运行 AWS g2.2xlarge 上的 cudaHashcat-1.33 - 尝试时出现错误 cuModuleLoad() 209 cudaExample0.sh
Running cudaHashcat-1.33 on AWS g2.2xlarge - Error cuModuleLoad() 209 when trying cudaExample0.sh
正如描述中所说,我已经在 AWS g2.2xlarge 实例上安装了 cudaHashcat-1.33。
我使用 .运行 文件安装了 CUDA 工具包,然后执行了这个测试:deviceQuery;如官方文档中所述 (http://docs.nvidia.com/cuda/cuda-getting-started-guide-for-linux/index.html#running-binaries).
然后我按照这些说明安装了 cudaHashcat-1.33。
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
然后我尝试 运行 这个: cudaExample0.sh
在 ~/cudaHashcat-1.33/cudaExample0.sh
中,我最终得到这个输出:
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
第二个例子是这个,我实际使用了我想要攻击的文件。
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
[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 |
+-----------------------------------------------------------------------------+
如果有人知道发生了什么,我将不胜感激。
所以在论坛中进行了大量搜索后,我终于找到了答案。 @Robert Crovella,感谢您指出 driver 是错误的。所以事实证明,为 NVIDIA 找到 linux driver 并不容易,但我遇到了这个 page, which then lead me to the Linux Drivers of NVIDIA。只需下载您的体系结构所需的 driver(如果您使用 wget,请先单击 'Download',因为有一个接受页面)。之后执行 'chmod +x nvidia-driver.run' 然后使用 'sudo ./nvidia-driver.run'.
安装它
希望我的经验对其他人有所帮助。
正如描述中所说,我已经在 AWS g2.2xlarge 实例上安装了 cudaHashcat-1.33。
我使用 .运行 文件安装了 CUDA 工具包,然后执行了这个测试:deviceQuery;如官方文档中所述 (http://docs.nvidia.com/cuda/cuda-getting-started-guide-for-linux/index.html#running-binaries).
然后我按照这些说明安装了 cudaHashcat-1.33。
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
然后我尝试 运行 这个: cudaExample0.sh
在 ~/cudaHashcat-1.33/cudaExample0.sh
中,我最终得到这个输出:
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
第二个例子是这个,我实际使用了我想要攻击的文件。
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
[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 |
+-----------------------------------------------------------------------------+
如果有人知道发生了什么,我将不胜感激。
所以在论坛中进行了大量搜索后,我终于找到了答案。 @Robert Crovella,感谢您指出 driver 是错误的。所以事实证明,为 NVIDIA 找到 linux driver 并不容易,但我遇到了这个 page, which then lead me to the Linux Drivers of NVIDIA。只需下载您的体系结构所需的 driver(如果您使用 wget,请先单击 'Download',因为有一个接受页面)。之后执行 'chmod +x nvidia-driver.run' 然后使用 'sudo ./nvidia-driver.run'.
安装它希望我的经验对其他人有所帮助。