[Pw_forum] QE-GPU (installation)
Phanikumar Pentyala
phani12.chem at gmail.com
Tue Dec 6 05:50:18 CET 2016
Here I am attaching my SERVER architecture and GPU device enquiry (text
file)
After whole long day I found some reasons (I don't know whether they are
correct or not ):
Initially I written my GPU was Tesla K40, but it is not. Actual series name
was *NVIDIA Tesla K40m. *Sorry for that, that was my mistake
>From "README" file in software, *NVIDIA Tesla K40m *was not mentioned. Is
that any problem?
If I try compilation with QE-5.3.0, It was different error (*config.status:
error: cannot find input file: ../include/fft_defs.h.in
<http://fft_defs.h.in>*)
Also, Intel® math kernel library (MKL) and Intel® Message Passing Interface
(MPI) library installation required or not?
Thank you once again
Regarrds
Phanikumar
On Tue, Dec 6, 2016 at 12:02 AM, Filippo SPIGA <
filippo.spiga at quantum-espresso.org> wrote:
> On Dec 5, 2016, at 2:11 PM, Phanikumar Pentyala <phani12.chem at gmail.com>
> wrote:
> > After change the compilation command: ./configure --enable-parallel
> --enable-openmp --with-scalapack --enable-cuda --with-gpu-arch=sm_35
> --with-cuda-dir=/usr/local/cuda-8.0/bin --without-magma --with-phigemm
> (now I changed with scalapack)
>
> You have a single server with 2 K40 right? No point of using ScaLAPACK for
> only 2 MPI processes, please disable scaLAPACk and enable MAGMA.
>
>
> > configure: error: Cannot compile against this version of Quantum
> ESPRESSO. Use v5.4
>
> Weird, it shoudl work. I tested it multiple time a month ago in my system.
> I will look into this or this night or tomorrow and get back to you.
>
> --
> Filippo SPIGA ~ Quantum ESPRESSO Foundation ~ http://www.quantum-espresso.
> org
>
>
> _______________________________________________
> Pw_forum mailing list
> Pw_forum at pwscf.org
> http://pwscf.org/mailman/listinfo/pw_forum
>
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://lists.quantum-espresso.org/pipermail/users/attachments/20161206/c7903bfe/attachment.html>
-------------- next part --------------
##################################################################################################################################################
SERVER architecture information (from "lscpu" command in terminal)
##################################################################################################################################################
Architecture: x86_64
CPU op-mode(s): 32-bit, 64-bit
Byte Order: Little Endian
CPU(s): 40
On-line CPU(s) list: 0-39
Thread(s) per core: 2
Core(s) per socket: 10
Socket(s): 2
NUMA node(s): 2
Vendor ID: GenuineIntel
CPU family: 6
Model: 79
Model name: Intel(R) Xeon(R) CPU E5-2640 v4 @ 2.40GHz
Stepping: 1
CPU MHz: 1200.000
BogoMIPS: 4788.53
Virtualization: VT-x
L1d cache: 32K
L1i cache: 32K
L2 cache: 256K
L3 cache: 25600K
NUMA node0 CPU(s): 0-9,20-29
NUMA node1 CPU(s): 10-19,30-39
##################################################################################################################################################
After I run device quiry in CUDA_samples I got this information about my GPU accelerators
##################################################################################################################################################
Detected 2 CUDA Capable device(s)
Device 0: "Tesla K40m"
CUDA Driver Version / Runtime Version 8.0 / 8.0
CUDA Capability Major/Minor version number: 3.5
Total amount of global memory: 11440 MBytes (11995578368 bytes)
(15) Multiprocessors, (192) CUDA Cores/MP: 2880 CUDA Cores
GPU Max Clock rate: 745 MHz (0.75 GHz)
Memory Clock rate: 3004 Mhz
Memory Bus Width: 384-bit
L2 Cache Size: 1572864 bytes
Maximum Texture Dimension Size (x,y,z) 1D=(65536), 2D=(65536, 65536), 3D=(4096, 4096, 4096)
Maximum Layered 1D Texture Size, (num) layers 1D=(16384), 2048 layers
Maximum Layered 2D Texture Size, (num) layers 2D=(16384, 16384), 2048 layers
Total amount of constant memory: 65536 bytes
Total amount of shared memory per block: 49152 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: No
Integrated GPU sharing Host Memory: No
Support host page-locked memory mapping: Yes
Alignment requirement for Surfaces: Yes
Device has ECC support: Enabled
Device supports Unified Addressing (UVA): Yes
Device PCI Domain ID / Bus ID / location ID: 0 / 2 / 0
Compute Mode:
< Default (multiple host threads can use ::cudaSetDevice() with device simultaneously) >
Device 1: "Tesla K40m"
CUDA Driver Version / Runtime Version 8.0 / 8.0
CUDA Capability Major/Minor version number: 3.5
Total amount of global memory: 11440 MBytes (11995578368 bytes)
(15) Multiprocessors, (192) CUDA Cores/MP: 2880 CUDA Cores
GPU Max Clock rate: 745 MHz (0.75 GHz)
Memory Clock rate: 3004 Mhz
Memory Bus Width: 384-bit
L2 Cache Size: 1572864 bytes
Maximum Texture Dimension Size (x,y,z) 1D=(65536), 2D=(65536, 65536), 3D=(4096, 4096, 4096)
Maximum Layered 1D Texture Size, (num) layers 1D=(16384), 2048 layers
Maximum Layered 2D Texture Size, (num) layers 2D=(16384, 16384), 2048 layers
Total amount of constant memory: 65536 bytes
Total amount of shared memory per block: 49152 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: No
Integrated GPU sharing Host Memory: No
Support host page-locked memory mapping: Yes
Alignment requirement for Surfaces: Yes
Device has ECC support: Enabled
Device supports Unified Addressing (UVA): Yes
Device PCI Domain ID / Bus ID / location ID: 0 / 129 / 0
Compute Mode:
< Default (multiple host threads can use ::cudaSetDevice() with device simultaneously) >
> Peer access from Tesla K40m (GPU0) -> Tesla K40m (GPU1) : No
> Peer access from Tesla K40m (GPU1) -> Tesla K40m (GPU0) : No
deviceQuery, CUDA Driver = CUDART, CUDA Driver Version = 8.0, CUDA Runtime Version = 8.0, NumDevs = 2, Device0 = Tesla K40m, Device1 = Tesla K40m
Result = PASS
More information about the users
mailing list