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hashcat for NVIDIA K10 card - Printable Version

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hashcat for NVIDIA K10 card - rocr - 12-18-2019

Hello,

will hashcat work on "NVIDIA Corporation GK104GL [Tesla K10] (rev a1)" cards?
(or is there a version that does?)

thanks,

Ron


RE: hashcat for NVIDIA K10 card - slyexe - 12-18-2019

(12-18-2019, 03:21 AM)rocr Wrote: Hello,

will hashcat work on "NVIDIA Corporation GK104GL [Tesla K10] (rev a1)" cards?
(or is there a version that does?)

thanks,

Ron

If it has OpenCL it should be compatible. Most Nvidia cards have no issues, I would suggest using latest beta for best results.

https://hashcat.net/beta/


RE: hashcat for NVIDIA K10 card - rocr - 12-18-2019

(12-18-2019, 05:17 AM)slyexe Wrote:
(12-18-2019, 03:21 AM)rocr Wrote: Hello,

will hashcat work on "NVIDIA Corporation GK104GL [Tesla K10] (rev a1)" cards?
(or is there a version that does?)

thanks,

Ron

If it has OpenCL it should be compatible. Most Nvidia cards have no issues, I would suggest using latest beta for best results.

https://hashcat.net/beta/

Alright, I'll try that.  I was just wondering because when I start "example0.sh", I get to see this below, I was wondering if there is a specific version for the hardware I have. When running NVIDIA examples/tests, I don't see anything out of the ordinary.

Ron

(Also, I was readin some 'generic' hashcat stuff and saw there is a might be a gui front end?_


The fan msgs I understand, there are no integrated fans, the chassis does the cooling

[rocr@cuda hashcat-5.1.0]$ ./example0.sh
hashcat (v5.1.0) starting...

* Device #1: This hardware has outdated CUDA compute capability (3.0).
            For modern OpenCL performance, upgrade to hardware that supports
            CUDA compute capability version 5.0 (Maxwell) or higher.
* Device #2: This hardware has outdated CUDA compute capability (3.0).
            For modern OpenCL performance, upgrade to hardware that supports
            CUDA compute capability version 5.0 (Maxwell) or higher.
* Device #3: This hardware has outdated CUDA compute capability (3.0).
            For modern OpenCL performance, upgrade to hardware that supports
            CUDA compute capability version 5.0 (Maxwell) or higher.
* Device #4: This hardware has outdated CUDA compute capability (3.0).
            For modern OpenCL performance, upgrade to hardware that supports
            CUDA compute capability version 5.0 (Maxwell) or higher.
nvmlDeviceGetFanSpeed(): Not Supported

nvmlDeviceGetFanSpeed(): Not Supported

nvmlDeviceGetFanSpeed(): Not Supported

nvmlDeviceGetFanSpeed(): Not Supported

OpenCL Platform #1: NVIDIA Corporation
======================================
* Device #1: Tesla K10.G1.8GB, 881/3527 MB allocatable, 8MCU
* Device #2: Tesla K10.G1.8GB, 881/3527 MB allocatable, 8MCU
* Device #3: Tesla K10.G1.8GB, 881/3527 MB allocatable, 8MCU
* Device #4: Tesla K10.G1.8GB, 881/3527 MB allocatable, 8MCU

Dictionary cache hit:
* Filename..: example.dict
* Passwords.: 128416
* Bytes.....: 1069601
* Keyspace..: 128416

Hashes: 6494 digests; 6494 unique digests, 1 unique salts
Bitmaps: 16 bits, 65536 entries, 0x0000ffff mask, 262144 bytes, 5/13 rotates

Applicable optimizers:
* Zero-Byte
* Early-Skip
* Not-Salted
* Not-Iterated
* Single-Salt
* Raw-Hash

Minimum password length supported by kernel: 0
Maximum password length supported by kernel: 256

ATTENTION! Pure (unoptimized) OpenCL kernels selected.
This enables cracking passwords and salts > length 32 but for the price of drastically reduced performance.
If you want to switch to optimized OpenCL kernels, append -O to your commandline.

Watchdog: Temperature abort trigger set to 90c

INFO: Removed 2237 hashes found in potfile.

Dictionary cache hit:
* Filename..: example.dict
* Passwords.: 128416
* Bytes.....: 1069601
* Keyspace..: 134653935616

Cracking performance lower than expected?       

* Append -O to the commandline.
  This lowers the maximum supported password- and salt-length (typically down to 32).

* Append -w 3 to the commandline.
  This can cause your screen to lag.

* Update your OpenCL runtime / driver the right way:
  https://hashcat.net/faq/wrongdriver

* Create more work items to make use of your parallelization power:
  https://hashcat.net/faq/morework

Approaching final keyspace - workload adjusted.