CUDA 11 has been swapped with CUDA 8.
Same type of errors appear using Hashcat 5.0 as with 4.0.
There are notable differences with 5.0 compared to 4.0 and 3.0. With 5.0 I get anywhere between 170 and 400 MH/s whereas with 4.0 I only get 270 MH/s at most but consistently in that ballpark (and 900 to 930 MH/s with 3.0). Also, the fans are spinning a bit faster when hashrate reaches 400 MH/s, they go up to 45% compared to 25% or so with version 4.0 and 3.0. This is probably because temperature thresholds are set set differently. The temperature never reaches 70 degrees C, whereas with version 4.0 and 3.0 it's allowed to go as high as 75 C (with fans at around 25% at most).
As for 6.2.5, it doesn't work at all.
I no longer have any expectations to see it work, knowing now that it requires CUDA 9. But that's related to using CUDA runtime rather than Open CL if I am not mistaken. The reason it totally fails to work at all, even in Open CL mode (the fallback mode) seems to be related memory limitations of the GPU. There is only 1 GB of GDDR5.
I'm not sure why it works in 3.0, 4.0 and 5.0 then. Version 3.0 is also using Open CL.
Note that 6.2.5 indicated that 704/1024 MB is allocatable, compared to 256/1024 MB for 3.0. This seems contradictory, for it would seem as if the current version requires more GPU memory. I don't know how much more or why the latest version would need more memory, but 2 GB would seem like a good minimum to look for in a new budget or outdated GPU for use with Hashcat.
Correction: The reason 6.2.5 doesn't work with GTX 560 Ti is more likely because of Open CL. Does 6.2.5 require Open CL 1.2? I see it listed in the string "OpenCL 1.2 CUDA 9.1.84" when Hashcart 6.2.5 is started. If this is the case then it would make sense why it fails, if the GTX 560 Ti only has Open CL 1.1 support. So it can't use CUDA and it can't use Open CL, and therefore it will not work.
Same type of errors appear using Hashcat 5.0 as with 4.0.
Code:
* Device #1: This hardware has outdated CUDA compute capability (2.1).
For modern OpenCL performance, upgrade to hardware that supports
CUDA compute capability version 5.0 (Maxwell) or higher.
* Device #1: WARNING! Kernel exec timeout is not disabled.
This may cause "CL_OUT_OF_RESOURCES" or related errors.
To disable the timeout, see: https://hashcat.net/q/timeoutpatch
nvmlDeviceGetCurrPcieLinkWidth(): Not Supported
nvmlDeviceGetClockInfo(): Not Supported
nvmlDeviceGetClockInfo(): Not Supported
nvmlDeviceGetTemperatureThreshold(): Not Supported
nvmlDeviceGetTemperatureThreshold(): Not Supported
nvmlDeviceGetUtilizationRates(): Not Supported
OpenCL Platform #1: NVIDIA Corporation
======================================
* Device #1: GeForce GTX 560 Ti, 256/1024 MB allocatable, 8MCUThere are notable differences with 5.0 compared to 4.0 and 3.0. With 5.0 I get anywhere between 170 and 400 MH/s whereas with 4.0 I only get 270 MH/s at most but consistently in that ballpark (and 900 to 930 MH/s with 3.0). Also, the fans are spinning a bit faster when hashrate reaches 400 MH/s, they go up to 45% compared to 25% or so with version 4.0 and 3.0. This is probably because temperature thresholds are set set differently. The temperature never reaches 70 degrees C, whereas with version 4.0 and 3.0 it's allowed to go as high as 75 C (with fans at around 25% at most).
As for 6.2.5, it doesn't work at all.
Code:
hashcat (v6.2.5) starting
Successfully initialized NVIDIA CUDA library.
Failed to initialize NVIDIA RTC library.
* Device #1: CUDA SDK Toolkit not installed or incorrectly installed.
CUDA SDK Toolkit required for proper device support and utilization.
Falling back to OpenCL runtime.
* Device #1: This hardware has outdated CUDA compute capability (2.1).
For modern OpenCL performance, upgrade to hardware that supports
CUDA compute capability version 5.0 (Maxwell) or higher.
* Device #1: WARNING! Kernel exec timeout is not disabled.
This may cause "CL_OUT_OF_RESOURCES" or related errors.
To disable the timeout, see: https://hashcat.net/q/timeoutpatch
nvmlDeviceGetCurrPcieLinkWidth(): Not Supported
nvmlDeviceGetClockInfo(): Not Supported
nvmlDeviceGetClockInfo(): Not Supported
nvmlDeviceGetTemperatureThreshold(): Not Supported
nvmlDeviceGetTemperatureThreshold(): Not Supported
nvmlDeviceGetUtilizationRates(): Not Supported
OpenCL API (OpenCL 1.2 CUDA 9.1.84) - Platform #1 [NVIDIA Corporation]
======================================================================
* Device #1: GeForce GTX 560 Ti, 704/1024 MB (256 MB allocatable), 8MCUI no longer have any expectations to see it work, knowing now that it requires CUDA 9. But that's related to using CUDA runtime rather than Open CL if I am not mistaken. The reason it totally fails to work at all, even in Open CL mode (the fallback mode) seems to be related memory limitations of the GPU. There is only 1 GB of GDDR5.
Code:
* Device #1: Not enough allocatable device memory for this attack.I'm not sure why it works in 3.0, 4.0 and 5.0 then. Version 3.0 is also using Open CL.
Code:
hashcat (v3.00-1-g67a8d97) starting...
OpenCL Platform #1: NVIDIA Corporation
======================================
- Device #1: GeForce GTX 560 Ti, 256/1024 MB allocatable, 8MCU
- Device #1: WARNING! Kernel exec timeout is not disabled, it might cause you errors of code 702
See the wiki on how to disable it: https://hashcat.net/wiki/doku.php?id=timeout_patchNote that 6.2.5 indicated that 704/1024 MB is allocatable, compared to 256/1024 MB for 3.0. This seems contradictory, for it would seem as if the current version requires more GPU memory. I don't know how much more or why the latest version would need more memory, but 2 GB would seem like a good minimum to look for in a new budget or outdated GPU for use with Hashcat.
Correction: The reason 6.2.5 doesn't work with GTX 560 Ti is more likely because of Open CL. Does 6.2.5 require Open CL 1.2? I see it listed in the string "OpenCL 1.2 CUDA 9.1.84" when Hashcart 6.2.5 is started. If this is the case then it would make sense why it fails, if the GTX 560 Ti only has Open CL 1.1 support. So it can't use CUDA and it can't use Open CL, and therefore it will not work.