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Message #28388
[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= PackageNameWillGoHere.so
shared library options: SO_OPTS= -L/usr/local/SuiteSparse-5.13.0/lib -Wl,-rpath=/usr/local/SuiteSparse-5.13.0/lib -shared -Wl,-soname -Wl,PackageNameWillGoHere.so.x -Wl,--no-undefined -Wl,-rpath, -Wl,-z,origin
shared library name tool: SO_INSTALL_NAME= echo
ranlib, for static libs: RANLIB= ranlib
static library command: ARCHIVE= ar rv
copy file: CP= cp -f
move file: MV= mv -f
remove file: RM= rm -f
pretty (for Tcov tests): PRETTY= grep -v "^#" | indent -bl -nce -bli0 -i4 -sob -l120
C compiler: CC= cc
C++ compiler: CXX= g++
CUDA enabled: CUDA= auto
CUDA compiler: NVCC= echo
CUDA root directory: CUDA_PATH=
OpenMP flags: CFOPENMP= -fopenmp
C/C++ compiler flags: CF= -O3 -fexceptions -fPIC -fopenmp
LD flags: LDFLAGS= -L/usr/local/SuiteSparse-5.13.0/lib -Wl,-rpath=/usr/local/SuiteSparse-5.13.0/lib
Fortran compiler: F77= f77
Fortran flags: F77FLAGS=
Intel MKL root: MKLROOT=
Auto detect Intel icc: AUTOCC= no
UMFPACK config: UMFPACK_CONFIG=
CHOLMOD config: CHOLMOD_CONFIG=
SuiteSparseQR config: SPQR_CONFIG=
CUDA library: CUDART_LIB=
CUBLAS library: CUBLAS_LIB=
METIS and CHOLMOD/Partition configuration:
Your METIS library: MY_METIS_LIB=
Your metis.h is in: MY_METIS_INC=
METIS is used via the CHOLMOD/Partition module, configured as follows.
If the next line has -DNPARTITION then METIS will not be used:
CHOLMOD Partition config:
CHOLMOD Partition libs: -lccolamd -lcamd -lmetis
CHOLMOD Partition include: -I/usr/local/SuiteSparse-5.13.0/CCOLAMD/Include -I/usr/local/SuiteSparse-5.13.0/CAMD/Include -I/usr/local/SuiteSparse-5.13.0/metis-5.1.0/include
MAKE: make
CMake options: -DCMAKE_INSTALL_PREFIX=/usr/local/SuiteSparse-5.13.0 -DCMAKE_CXX_COMPILER=g++ -DCMAKE_C_COMPILER=cc
As observed, the paths are blank for CUDART_LIB= and CUBLAS_LIB= which is not a good sign.
My effort for manual pointing to the Cuda directory in /usr/local/SuiteSparse/SuiteSparse_config/SuiteSparse_config.mk were not successful.
What is wrong with my implementation?
Cheers
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