Re: [Yade-users] [Question #703335]: Setting Up GPU
Question #703335 on Yade changed:
https://answers.launchpad.net/yade/+question/703335
Nima Goudarzi posted a new comment:
Hi Robert,
Thanks. I had been able to check the Cuda capability (Cuda 11.7) and
compile SuitSparse (5.13.0). I even compiled YADE with GPU enabled.
(1) I guess, there is an inconsistency in the Cuda installation
instruction (YADE manual) for adding CUDA library to the path:
Yade manual:
# Add the CUDA library to your path
export PATH=/usr/local/cuda/bin${PATH:+:${PATH}}
export LD_LIBRARY_PATH=/usr/local/cuda/lib64\
${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}
After installation of Cuda, three different Cuda folders are generated in my
usr/local directory
1- Cuda
2- Cuda 11.7
3-Cuda 11
Original instruction manual:
The PATH variable needs to include export
PATH=/usr/local/cuda-11.8/bin${PATH:+:${PATH}}. Nsight Compute has moved
to /opt/nvidia/nsight-compute/ only in rpm/deb installation method. When
using .run installer it is still located under /usr/local/cuda-11.8/.
To add this path to the PATH variable:
export PATH=/usr/local/cuda-11.8/bin${PATH:+:${PATH}}
In addition, when using the runfile installation method, the LD_LIBRARY_PATH
variable needs to contain /usr/local/cuda-11.8/lib64 on a 64-bit system, or
/usr/local/cuda-11.8/lib on a 32-bit system
To change the environment variables for 64-bit operating systems:
export LD_LIBRARY_PATH=/usr/local/cuda-11.8/lib64\
${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}
This is different from Yade manual. Which one to use?
However neither resolve the blank path issue unless the CUDAPATH is introduced
(in the terminal)
For example if Cuda 11.7 is installed:
CUDAPATH=/usr/local/cuda- 11.7
export PATH=/usr/local/cuda- 11.7/bin${PATH: + ${PATH}}
export_LD_LIBRARY_PATH=/usr/local/cuda- 11.7/lib64\ ${LD_LIBRARY_PATH: +
:${LD_LIBRARY_PATH}}
and make config within cd '/usr/local/SuiteSparse-5.13.0'
gives
CUDA root directory: CUDA PATH=/usr/local/cuda-11.7
.
.
.
Cuda library:CUDART_LIB=/usr/local/cuda-11.7/lib64/libcudart.so
CUBLAS library: CUBLAS_LIB=/usr/local/cuda-11.7/lib64/libcublas.so
I am able to compile SuiteSparse-5.13.0 by make after this but am not sure if
the provided paths are correct.
(2) Regarding manual entry of CUDA_PATH in SuitSparse_Config.mk if this
is the first few lines for #NVIDIA CUDA configuration for CHOLMOD and
SPQR
CUDA=auto
if fneq ($(CUDA), no)
CUDA_PATH= $(shell which nvcc 2>/dev/null | sed "s/ \ /bin\ /nvcc//")
else
CUDA_PATH=
Manual entry of the CUDA_PATH (enforcing all conditions to point to the
location of installed Cuda)
CUDA=auto
if fneq ($(CUDA), no)
CUDA_PATH= /usr/local/cuda-11.7
else
CUDA_PATH=/usr/local/cuda-11.7
Leads to the similar result as (1)
Is this the appropriate approach for manual change of SuitSparse_Config.mk or
I need to point to another directory (for example cuda itself-- not cuda 11.7?
Please advise
I have been able to verify the accuracy of compilation by executing sh
gpu.sh within SuiteSparse/CHOLMOD/Demo.
3- Here is the cmake command I use for compiling yade:
cmake -DCMAKE_INSTALL_PREFIX=../install ../trunk -DCHOLMOD_GPU=ON
-DSUITESPARSEPATH=/usr/local/SuiteSparse-5.13.0
Cmake finds the paths as recommended in YADE manual but the paths are
not the ones I introduce either in SuitSparse_Config.mk or in the
terminal. Also, multiple identical paths are reported for the same
CHOLMOD (and dependencies such as AMD), SuiteSparse, CuBlas, and Metis.
I feel something is wrong here.
BTW, I can compile YADE with this approach but when I run YADE executable, I
get segmentation fault (core dumped).
Similar deployment on an Azure VM gives another error.
3- I'm now working on your comment for Cuda 9.0 but need to know which trunk
version (for YADE compilation) is compatible with this installation. Also, how
important is finding Nvidia 384.11 GPU drivers? Basically, how can I enforce
to install this specific version?
Thanks so much
Nima
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Re: [Yade-users] [Question #703335]: Setting Up GPU
Question #703335 on Yade changed: https://answers.launchpad.net/yade/+question/703335 Status: Open => Answered Robert Caulk proposed the following answer: Hey, Have you tried downloading the versions of CUDA and suitesparse mentioned in [1]? Notably: Suite-sparse 4.6.0-beta CUDA 9.0 Nvidia 384.11 GPU drivers In the CUDA install you will find the samples folder indicated in [2]. Your question: >> Question: Is extracting to usr/local mandatory? No it is in-fact not mandatory. Try extracting to your /home/ folder instead. >> the paths are blank for CUDART_LIB= and CUBLAS_LIB= which is not a good sign Yes, it is not a good sign. But you should be able to navigate and find these libraries manually inside the cuda-9.0/lib64 folder (please verify that they do exist ). Then you can put that path in SuiteSparse_config.mk directly. Please keep me updated. Cheers, Robert [1] https://www.sciencedirect.com/science/article/abs/pii/S0010465519303340 [2] https://yade-dev.gitlab.io/trunk/GPUacceleration.html#accelerating-yade-s-flowengine-with-gpu -- You received this question notification because your team yade-users is an answer contact for Yade. ___ Mailing list: https://launchpad.net/~yade-users Post to : yade-users@lists.launchpad.net Unsubscribe : https://launchpad.net/~yade-users More help : https://help.launchpad.net/ListHelp
[Yade-users] [Question #703335]: Setting Up GPU
New question #703335 on Yade: https://answers.launchpad.net/yade/+question/703335 Hi there, I'm trying to set up GPU following https://yade-dev.gitlab.io/trunk/GPUacceleration.html#install-suitesparse. I have encountered doing so. Two main issues are: 1- After installation of Cuda, the samples folder is not generated within the Cuda directory (/usr/local/Cuda/Samples). Therefore, I have to download the Cuda Samples by git clone https://github.com/NVIDIA/cuda-samples.git and then compiling within Samples folder. Running ./deviceQuery inside'/Samples/1_Utilities/deviceQuery' seems satisfactory giving: ./deviceQuery Starting... CUDA Device Query (Runtime API) version (CUDART static linking) Detected 1 CUDA Capable device(s) Device 0: "Quadro P2200" CUDA Driver Version / Runtime Version 11.7 / 11.7 CUDA Capability Major/Minor version number:6.1 Total amount of global memory: 5051 MBytes (5296029696 bytes) (010) Multiprocessors, (128) CUDA Cores/MP:1280 CUDA Cores GPU Max Clock rate:1493 MHz (1.49 GHz) Memory Clock rate: 5005 Mhz Memory Bus Width: 160-bit L2 Cache Size: 1310720 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:98304 bytes Total number of registers available per block: 65536 Warp size: 32 Maximum number of threads per multiprocessor: 2048 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 2 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: Yes Device PCI Domain ID / Bus ID / location ID: 0 / 101 / 0 Compute Mode: < Default (multiple host threads can use ::cudaSetDevice() with device simultaneously) > deviceQuery, CUDA Driver = CUDART, CUDA Driver Version = 11.7, CUDA Runtime Version = 11.7, NumDevs = 1 Result = PASS Is this the right approach for testing the Cuda installation for the most recent version? I'm not aware if the Samples folder had been generated for eralier versions inside the Cuda directory itself. I, then, run sudo apt-get install libopenblas-dev liblapack-dev 2- Following the instruction, I download the latest version of SuiteSparse package (5.13.0) and extracted it to usr/local folder using sudo (Question: Is extracting to usr/local mandatory?). Therefore, there is a /usr/local/SuiteSparse-5.13.0 directory from which I run make config within this directory gives: SuiteSparse package compilation options: SuiteSparse Version: 5.13.0 SuiteSparse top folder: /usr/local/SuiteSparse-5.13.0 Package: LIBRARY= PackageNameWillGoHere Version: VERSION= x.y.z SO version: SO_VERSION= x System: UNAME= Linux Install directory:INSTALL= /usr/local/SuiteSparse-5.13.0 Install libraries in: INSTALL_LIB= /usr/local/SuiteSparse-5.13.0/lib Install include files in: INSTALL_INCLUDE= /usr/local/SuiteSparse-5.13.0/include Install documentation in: INSTALL_DOC= /usr/local/SuiteSparse-5.13.0/share/doc/suitesparse-5.13.0 Optimization level: OPTIMIZATION=-O3 parallel make jobs: JOBS=8 BLAS library: BLAS=-lblas LAPACK library: LAPACK= -llapack Other libraries: LDLIBS= -lm -lrt static library: AR_TARGET= PackageNameWillGoHere.a shared library (full):SO_TARGET= PackageNameWillGoHere.so.x.y.z shared library (main):SO_MAIN= PackageNameWillGoHere.so.x shared library (short): SO_PLAIN=PackageN
