(.4)-17.0	17	13.1(.2)	2012-17	3.8-3.9	???.??	1.9.0-patch4	device-side C++14; __CUDACC_VER__ deprecated for __CUDACC_VER_MAJOR/MINOR/BUILD__
9.0.103 (RC)	3.0-7.0	<=5.5 (<=6)	15.0(.4)-17.0	17	13.1(.2)	2012-17	3.8-3.9	384.59	1.9.0-patch4	same as above, __CUDACC_VER__ defined as #error rendering it fully broken
9.0.176	3.0-7.0	<=5.5 (<=6)	(15.0-)17.0	17.1	13.1(.5)	2012-17	(3.8-)3.9	384.81	1.9.0-patch5	same as above
9.1.85	3.0-7.2	<=5.5 (<=6)	(15.0-)17.0	17.X	13.1(.6)	2012-17	(3.8-)4.0	390.46	1.9.1-patch2	math_functions.hpp moved to crt/
9.1.85.1										cuBLAS 9.1.128: Volta GEMM kernels optimized
9.1.85.2										ptxas: fix address calculations using large immediate operands
9.1.85.3										cuBLAS: fixes to GEMM optimizations for convolutional sequence to sequence (seq2seq) models.
9.0-9.1										nvcc 9.0-9.1 is incompatible with std::tuple in gcc 6+
9.2.88	3.0-7.2	<=7.3.0 (<=7)	(15.0-)17.0	17-18.X	13.1(.6),16.1	2012-17	(3.8-)5.0	396.26	1.9.2	CUTLASS 1.0 added; std::tuple fixed (prior GCC 6 issues)
9.2.148								396.37	1.9.2
10.0.130	3.0-7.5	<=7	(15.0-)18.0	17-18.X	13.1, 16.1	2013-17	(3.8-)6.0	410.48	1.9.3	CUDA Forward Compatible Upgrade
10.1.105	3.0-7.5	<=8	(15.0-)19.0	17-19.X		2013-19	(3.8-)7.0	418.39	1.9.4
10.1.168							(3.8-)8.0	418.67		10.1 "Update 1"
10.1.243								418.87		10.1 "Update 2"
10.2.89	3.0-7.5	<=8	(15.0-)19.0	18-19.X	13.1, 16.1	2015-19	(3.3-)8.X	440.33.01	1.9.7	sm_30,35,37,50 deprecated; nvcc: -allow-unsupported-compiler
11.0.1 (RC) NVCC:11.0.167	3.5-8.0	(5-)6-9.*	(15.0-)19.1	18-20.1	13.1, 16.1	2015-19	3.2-9.0.0	450.36.06	1.9.9	macOS dropped; libs drop pre-C++11, deprecate pre-C++14 (GCC < 5, Clang < 6, and MSVC < 2017); Arm C/C++ 19.2 support
11.0.2-1 NVCC:11.0.194							(3.3/)6-9.0.0	450.51.05		nvcc: --Wext-lambda-captures-this
11.0.3 NVCC:11.0.221	?	?	?	?	?	?	?	450.51.06	?	11.0 "Update 1"; nvcc: --forward-unknown-to-host-compiler, --forward-unknown-to-host-linker flags
11.1.0 NVCC:11.1.74	3.5-8.6	(5-)6-10.0	(15.0-)19.1	18-20.1	13.1, 16.1	2017-19	(3.3/)6-10.X	455.23.05	1.9.10-1	Ubuntu@ppc64le deprecated; CUDA Enhanced Compatibility
11.1.1 NVCC:11.1.?								?	?	?
11.2.0 NVCC:11.2.67							<12	460.27.04	1.10.0
11.2.1 NVCC:11.2.142								460.32.03	?	"Update 1"
11.2.2 NVCC:11.2.152								460.32.03	?	"Update 2"
11.3.0 NVCC:11.3.58		6.0-10.X						465.19.01	?	cu++flt added, Python Driver/RT bindings, alloca()
11.4.0 NVCC:11.4.48		6.0-11.X					<13	470.42.01	?	sm30,32 and Ubuntu 16.04 dropped, C++11 stdlib for math
11.4.1 NVCC:11.4.100		6.0-11.X						470.57.02	?	11.4 "Update 1", fix g++ 10 issues with chrono headers of libstdc++; Ubuntu 16.04 dropped (x86)
11.4.2 NVCC:11.4.120							3.2-12.X	470.57.02	?	...
11.5.0 NVCC:11.5.50		6.0-11.X					3.2-12.X	495.29.05	?	...
11.5.1 NVCC:11.5.119
11.6.0 NVCC:11.6.55		6.0-11.X				adds VS2022	3.2-13.X	510.39.01	?	adds -arch=native and PTX generation in nvlink (for LTO workflows with PTX)
11.6.1 NVCC:11.6.112								510.47.03	?
11.6.2 NVCC:11.6.124								510.47.03	?
11.7.0 NVCC:11.7.64		?	?	?	?			515.43.04	?
11.7.1 NVCC:11.7.99								515.65.01	?
11.8.0 NVCC:11.8.89		6.0-11.2.1						520.61.05	?
12.0.0 NVCC:12.0.76	4.0-9.0	6.0-12.1 (12.2.1)	2021.6	22.7	16.1.x	-VS2022 17.4	-14.X	525.60.13	2.0.1	Hopper and Lovelance, JIT LTO (nvJitLink lib), NVVM IR 2.0, CUDA-MEMCHECK -> Compute Sanitizer , sm_35/37 dropped in all libs, 32-bit compilation support dropped
12.3.0 NVCC:12.0.76								545.23.06	2.2.0
CUDA version	SM	g++	icpc	pgc++	xlC	MSVC	clang++	Linux driver	thrust	note

SM: means SM architecture support.

pgc++: now NVHPC products, e.g., nvc/nvfortran/nvc++.

Note: empty cells generally mean "same as above" for readability.

macOS: As of 7.0, clang seems to be the only supported compiler on OSX (but no version check found). CUDA 10.1.243 adds support for Xcode 10.2 . CUDA 11.0 dropped macOS support.

Compilers such as pgC, icc, xlC are only supported on x86 linux and little endian.

Dynamic parallelism was added with sm_35 and CUDA 5.0.

Newer CUDA releases have a per-release support matrix for compilers, which also lists supported kernel and glibc versions: https://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html#system-requirements

clang++ -x cuda

clang++ can compile CUDA C++ to ptx as well. Give it a whirl!

clang++	supported CUDA release	supported SMs
3.9-5.0	7.0-8.0	2.0-(5.0)6.0
6.0	7.0-9.0	(2.0)3.0-7.0
7.0	7.0-9.2	(2.0)3.0-7.2
8.0	7.0-10.0	(2.0)3.0-7.5
9.0	7.0-10.1	(2.0)3.0-7.5
10.0	7.0-10.1	(2.0)3.0-7.5
11.0	7.0-11.0	(2.0)3.0-8.0
12.0	7.0-11.0	(2.0)3.0-8.0
13.0	7.0-11.2	(2.0)3.0-8.6
14.0	7.0-11.5	(2.0)3.0-8.6
15.0	7.0-11.5	(2.0)3.0-8.6
16.0	7.0-11.8	(2.0)3.0-9.0
main	7.0-12.1	(2.0)3.5-9.0

https://llvm.org/docs/CompileCudaWithLLVM.html

Device-Side C++ Standard Support

C++ core language features:

	supported C++ standard	notes
nvcc -6.0	c++03
nvcc 6.5	c++03, exp. c++11	undocumented
nvcc 7.0-8.0	c++03,11	only c++11 switch
nvcc 9.0-10.2	c++03,11,14	10.2 adds libcu++ (atomics); open repository: https://github.com/NVIDIA/libcudacxx/releases
nvcc 11.0.167+	c++03,11,14,17	C++11 host compiler needed for math libs; ships C++11-compatible backport of the C++20 synchronization library; device LTO added; starting with CUDA Toolkit 11.0.1, nvcc and CUDA Toolkit versions are not equivalent anymore
nvcc 12.0+	c++03,11,14,17,20
clang 5+	c++03,11,14,17
clang 6+	c++03,11,14,17,2a
clang 10+	c++03,11,14,17,20
clang 13+	c++03,11,14,17,20,2b
clang trunk	c++03,11,14,17,20,2b	status

CUDA-enabled C++ standard library libcu++, based on LLVM's libc++ (docs):

	introduced components	notes
CUDA 10.2	<atomic> (SM6.0+), <type_traits>	introduction of libcu++
CUDA 11.0	atomic<T>::wait/notify, <barrier>, <latch>, <counting_semaphore>(SM7.0+), <chrono>, <ratio>, <functional> w/o function	anticipated with GTC 2020 slides
CUDA 11.2	cuda::std::tuple,pair	notes
CUDA 12.0	cuda::std::barrier
CUDA next	cuda::std::complex, backports: chrono, type_traits	notes
newer	see the release notes and api docs	all open source now

Incremental libcu++ release goals (GTC 2020):

• Version 1 (CUDA 10.2): <atomic>(SM6.0+), <type_traits>.
• Version 2 (CUDA next): atomic<T>::wait/notify, <barrier>, <latch>, <counting_semaphore>(SM7.0+), <chrono>, <ratio>, <functional>minus function.
• Future priorities: atomic_ref<T>, <complex>, <tuple>, <array>, <utility>, <cmath>, string processing, ...

NVC++

NVC++ is a unified C++ compiler and GPU-accelerated STL for the CUDA platform. It also seems to support OpenACC. NVC++ does currently not support the CUDA C++ language.

	supported C++ standard	notes
nvc++ 11.0	...,c++17	initial release, ships C++11-compatible backport of the C++20 synchronization library

All GPU compilers are cheese.

Agree CUDA on Mac is dead sometime soon. Compiling CUDA with clang is a viable proposition on at least Linux now and moving forward :-)

@ax3l: since you added question marks into the support row for CUDA 11.2.
I spotted no changes so you can remove ?

CUDA 11.2.0_460.27.04

• nvcc + clang as host compiler:
  • clang 3.3+ - 10.x are supported

#if defined(__clang__) && !defined(__ibmxl_vrm__) && !defined(__ICC) && !defined(__HORIZON__) && !defined(__APPLE__)
#if (__clang_major__ >= 11) || (__clang_major__ < 3) || ((__clang_major__ == 3) &&  (__clang_minor__ < 3))
#error -- unsupported clang version! clang version must be less than 11 and greater than 3.2 . The nvcc flag '-allow-unsupported-compiler' can be used to override this version check; however, using an unsupported host compiler may cause compilation failure or incorrect run time execution. Use at your own risk.
//...

• nvcc + gcc as host compiler:
  • up to gcc 10.X are supported

#if defined(__GNUC__)
#if __GNUC__ > 10
#error -- unsupported GNU version! gcc versions later than 10 are not supported! The nvcc flag '-allow-unsupported-compiler' can be used to override this version check; however, using an unsupported host compiler may cause compilation failure or incorrect run time execution. Use at your own risk.
//...

• pgi 18.X - 20.X

#if defined(__PGIC__)
#if ((__PGIC__ != 18) && (__PGIC__ != 19) && (__PGIC__ != 20) && !(__PGIC__ == 99 && __PGIC_MINOR__ == 99))
#error -- unsupported pgc++ configuration! Only pgc++ 18, 19 and 20 are supported! The nvcc flag '-allow-unsupported-compiler' can be used to override this version check; however, using an unsupported host compiler may cause compilation failure or incorrect run time execution. Use at your own risk.

• XL

  • ... only xlC 13.1 and 16.1 ...

• ICC

  • (15.0) - 19.1

#if (__ICC != 1500 && __ICC != 1600 && __ICC != 1700 && __ICC != 1800 && !(__ICC >= 1900 && __ICC <= 1999)) || !defined(__GNUC__) || !defined(__LP64__)

#error -- unsupported ICC configuration! Only ICC 15.0, ICC 16.0, ICC 17.0, ICC 18.0 and ICC 19.x on Linux x86_64 are supported! 

• MSC

#if _MSC_VER < 1910 || _MSC_VER >= 1930
#error -- unsupported Microsoft Visual Studio version! Only the versions between 2017 and 2019 (inclusive) are

@ax3l @bernhardmgruber pointed out that the table is saying clang 3.X is not supported for CUDA 11.X. I think it is wrong because clang 3.3+ is supported.

@Artem-B (and others)

Any idea when clang will support cuda 11? At my group, we are undecided if to choose c++20 and cuda 10.1 or c++17 and cuda 11 (with nvcc instead of clang), for an upcoming project which we will start in around 3 months.
Ideally we would prefer to use clang w/ support for cuda 11 (as we will be working with new ampere cards) but some of the features (i.e. modules) of c++ 20 are too good to ignore for a project that will be written from scratch.

Clang (top-of-the-tree) is able to compile with CUDA-11.x. It works well enough to compile TensorFlow. What's missing is the support for the full set of the new TensorCore instructions for newer GPUs (that's been the case for a while, already), ability to target sm_86, and support for bf16/tf32 types. Existing code that compiles with CUDA-10.1 is expected to compile with CUDA-11.x.

I'll likely add sm_86 support in January. The rest is a larger undertaking with no specific plans to get it done. In practice the code that would need TensorCore instructions tends to use inline assembly for the new instructions and should compile with clang now. Support for bf16/tf32 will probably not happen any time soon.

@Artem-B
Thanks for the update. We already have a few 3090 (which we will be using fp16) while we wait for the a100 system to be delivered, so we will probably start working with clang and then see if its worth to port the c++ 20 code to c++17 to be used with nvcc.

Also, any idea of how clang is comparing to nvcc in terms of optimal code/performance?
We will be using cuda/cudnn/cublas.

Also, any idea of how clang is comparing to nvcc in terms of optimal code/performance?

Performance-wise clang is usually on par. Sometimes a bit better (it tends to have a bit better optimizer), sometimes a bit worse (e.g. NVCC is much more aggressive at unrolling loops). A lot of the differences are eliminated due to the fact that both NVCC and clang in the end use ptxas which optimizes generated PTX and often produces nearly identical SASS for somewhat different PTX from both compilers.

We will be using cuda/cudnn/cublas.

For using NVIDIA's libraries compiler does not matter -- it's the same library regardless of whether you use clang or nvcc.
For CUDA sources, see above.

Great, Thanks.

@psychocoderHPC thank you for the update!

I updated the old clang versions, since the changelog does officially drop support for them. That means the library teams at Nvidia do not run CI against it anymore, so the range of usage will get narrower and less useful for those ancient compiler releases with modern CUDA releases (think: cuRand, cuBLAS, cuFFT, cub and thrust). Also, Nvidia libs transition all to C++14, so essentially you don't want to bother with gcc<5 and clang<5 anymore with CUDA11+.

With that disclaimer said, I updated the table accordingly nonetheless :) (putting ancient asserts in brackets)

Note that https://llvm.org/docs/CompileCudaWithLLVM.html still documents that latest supported CUDA is 10.1. Whose error is that?

@mabraham The documentation is in this file: https://github.com/llvm/llvm-project/blob/main/llvm/docs/CompileCudaWithLLVM.rst
You could send a PR to http://reviews.llvm.org and assign/request @Artem-B for a review :)

latest supported CUDA is 10.1.
This is still true. This is the version for which clang implements all builtins needed by CUDA headers.
More recent CUDA versions will mostly compile and work as long as you don't happen to need the new compiler builtins. I.e. if you include mma.h or cuda_fp16.h when bf16/tf32 types are enabled in CUDA-11.x, things will likely break. Most of the code that compiles with CUDA-11.1 will still compile with newer CUDA versions, so clang issues a warning, but allows compilation to proceed. The results vary.

You can check out the PyTorch documentation or use a from-source package manager like Spack (package: py-torch). This comment section is not the right place for support for specific CUDA-dependent software though, all we do is document CUDA compiler compatibility.

@Artem-B I was wondering, should the C++ standard default for -x cuda maybe be in lockstep with the Clang default for -x c++ to avoid confusion?

$ clang++-9 -dM -E -x c++  /dev/null | grep -F __cplusplus
#define __cplusplus 201402L

$ clang++-9 -dM -E -nocudalib -nocudainc -x cuda /dev/null | grep -F __cplusplus
#define __cplusplus 199711L
#define __cplusplus 199711L

Huh. Interesting. I don't think we do anything special to set the default C++ version during CUDA compilation.
I suspect that whatever sets it only checks if the input language is C++, but does not pay attention to C++ extensions.

Yes, it would make sense to match the default version set by clang for C++. I'll get that fixed.

@Artem-B awesome, thanks a lot!

If it's any good, the friendly folks over at AMD/HIP seem to have the same challenge :)
ROCm/HIP#2278

CUDA and HIP front-end share the same code under the hood, so it's not surprising.

AMD folks beat me to it: https://reviews.llvm.org/D103221

Cool! But that diff only changed the HIP frontend, not yet the CUDA frontend?
The CUDA defaults a few lines above probably need changing, too :)

It's c++14 by default now for both CUDA and HIP: llvm/llvm-project@f7e87dd

Wuhu, thanks a lot!

nvcc 11.4.1 now works again with g++ 10. Previous versions of nvcc choked somewhere in the chrono headers of libstdc++ IIRC.
Also g++ 11 is now supported with nvcc 11.4.1. I just successfully compiled an alpaka/LLAMA program with both combinations.

Thanks for the info @bernhardmgruber. So you say we should mark nvcc 11.1..11.4.0 as broken for g++10, right?

I am mainly happy that nvcc 11.4.1 supports g++11 now, which you updated, thx!

So you say we should mark nvcc 11.1..11.4.0 as broken for g++10, right?

Well, some versions of nvcc before 11.4.1 failed to parse the chrono headers. Whether that should be considered broken is beyond my judgement. Some people may not need this part of the stdlib and are fine. So I think your comment, that nvcc 11.4.1 fixes compilation of chrono, is good enough. Thanks!

Automated compiler crawling script on include/host_config.h by @haampie:
spack/spack#25054 (comment)

BTW, top-of-the-tree clang (14?) now defaults to sm_35 with CUDA support bumped up up to 11.4.
Default C++ version for CUDA compilation now matches that of C++ compilation and is currently C++14.

Thanks Artem, updated :)

CUDA 11.2.2 supports GCC-9, not 10, see:
https://docs.nvidia.com/cuda/archive/11.2.2/cuda-installation-guide-linux/index.html

CUDA 11.3.1 supports GCC 10.x, i.e. all GCC 10 minor versions, similar 11.4.1 supports all GCC 11 versions, so more complete:

• 9.2 GCC < 8
• 10.1 - 10.2 GCC < 9
• 11.0 GCC < 10
• 11.1 - 11.3 GCC < 11
• 11.4 - 11.7 GCC < 12

And for Clang:

• 10.2 Clang < 9
• 11.1 Clang < 11
• 11.2 - 11.3 Clang < 12
• 11.4 - 11.5 Clang < 13
• 11.6 - 11.7 Clang < 14

All checked for the SDKs I have installed via the checks in crt/host_config.h. I found this after an error in PyTorch pointed me to a compatibility check based on this table

@Flamefire Thanks, that usually is right - I try to document the host compiler version known at release time and documented by Nvidia for the specific release to have been tested with. Minor releases of host compilers released after the CTK usually (but not always) work well together.

Updated the 11.3 and 11.4 tables accordingly to your tests - thanks a lot!

Glad to see that PyTorch cites us! :)

CUDA 11.2.2 supports GCC-9, not 10, see:
https://docs.nvidia.com/cuda/archive/11.2.2/cuda-installation-guide-linux/index.html

@DStrelak thanks - I thik that is not as strict, checking crt/host_config.h. See @Flamefire's comment for comparison.

@DStrelak thanks - I thik that is not as strict, checking crt/host_config.h. See @Flamefire's comment for comparison.

I disagree, at least my my particular case it seems to be rather explicit about it :-)

/usr/local/cuda-11.2/bin/nvcc -o mycode.o -c --x cu -D_FORCE_INLINES -Xcompiler -fPIC -ccbin /usr/bin/g++-10 -std=c++14 --expt-extended-lambda -gencode=arch=compute_60,code=compute_60 -gencode=arch=compute_61,code=compute_61 -gencode=arch=compute_75,code=compute_75 -gencode=arch=compute_86,code=compute_86 -I../ -I/usr/include -I/usr/include/hdf5/serial -I/usr/include/opencv4 -Iexternal -Ilibraries mycode.cpp
/usr/include/c++/10/chrono: In substitution of 'template<class _Rep, class _Period> template<class _Period2> using __is_harmonic = std::__bool_constant<(std::ratio<((_Period2::num / std::chrono::duration<_Rep, _Period>::_S_gcd(_Period2::num, _Period::num)) * (_Period::den / std::chrono::duration<_Rep, _Period>::_S_gcd(_Period2::den, _Period::den))), ((_Period2::den / std::chrono::duration<_Rep, _Period>::_S_gcd(_Period2::den, _Period::den)) * (_Period::num / std::chrono::duration<_Rep, _Period>::_S_gcd(_Period2::num, _Period::num)))>::den == 1)> [with _Period2 = _Period2; _Rep = _Rep; _Period = _Period]':
/usr/include/c++/10/chrono:473:154:   required from here
/usr/include/c++/10/chrono:428:27: internal compiler error: Segmentation fault
  428 |  _S_gcd(intmax_t __m, intmax_t __n) noexcept
      |                           ^~~~~~
0x7f784e68b08f ???
	/build/glibc-SzIz7B/glibc-2.31/signal/../sysdeps/unix/sysv/linux/x86_64/sigaction.c:0
0x7f784e66c082 __libc_start_main
	../csu/libc-start.c:308
Please submit a full bug report,
with preprocessed source if appropriate.
Please include the complete backtrace with any bug report.
See <file:///usr/share/doc/gcc-10/README.Bugs> for instructions.

I found this page very useful - I am wondering if anyone is using github action for CI?

after github retires macos-10.5/xcode 10.0.3, I can non longer compile my cuda code using github's macos-11 and newer runners. see

actions/runner-images#7838

a strange thing is that even I copy cuda 10.2 or 8 on the macos-11 runner and use the nvcc in these older cuda versions, it still complain Apple Clang or GNU GCC are not supported. It also appears to me that such error was not thrown by crt/host_config.h.

is there ANY way to build CUDA on macos 11 or newer?

@fangq I'd just not bother with building CUDA on CI for macos anymore if CUDA support is dropped. What is the point of testing something if it cannot be run anymore? And it seems the latest working CUDA on macos is 10.2 and that only supports Clang <= 8.x
But if you really want you can try nvcc: -allow-unsupported-compiler as mentioned in the table above.

@Flamefire, I can't run any test from the runner anyways because it does not have GPU. I need it for building binaries for supported OSes. I statically link with cudart, so even cuda can not run on newer macos, a binary can still run as long as nvidia driver is installed.

I just tried the -allow-unsupported-compiler flag, unfortunately it has no effect, nvcc still complains that Apple Clang or GCC are not supported, nvcc 10.2 on macos 12; tried --allow-unsupported-compiler as well, same error.

$ nvcc --version
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2019 NVIDIA Corporation
Built on Wed_Oct_23_19:34:12_PDT_2019
Cuda compilation tools, release 10.2, V10.2.89

$ make CUDACC='nvcc -allow-unsupported-compiler'
nvcc -allow-unsupported-compiler -c -g -lineinfo -Xcompiler -Wall -DSAVE_DETECTORS -use_fast_math -arch=sm_35 -DMCX_TARGET_NAME='"Fermi MCX"' -DUSE_ATOMIC -use_fast_math -DSAVE_DETECTORS -o mcx_core.o  mcx_core.cu
nvcc fatal   : The version ('14.0') of the host compiler ('Apple clang') is not supported
make: *** [mcx_core.o] Error 1

$ make CUDACC='nvcc -allow-unsupported-compiler -ccbin /usr/local/bin/gcc-7'
/bin/sh: line 0: [: /Users/fangq/Downloads/cuda/bin/nvcc: binary operator expected
nvcc -allow-unsupported-compiler -ccbin /usr/local/bin/gcc-7 -c -g -lineinfo -Xcompiler -Wall -DSAVE_DETECTORS -use_fast_math -arch=sm_35 -DMCX_TARGET_NAME='"Fermi MCX"' -DUSE_ATOMIC -use_fast_math -DSAVE_DETECTORS -o mcx_core.o  mcx_core.cu
nvcc fatal   : GNU C/C++ compiler is no longer supported as a host compiler on Mac OS X.
make: *** [mcx_core.o] Error 1

@Flamefire, I can't run any test from the runner anyways because it does not have GPU. I need it for building binaries for supported OSes.

I meant: Is it worth building those binaries if they may not be run anymore (by users) as the OS stopped supporting CUDA (or the other way round)?

I just tried the -allow-unsupported-compiler flag, unfortunately it has no effect, nvcc still complains that Apple Clang or GCC are not supported, nvcc 10.2 on macos 12

https://docs.nvidia.com/cuda/cuda-compiler-driver-nvcc/index.html#allow-unsupported-compiler-allow-unsupported-compiler

This option has no effect on MacOS.

So there is no solution.

@ax3l I think the 11.4.0 for g++ is wrong. It only supports up to 10.X but the table shows compatibility with version 11. From my crt/host_config.h:

#if __GNUC__ > 10

#error -- unsupported GNU version! gcc versions later than 10 are not supported! The nvcc flag '-allow-unsupported-compiler' can be used to override this version check; however, using an unsupported host compiler may cause compilation failure or incorrect run time execution. Use at your own risk.

#endif /* __GNUC__ > 10 */

@Seralpa which CUDA version did you refer to? CUDA 11.4.0?

@ax3l yeah, CUDA version 11.4.0