CUDA DEVICEQUERY返回代替1- 2

設備：2張780Ti卡，軟件：的Ubuntu 14.01 LTS NVIDIA UNIX x86_64的內核模塊352.79星期三年01月13 16點17分53秒PST 2016 GCC版本：gcc版本4.8.4（ Ubuntu的4.8.4-2ubuntu1〜14.04.1） CUDA 7.5CUDA DEVICEQUERY返回代替1- 2

NVIDIA-SMI節目

+------------------------------------------------------+      
| NVIDIA-SMI 352.79  Driver Version: 352.79   |      
|-------------------------------+----------------------+----------------------+ 
| GPU Name  Persistence-M| Bus-Id  Disp.A | Volatile Uncorr. ECC | 
| Fan Temp Perf Pwr:Usage/Cap|   Memory-Usage | GPU-Util Compute M. | 
|===============================+======================+======================| 
| 0 GeForce GTX 780 Ti Off | 0000:01:00.0  N/A |     N/A | 
| 30% 43C P2 N/A/N/A | 877MiB/3071MiB |  N/A  Default | 
+-------------------------------+----------------------+----------------------+ 
| 1 GeForce GTX 780 Ti Off | 0000:03:00.0  N/A |     N/A | 
| 29% 25C P8 N/A/N/A |  11MiB/3071MiB |  N/A  Default | 
+-------------------------------+----------------------+----------------------+

DEVICEQUERY顯示

CUDA Device Query (Runtime API) version (CUDART static linking) 

Detected 1 CUDA Capable device(s) 

Device 0: "GeForce GTX 780 Ti" 
    CUDA Driver Version/Runtime Version   7.5/7.5 
    CUDA Capability Major/Minor version number: 3.5 
    Total amount of global memory:     3072 MBytes (3221028864 bytes) 
    (15) Multiprocessors, (192) CUDA Cores/MP:  2880 CUDA Cores 
    GPU Max Clock rate:       1084 MHz (1.08 GHz) 
    Memory Clock rate:        3500 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 1 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:      Disabled 
    Device supports Unified Addressing (UVA):  Yes 
    Device PCI Domain ID/Bus ID/location ID: 0/3/0 
    Compute Mode: 
    < Default (multiple host threads can use ::cudaSetDevice() with device simultaneously) > 

deviceQuery, CUDA Driver = CUDART, CUDA Driver Version = 7.5, CUDA Runtime Version = 7.5, NumDevs = 1, Device0 = GeForce GTX 780 Ti 
Result = PASS

在/ dev目錄NVIDIA文件3210

權限是：

crw-rw-rw- 1 root root 195, 0 Apr 3 21:18 nvidia0 
crw-rw-rw- 1 root root 195, 1 Apr 3 21:18 nvidia1 
crw-rw-rw- 1 root root 195, 255 Apr 3 21:18 nvidiactl 
crw-rw-rw- 1 root root 244, 0 Apr 3 21:24 nvidia-uvm

爲什麼DEVICEQUERY只顯示1個GPU？

來源

2016-04-04 aquagremlin

你是否在nvidia驅動之後安裝了第二張卡？我很好奇P8/P2的狀態。如果可能是那個司機沒有管理這兩張卡片。安裝新的驅動程序可能有幫 –

這個問題對於[SO]是完全偏離主題的，我已經投了票關閉它 – talonmies

-1

只是一個猜測，但你有任何機會有CUDA_VISIBLE_DEVICES propery設置？

http://www.resultsovercoffee.com/2011/02/cudavisibledevices.html

來源

2016-04-04 02:19:05

嘗試了這兩種方式 - 沒有設置環境變量並將該環境變量設置爲1（deviceQuery看不到的卡）。但是，我認爲問題是deviceQuery，因爲當我使用nvidia-smi -l 1監視性能時--query --display = PERFORMANCE --filename = gpu_utillization.log當我運行cuda編譯時，我看到了兩個卡的性能狀態發生了變化應用程序像粒子。 – aquagremlin

您是否嘗試將其設置爲「」0,1「'？ –

是的，我試過「0,1」，也是0,1。看到這個http://askubuntu.com/questions/752534/assign-cuda-to-a-specific-gpu/753544#753544但即使當我將env變量設置爲'1'時，我仍然看到兩張卡都提高了性能。我不知道SLI橋是否讓人感到困惑？ – aquagremlin

-2

事實證明，大部分的CUDA樣品根本不編碼爲使用兩張卡。如果編碼正確，則使用兩個gpus。

來源

2016-05-16 20:19:34 aquagremlin

據我所知，設備查詢的目的是查看所有卡。你有另一個樣本嗎？ –

CUDA DEVICEQUERY返回代替1- 2

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