因为它说，在一个AWS g2.2xlarge比如我已经安装了cudaHashcat-1.33的说明。

As it says in the description I have installed cudaHashcat-1.33 on an AWS g2.2xlarge instance.

我用的。运行文件，安装CUDA工具包，然后进行一下测试：DEVICEQUERY;这里介绍的官方文档（的http://docs.nvidia.com/cuda/cuda-getting-started-guide-for-linux/index.html#running-binaries).

I've used the .run file to install the CUDA Toolkit and then performed this test: deviceQuery ; as explained here in the official documentation (http://docs.nvidia.com/cuda/cuda-getting-started-guide-for-linux/index.html#running-binaries).

然后我安装cudaHashcat-1.33，按照以下说明。

Then I installed cudaHashcat-1.33, following these instructions.

sudo apt-get install p7zip-full
wget http://hashcat.net/files/cudaHashcat-1.33.7z
7za x cudaHashcat-1.33.7z
cd cudaHashcat-1.33

然后我试图运行这样的：〜/ cudaExample0.sh cudaHashcat-1.33 / cudaExample0.sh 和我最终得到这样的输出：

Then I tried to run this: cudaExample0.sh in ~/cudaHashcat-1.33/cudaExample0.sh and I end up getting this output:

cudaHashcat v1.33 starting...

Device #1: GRID K520, 4095MB, 797Mhz, 8MCU
Device #1: WARNING! Kernel exec timeout is not disabled, it might cause you errors of code 702

Hashes: 6494 hashes; 6494 unique digests, 1 unique salts
Bitmaps: 16 bits, 65536 entries, 0x0000ffff mask, 262144 bytes
Applicable Optimizers:
* Zero-Byte
* Precompute-Init
* Precompute-Merkle-Demgard
* Meet-In-The-Middle
* Early-Skip
* Not-Salted
* Not-Iterated
* Single-Salt
* Scalar-Mode
* Raw-Hash
Watchdog: Temperature abort trigger set to 90c
Watchdog: Temperature retain trigger set to 80c


ERROR: cuModuleLoad() 209

第二个例子是这样的，在这里我实际使用我想攻击文件。

A second example is this one, where I actually use the file I want to attack.

ubuntu@ip-172-31-58-154:~$ ~/maskprocessor/src/mp64.bin ?l?l?l?l?l?l?l?l | ~/cudaHashcat-1.33/cudaHashcat64.bin -m 2500 xxx.hccap
cudaHashcat v1.33 starting...

Device #1: GRID K520, 4095MB, 797Mhz, 8MCU
Device #1: WARNING! Kernel exec timeout is not disabled, it might cause you errors of code 702

Hashes: 1 hashes; 1 unique digests, 1 unique salts
Bitmaps: 8 bits, 256 entries, 0x000000ff mask, 1024 bytes
Rules: 1
Applicable Optimizers:
* Zero-Byte
* Single-Hash
* Single-Salt
Watchdog: Temperature abort trigger set to 90c
Watchdog: Temperature retain trigger set to 80c


ERROR: cuModuleLoad() 209

NVIDIA-SMI 的

[root@ip-xxx-xxx-xxx-xxx cudaHashcat-1.33]$ nvidia-smi
Wed Mar  4 19:07:35 2015       
+------------------------------------------------------+                       
| NVIDIA-SMI 340.32     Driver Version: 340.32         |                       
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|===============================+======================+======================|
|   0  GRID K520           On   | 0000:00:03.0     Off |                  N/A |
| N/A   43C    P8    17W / 125W |     10MiB /  4095MiB |      0%      Default |
+-------------------------------+----------------------+----------------------+

+-----------------------------------------------------------------------------+
| Compute processes:                                               GPU Memory |
|  GPU       PID  Process name                                     Usage      |
|=============================================================================|
|  No running compute processes found                                         |
+-----------------------------------------------------------------------------+

如果有人知道是怎么回事，我倒是AP preciate任何帮助。

If someone knows what is going on, I'd appreciate any help.

推荐答案

所以在很多通过论坛搜索，我终于找到了答案。 @Robert Crovella，感谢您指出的驱动力是错误的。所以，事实证明，找到Linux驱动程序的NVIDIA并不容易，但我遇到了这个的页面，然后带我到 NVIDIA 的Linux的驱动程序。只要下载所需的架构的驱动程序（如果你使用wget点击下载第一，因为有一个接受页）。之后，做'搭配chmod + X NVIDIA-driver.run，然后用须藤./nvidia-driver.run。安装

So after a lot of searching through forums I finally found an answer. @Robert Crovella, thanks for pointing out that the driver was the wrong one. So it turns out that finding the linux drivers for NVIDIA is not that easy, but I came across this page, which then lead me to the Linux Drivers of NVIDIA. Just download the driver required for your architecture (if you use wget click on 'Download' first, since there is an acceptance page). After that do 'chmod +x nvidia-driver.run' and then install it with 'sudo ./nvidia-driver.run'.

希望我的经验可以帮助别人。

Hope that my experience helps someone else.