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Hi guys, I’m having trouble installing GPU enabled gromacs on my computer (running ubuntu 20.04, GPU: NVIDIA GeForce RTX 2080). I got an error:
nvcc fatal : Unsupported gpu architecture 'compute_30'
Seems like the error is because Cuda (version 11) doesn’t support ‘compute_30’. After some searches, I tried passing following flags in CMake
-DGMX_CUDA_TARGET_COMPUTE=50 as well as
However, none of them worked: the installation failed in one of the tests
12 - GpuUtilsUnitTests (Failed)
I’m wondering if someone has experienced a similar issue and might have any solution?
You’re right that it’s likely an incompatibility of Gromacs with CUDA 11 - it just came out, after all. I suggest downgrading to CUDA 10 if you can. I have access to a 2080 system with that OS so I’ll see if I can get it working and report back here if it’s an easy patch, but otherwise you might have to wait until the next Gromacs release.
as like this
# Set the CUDA GPU architectures to compile for: # - with CUDA >=9.0 CC 7.0 is supported and CC 2.0 is no longer supported # => compile sm_61, sm_70 SASS, and compute_70 PTX # - with CUDA >=10.0 CC 7.5 is supported # => compile sm_61, sm_70, sm_75 SASS, and compute_75 PTX # First add flags that trigger SASS (binary) code generation for physical arch list (APPEND GMX_CUDA_NVCC_GENCODE_FLAGS "-gencode;arch=compute_61,code=sm_61") list (APPEND GMX_CUDA_NVCC_GENCODE_FLAGS "-gencode;arch=compute_70,code=sm_70") # Next add flags that trigger PTX code generation for the newest supported virtual arch # that's useful to JIT to future architectures list (APPEND GMX_CUDA_NVCC_GENCODE_FLAGS "-gencode;arch=compute_61,code=compute_61") list (APPEND GMX_CUDA_NVCC_GENCODE_FLAGS "-gencode;arch=compute_70,code=compute_70") if(NOT CUDA_VERSION VERSION_LESS "10.0") list (APPEND GMX_CUDA_NVCC_GENCODE_FLAGS "-gencode;arch=compute_75,code=compute_75") endif()
It’s gonna force gromacs to use compute 6.1 or u can use compute 7.0 for RTX 2080
The important part there is removing the sm_30 compilation flag from both sections, since it’s no longer supported in CUDA 11. Removing sm_35,37,50,52 is optional - it’ll give you a deprecation warning if you compile with it, but shouldn’t crash
Thank you both for your responses. I edited the gmxManageNvccConfig.cmake file as suggested. But the installation still failed the Test #12: GpuUtilsUnitTests (3 failed, 70 passed) :
[ FAILED ] 3 tests, listed below:
[ FAILED ] HostAllocatorTestCopyable/0.ManualPinningOperationsWorkWithCuda, where TypeParam = int
[ FAILED ] HostAllocatorTestCopyable/1.ManualPinningOperationsWorkWithCuda, where TypeParam = float
[ FAILED ] HostAllocatorTestCopyable/2.ManualPinningOperationsWorkWithCuda, where TypeParam = gmx::BasicVector
Errors while running CTest
make: *** [CMakeFiles/run-ctest-nophys.dir/build.make:58: CMakeFiles/run-ctest-nophys] Error 8
make: *** [CMakeFiles/Makefile2:2486: CMakeFiles/run-ctest-nophys.dir/all] Error 2
make: *** [CMakeFiles/Makefile2:2465: CMakeFiles/check.dir/rule] Error 2
make: *** [Makefile:249: check] Error 2
I went ahead and installed the gromacs anyway but I got segmentation fault error during runtime.
CUDA 11 is now supported from the head of github master but isn’t available in a stable release yet. Do you have access to CUDA 10? It should be fine to have the CUDA 11 drivers on the device but build against CUDA 10.
I downgraded to CUDA 10 and installed gromacs2020.3. However, there was an issue with the ‘renumbering of residue number to 1’. So I installed gromacs2019.6 instead and have been using it since. I will wait until new version comes out to upgrade. Thanks!
I am facing the same problem with Gromacs 2020.3 and CUDA 11 on Ubuntu 20.04 LTS.
Is there any workaround available yet?
please , did you solve it ?
No more workarounds are needed, just get the latest release (2020.4).
thanks, i will try it now … but does it will be compitabele with nvidia rtx 2060 cuda 11.1 ?
finally, it is solved … Many thanks
I used GCC 7 and CUDA 10.2. The newer version of Gromacs 2020.4 seems to be CUDA 11 compatible but I didn’t give it a try yet.
Yes, the CUDA 11 compatibility issues have been addressed in the 2020.4 release.
The code was running with gpu and suddenly screen of ubuntu gave me log in … I tried to log in but couldn’t until I restart laptop and got
Starting authorization manager
I know it’s a problem of ubuntu … but I had two graphic card one is nvidia and another is intel … does that because of enforce gpu for working… can you help me because I was happy that code is running and afraid of deleting or doing something with make me stuck again
Appreciate you help