06-11-2019, 03:47 AM
Hello,
I have hashcat installed on an Ubuntu 18.04 box that has a GTX 960, GTX 750TI, and a GTS 450 in it.
I'm able to run the benchmark with each graphics card separately, as well as with the GTX 960 and 750TI together. However, when I attempt to run the benchmark with all three graphics cards simultaneously I'm getting these errors:
I understand that the initial errors are saying that the GTS 450 has outdated CUDA compatibility, but given that it is still able to run solo, I'm not sure why it wouldn't be able to run with the other GPUs.
Here's what it looks like when the GTS 450 runs by itself:
Any insight into this issue would be very much appreciated, thank you.
I have hashcat installed on an Ubuntu 18.04 box that has a GTX 960, GTX 750TI, and a GTS 450 in it.
I'm able to run the benchmark with each graphics card separately, as well as with the GTX 960 and 750TI together. However, when I attempt to run the benchmark with all three graphics cards simultaneously I'm getting these errors:
Code:
hashcat (v5.1.0) starting in benchmark mode...
Benchmarking uses hand-optimized kernel code by default.
You can use it in your cracking session by setting the -O option.
Note: Using optimized kernel code limits the maximum supported password length.
To disable the optimized kernel code in benchmark mode, use the -w option.
* 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
* Device #2: This hardware has outdated CUDA compute capability (2.1).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.
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 960, 499/1999 MB allocatable, 8MCU
* Device #2: GeForce GTS 450, 241/964 MB allocatable, 4MCU
* Device #3: GeForce GTX 750 Ti, 500/2002 MB allocatable, 5MCU
Benchmark relevant options:
===========================
* --optimized-kernel-enable
Hashmode: 0 - MD5
clCreateContext(): CL_INVALID_DEVICE
Started: Mon Jun 10 18:17:06 2019
Stopped: Mon Jun 10 18:17:09 2019
I understand that the initial errors are saying that the GTS 450 has outdated CUDA compatibility, but given that it is still able to run solo, I'm not sure why it wouldn't be able to run with the other GPUs.
Here's what it looks like when the GTS 450 runs by itself:
Code:
hashcat (v5.1.0) starting in benchmark mode...
Benchmarking uses hand-optimized kernel code by default.
You can use it in your cracking session by setting the -O option.
Note: Using optimized kernel code limits the maximum supported password length.
To disable the optimized kernel code in benchmark mode, use the -w option.
* Device #2: 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.
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 960, skipped.
* Device #2: GeForce GTS 450, 241/964 MB allocatable, 4MCU
* Device #3: GeForce GTX 750 Ti, skipped.
Benchmark relevant options:
===========================
* --opencl-devices=2
* --optimized-kernel-enable
Hashmode: 0 - MD5
Speed.#2.........: 840.2 MH/s (59.15ms) @ Accel:128 Loops:128 Thr:768 Vec:2
Hashmode: 100 - SHA1
Speed.#2.........: 223.5 MH/s (74.40ms) @ Accel:128 Loops:64 Thr:512 Vec:4
<.. and so on>
Any insight into this issue would be very much appreciated, thank you.