I got a problem at installation of two tesla cards. Acturally, they worked well previously, but one of them cannot be recognized after reinstall of windows. Two of them can be recognized by nvidia-smi.exe, but I can use only one. How can I use them all? Is there any procedure to set up multiple GPUs? I attached the outputs of nvidia-smi and devicequery.
C:\Program Files\NVIDIA Corporation\NVSMI>nvidia-smi.exe
Tue Jul 26 16:43:11 2016
+------------------------------------------------------+
| NVIDIA-SMI 358.91 Driver Version: 358.91 |
|-------------------------------+----------------------+----------------------+
| GPU Name TCC/WDDM | Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
|===============================+======================+======================|
| 0 ERR! TCC* | ERR! N/A | N/A |
|ERR! ERR! ERR! N/A / N/A | Unknown Error | N/A ERR! |
+-------------------------------+----------------------+----------------------+
| 1 Tesla K40m TCC | 0000:03:00.0 Off | 0 |
| N/A 24C P8 20W / 235W | 25MiB / 11519MiB | 0% Default |
+-------------------------------+----------------------+----------------------+
| 2 Tesla K40m TCC | 0000:83:00.0 Off | 0 |
| N/A 25C P8 20W / 235W | 25MiB / 11519MiB | 0% Default |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: GPU Memory |
| GPU PID Type Process name Usage |
|=============================================================================|
| 0 Not Supported |
+-----------------------------------------------------------------------------+
C:\Program Files\NVIDIA Corporation\Installer2\CUDASamples_6.5.{5C64BCE6-CAC8-43
92-AB3F-CC5E72544DA6}\bin\win64\Release>deviceQuery.exe
deviceQuery.exe Starting...
CUDA Device Query (Runtime API) version (CUDART static linking)
Detected 1 CUDA Capable device(s)
Device 0: "Tesla K40m"
CUDA Driver Version / Runtime Version 7.5 / 6.5
CUDA Capability Major/Minor version number: 3.5
Total amount of global memory: 11520 MBytes (12079398912 bytes
)
(15) Multiprocessors, (192) CUDA Cores/MP: 2880 CUDA Cores
GPU 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
CUDA Device Driver Mode (TCC or WDDM): TCC (Tesla Compute Cluster Driv
er)
Device supports Unified Addressing (UVA): Yes
Device PCI Bus ID / PCI location ID: 3 / 0
Compute Mode:
< Default (multiple host threads can use ::cudaSetDevice() with device simu
ltaneously) >
deviceQuery, CUDA Driver = CUDART, CUDA Driver Version = 7.5, CUDA Runtime Versi
on = 6.5, NumDevs = 1, Device0 = Tesla K40m
Result = PASS