Hi Dan,
I was able to build and run deviceQuery. I had to build as sudo as cuda is
installed as root. I noticed that CUDART library was statically linked. The
cmake error for amber install is still about CUDART library missing. Here
is the test output:
banipsita.MSI:/usr/local/cuda-11.4/samples/1_Utilities/deviceQuery$ sudo
CUDA_PATH=$CUDA_HOME make
[sudo] password for banipsita:
/usr/local/cuda-11.4/bin/nvcc -ccbin g++ -I../../common/inc -m64
--threads 0 -gencode arch=compute_35,code=sm_35 -gencode
arch=compute_37,code=sm_37 -gencode arch=compute_50,code=sm_50 -gencode
arch=compute_52,code=sm_52 -gencode arch=compute_60,code=sm_60 -gencode
arch=compute_61,code=sm_61 -gencode arch=compute_70,code=sm_70 -gencode
arch=compute_75,code=sm_75 -gencode arch=compute_80,code=sm_80 -gencode
arch=compute_86,code=sm_86 -gencode arch=compute_86,code=compute_86 -o
deviceQuery.o -c deviceQuery.cpp
nvcc warning : The 'compute_35', 'compute_37', 'compute_50', 'sm_35',
'sm_37' and 'sm_50' architectures are deprecated, and may be removed in a
future release (Use -Wno-deprecated-gpu-targets to suppress warning).
/usr/local/cuda-11.4/bin/nvcc -ccbin g++ -m64 -gencode
arch=compute_35,code=sm_35 -gencode arch=compute_37,code=sm_37 -gencode
arch=compute_50,code=sm_50 -gencode arch=compute_52,code=sm_52 -gencode
arch=compute_60,code=sm_60 -gencode arch=compute_61,code=sm_61 -gencode
arch=compute_70,code=sm_70 -gencode arch=compute_75,code=sm_75 -gencode
arch=compute_80,code=sm_80 -gencode arch=compute_86,code=sm_86 -gencode
arch=compute_86,code=compute_86 -o deviceQuery deviceQuery.o
nvcc warning : The 'compute_35', 'compute_37', 'compute_50', 'sm_35',
'sm_37' and 'sm_50' architectures are deprecated, and may be removed in a
future release (Use -Wno-deprecated-gpu-targets to suppress warning).
mkdir -p ../../bin/x86_64/linux/release
cp deviceQuery ../../bin/x86_64/linux/release
banipsita.MSI:/usr/local/cuda-11.4/samples/1_Utilities/deviceQuery$
./deviceQuery
./deviceQuery Starting...
CUDA Device Query (Runtime API) version (CUDART static linking)
Detected 1 CUDA Capable device(s)
Device 0: "NVIDIA GeForce RTX 3070 Laptop GPU"
CUDA Driver Version / Runtime Version 11.6 / 11.4
CUDA Capability Major/Minor version number: 8.6
Total amount of global memory: 8192 MBytes (8589410304
bytes)
(040) Multiprocessors, (128) CUDA Cores/MP: 5120 CUDA Cores
GPU Max Clock rate: 1620 MHz (1.62 GHz)
Memory Clock rate: 7001 Mhz
Memory Bus Width: 256-bit
L2 Cache Size: 4194304 bytes
Maximum Texture Dimension Size (x,y,z) 1D=(131072), 2D=(131072,
65536), 3D=(16384, 16384, 16384)
Maximum Layered 1D Texture Size, (num) layers 1D=(32768), 2048 layers
Maximum Layered 2D Texture Size, (num) layers 2D=(32768, 32768), 2048
layers
Total amount of constant memory: 65536 bytes
Total amount of shared memory per block: 49152 bytes
Total shared memory per multiprocessor: 102400 bytes
Total number of registers available per block: 65536
Warp size: 32
Maximum number of threads per multiprocessor: 1536
Maximum number of threads per block: 1024
Max dimension size of a thread block (x,y,z): (1024, 1024, 64)
Max dimension size of a grid size (x,y,z): (2147483647, 65535, 65535)
Maximum memory pitch: 2147483647 bytes
Texture alignment: 512 bytes
Concurrent copy and kernel execution: Yes with 5 copy engine(s)
Run time limit on kernels: Yes
Integrated GPU sharing Host Memory: No
Support host page-locked memory mapping: Yes
Alignment requirement for Surfaces: Yes
Device has ECC support: Disabled
Device supports Unified Addressing (UVA): Yes
Device supports Managed Memory: Yes
Device supports Compute Preemption: Yes
Supports Cooperative Kernel Launch: Yes
Supports MultiDevice Co-op Kernel Launch: No
Device PCI Domain ID / Bus ID / location ID: 0 / 1 / 0
Compute Mode:
< Default (multiple host threads can use ::cudaSetDevice() with device
simultaneously) >
deviceQuery, CUDA Driver = CUDART, CUDA Driver Version = 11.6, CUDA Runtime
Version = 11.4, NumDevs = 1
Result = PASS
Thank you for your help,
Charlotta Lebedenko
On Mon, Mar 7, 2022 at 6:38 PM Daniel Roe <daniel.r.roe.gmail.com> wrote:
> On Mon, Mar 7, 2022 at 6:49 AM Daniel Roe <daniel.r.roe.gmail.com> wrote:
> > .Charlotta, are you able to compile/run any cuda code at all? Maybe the
> devicequery sample from cuda?
>
> Specifically, try the following.
>
> Change to the directory <cuda samples>//1_Utilities/deviceQuery
>
> Build it (assuming CUDA_HOME is pointing to your CUDA install):
>
> CUDA_PATH=$CUDA_HOME make
>
> Run deviceQuery
>
> You should hopefully get a Result = PASS at the end. If not, something
> is wrong with the CUDA install.
>
> -Dan
>
> >
> > -Dan
> >
> >
> >> CUDA in Windows since it runs
> >> with a DOS system. If you want to have CUDA support, you can opt to dual
> >> boot your computer with Ubuntu or any Linux OS. There are installation
> >> guidelines on the internet.
> >>
> >> I hope this helps.
> >>
> >>
> >>
> >> Cheers,
> >>
> >> Alexis
> >>
> >> On Mon, Mar 7, 2022 at 2:47 AM Charlotta Lebedenko <
> clebedenko.fordham.edu>
> >> wrote:
> >>
> >> > Hello,
> >> >
> >> > Unfortunately I am still facing this problem with amber installation
> on
> >> > windows. I am not sure how to resolve it. Does anyone have any advice
> about
> >> > cmake and cuda?
> >> >
> >> > Thank you,
> >> > Charlotta Lebedenko
> >> >
> >> >
> >> >
> >> > > On Mar 3, 2022, at 15:30, Charlotta Lebedenko <
> clebedenko.fordham.edu>
> >> > wrote:
> >> > >
> >> > >
> >> > > Hello,
> >> > >
> >> > > Thank you for the advice. We tried these steps and we are still
> getting
> >> > the same error. We are doing this on Windows 10, not Windows 11. So
> maybe
> >> > there is a problem there.
> >> > > We set -DCUDA_TOOLKIT_ROOT_DIR and CUDA_HOME to cuda home
> directory. We
> >> > probably need help from someone who understands Cmake.
> >> > >
> >> > > Here is the error again:
> >> > >
> >> > > -- Amber source found, building AmberTools and Amber
> >> > > -- Could NOT find CUDA (missing: CUDA_CUDART_LIBRARY) (found version
> >> > "11.4")
> >> > > CMake Error at cmake/CudaConfig.cmake:15 (message):
> >> > > You turned on CUDA, but it was not found. Please set the
> >> > > CUDA_TOOLKIT_ROOT_DIR option to your CUDA install directory.
> >> > > Call Stack (most recent call first):
> >> > > CMakeLists.txt:120 (include)
> >> > >
> >> > > We also set:
> >> > >
> >> >
> -DCUDA_CUDART_LIBRARY=/usr/local/cuda-11.4/targets/x86_64-linux/lib/libcudart.so.11.4.43
> >> > >
> >> > > Our cmake command is:
> >> > > cmake $AMBER_PREFIX/amber20_src \
> >> > > -DCMAKE_INSTALL_PREFIX=$AMBER_PREFIX/amber20 \
> >> > > -DCOMPILER=GNU -DBUILD_QUICK=TRUE \
> >> > > -DMPI=FALSE -DCUDA=TRUE
> -DCUDA_TOOLKIT_ROOT_DIR=/usr/local/cuda-11.4
> >> >
> -DCUDA_CUDART_LIBRARY=/usr/local/cuda-11.4/targets/x86_64-linux/lib/libcudart.so.11.4.43
> >> > -DINSTALL_TESTS=TRUE \
> >> > > -DDOWNLOAD_MINICONDA=TRUE -DMINICONDA_USE_PY3=TRUE \
> >> > > 2>&1 | tee cmake.log
> >> > >
> >> > > Thank you,
> >> > > Charlotta Lebedenko
> >> > >
> >> > >
> >> > >
> >> > >> On Thu, Mar 3, 2022 at 9:32 AM Daniel Roe <daniel.r.roe.gmail.com>
> >> > wrote:
> >> > >> Hi,
> >> > >>
> >> > >> I've been able to install Amber on Windows11/WSL2 with CUDA with no
> >> > issue.
> >> > >> The only different is that I installed CUDA manually (
> >> > >>
> >> >
> https://urldefense.proofpoint.com/v2/url?u=https-3A__developer.nvidia.com_cuda-2D11-2D4-2D4-2Ddownload-2Darchive-3Ftarget-5Fos-3DLinux-26target-5Farch-3Dx86-5F64-26Distribution-3DWSL-2DUbuntu-26target-5Fversion-3D2.0-26target-5Ftype-3Drunfile-5Flocal&d=DwIGaQ&c=aqMfXOEvEJQh2iQMCb7Wy8l0sPnURkcqADc2guUW8IM&r=jOIeI-lTF_2GutlqJUB8jwla6pUZ7k5EeNYDA2RM36A&m=LxDU4uEY3ByKgpRHV5eDbVEPCIZYsLumYeEsQtFAup467V5dapkwob69zo1tel2k&s=iswwSnDzYx_pohoZpVrttYR7-lmM39JF1-6fEZHyMwc&e=
> >> > )
> >> > >> into a subdirectory of my home directory and set the environment
> >> > variables
> >> > >> CUDA_HOME, PATH, and LD_LIBRARY_PATH, e.g.
> >> > >>
> >> > >> export CUDA_HOME=<path_to_cuda>
> >> > >> export LD_LIBRARY_PATH=<path_to_cuda>/lib64:$LD_LIBRARY_PATH
> >> > >> export PATH=<path_to_cuda>/bin:$PATH
> >> > >>
> >> > >> With those set all I had to do is pass -DCUDA=TRUE to cmake and it
> was
> >> > >> picked up just fine.
> >> > >>
> >> > >> -Dan
> >> > >>
> >> > >> On Wed, Mar 2, 2022 at 4:28 PM Charlotta Lebedenko <
> >> > clebedenko.fordham.edu>
> >> > >> wrote:
> >> > >>
> >> > >> > Hello,
> >> > >> >
> >> > >> > I am still struggling with this same issue during installation.
> I was
> >> > >> > hoping someone who has installed Amber with CUDA support on
> Windows
> >> > before
> >> > >> > using WSL2 could offer some advice?
> >> > >> >
> >> > >> > Thank you,
> >> > >> > Charlotta Lebedenko
> >> > >> >
> >> > >> > >
> >> > >> > > On Feb 28, 2022, at 13:04, Charlotta Lebedenko <
> >> > clebedenko.fordham.edu>
> >> > >> > wrote:
> >> > >> > >
> >> > >> > >
> >> > >> > > Dear Amber support,
> >> > >> > >
> >> > >> > > We are trying to install Amber20 and Ambertools21 with CUDA
> support
> >> > on
> >> > >> > Windows 10 21H2 using WSL2 with ubuntu. We see this cmake error:
> >> > >> > > -- Could NOT find CUDA (missing: CUDA_CUDART_LIBRARY) (found
> version
> >> > >> > "11.4")
> >> > >> > > CMake Error at cmake/CudaConfig.cmake:15 (message):
> >> > >> > > You turned on CUDA, but it was not found. Please set the
> >> > >> > > CUDA_TOOLKIT_ROOT_DIR option to your CUDA install directory.
> >> > >> > > Call Stack (most recent call first):
> >> > >> > > CMakeLists.txt:120 (include)
> >> > >> > >
> >> > >> > > nvcc is installed at: /usr/local/cuda-11.4/bin/nvcc
> >> > >> > > CUDA toolkit is installed into a standard location
> /usr/local/cuda:
> >> > >> > > ls -l /usr/local
> >> > >> > > total 36
> >> > >> > > drwxrwxr-x 2 root root 4096 Feb 28 11:49 bin
> >> > >> > > lrwxrwxrwx 1 root root 22 Feb 28 11:49 cuda ->
> >> > /etc/alternatives/cuda
> >> > >> > > lrwxrwxrwx 1 root root 25 Feb 28 11:49 cuda-11 ->
> >> > >> > /etc/alternatives/cuda-11
> >> > >> > > drwxr-xr-x 17 root root 4096 Feb 28 11:49 cuda-11.4
> >> > >> > >
> >> > >> > > ls -l /etc/alternatives
> >> > >> > > lrwxrwxrwx 1 root root 20 Feb 28 11:49 cuda ->
> /usr/local/cuda-11.4
> >> > >> > > lrwxrwxrwx 1 root root 20 Feb 28 11:49 cuda-11 ->
> >> > /usr/local/cuda-11.4
> >> > >> > >
> >> > >> > > We set export CUDA_HOME=/usr/local/cuda-11.4
> >> > >> > >
> >> > >> > > We added this to run_cmake to point to CUDA toolkit and cudart
> >> > library:
> >> > >> > > -DCUDA=TRUE -DCUDA_TOOLKIT_ROOT_DIR=/usr/local/cuda-11.4
> >> > >> >
> >> >
> -DCUDA_CUDART_LIBRARY=/usr/local/cuda-11.4/targets/x86_64-linux/lib/libcudart.so
> >> > >> >
> >> > >> > >
> >> > >> > > We still see the error above. What else can we try?
> >> > >> > >
> >> > >> > > We installed CUDA driver and toolkit following these
> instructions:
> >> > >> > > CUDA on WSL :: CUDA Toolkit Documentation (nvidia.com)
> >> > >> > >
> >> > >> > > Thank you,
> >> > >> > > Charlotta Lebedenko
> >> > >> > _______________________________________________
> >> > >> > AMBER mailing list
> >> > >> > AMBER.ambermd.org
> >> > >> >
> >> >
> https://urldefense.proofpoint.com/v2/url?u=http-3A__lists.ambermd.org_mailman_listinfo_amber&d=DwIGaQ&c=aqMfXOEvEJQh2iQMCb7Wy8l0sPnURkcqADc2guUW8IM&r=jOIeI-lTF_2GutlqJUB8jwla6pUZ7k5EeNYDA2RM36A&m=LxDU4uEY3ByKgpRHV5eDbVEPCIZYsLumYeEsQtFAup467V5dapkwob69zo1tel2k&s=Qt2CnTbykcS2KFNj_kieGCGm35YDQhDwppdlYm1Vya0&e=
> >> > >> >
> >> > >> _______________________________________________
> >> > >> AMBER mailing list
> >> > >> AMBER.ambermd.org
> >> > >>
> >> >
> https://urldefense.proofpoint.com/v2/url?u=http-3A__lists.ambermd.org_mailman_listinfo_amber&d=DwIGaQ&c=aqMfXOEvEJQh2iQMCb7Wy8l0sPnURkcqADc2guUW8IM&r=jOIeI-lTF_2GutlqJUB8jwla6pUZ7k5EeNYDA2RM36A&m=LxDU4uEY3ByKgpRHV5eDbVEPCIZYsLumYeEsQtFAup467V5dapkwob69zo1tel2k&s=Qt2CnTbykcS2KFNj_kieGCGm35YDQhDwppdlYm1Vya0&e=
> >> > _______________________________________________
> >> > AMBER mailing list
> >> > AMBER.ambermd.org
> >> >
> https://urldefense.proofpoint.com/v2/url?u=http-3A__lists.ambermd.org_mailman_listinfo_amber&d=DwIGaQ&c=aqMfXOEvEJQh2iQMCb7Wy8l0sPnURkcqADc2guUW8IM&r=jOIeI-lTF_2GutlqJUB8jwla6pUZ7k5EeNYDA2RM36A&m=dDmUDpfZ7phpbAWIypFSiJAtCWKxJ7zE2Q1TrJhbpIjM9dsufD1FExOOQAFtRt-L&s=5YzJQJDkjA4b8YF82kXSTxmQLemTlmCmOzIzts35fPI&e=
> >> >
> >> --
> >> Alexis Azucena
> >>
> >> Instructor
> >>
> >> School of Technology | University of the Philippines Visayas
> >> +639175841130
> >> agazucena.up.edu.ph
> >> _______________________________________________
> >> AMBER mailing list
> >> AMBER.ambermd.org
> >>
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>
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Received on Thu Mar 10 2022 - 15:30:02 PST
