Gtx 1080ti evga driver download

Do not attempt this in a VM. It is possible in theory, however this likely will not work and we do not recommend that users attempt this.

This document explains how to install NVIDIA GPU drivers and CUDA support, allowing integration with popular penetration testing tools.

This guide is also for a dedicated card (desktops users), not Optimus (notebook users). We do not have the hardware in order to write up the guide. So we are looking for community contribution to help out. If you have the hardware, and expertise, please edit this guide!

Prerequisites

First, you'll need to ensure that your card supports CUDA.

Afterwards, make sure you have & components are enabled in your network Repositories and that your system is fully upgraded:

Let's determine the exact GPU installed, and check the kernel modules it's using:

Notice how & are using nouveau? This is the open source driver for nVidia. This guide covers installing the close source, from NVIDIA.

Installation

Once the system has rebooted from doing an OS upgrade, we will proceed to install the Drivers, and the CUDA toolkit(allowing for tool to take advantage of the GPU).

During installation of the drivers the system created new kernel modules, so a reboot is required:

DPI/PPI

Upon Kali starting back up, certain things may appear different than what is expected.

• If certain things are smaller, this could because of HiDPI.
• However, if certain things are larger, this could because the DPI is incorrect.

Verify Driver Installation

Now that our system should be ready to go, we need to verify the drivers have been loaded correctly. We can quickly verify this by running the nvidia-smi tool.

You can see our hardware has been detected we are using nvidia rather than nouveau drive now.

Hashcat

With the output displaying our driver and GPU correctly, we can now dive into benchmarking (using the CUDA toolkit). Before we get too far ahead, let's double check to make sure hashcat and CUDA are working together.

It appears everything is working, let's go ahead and run hashcat's inbuilt benchmark test.

Benchmarking

There are a multitude of configurations to improve cracking speed, not mentioned in this guide. However, we encourage you to take a look at the hashcat documentation for your specific cases.

Troubleshooting

In the event setup isn't going as planned, we'll install clinfo for detailed troubleshooting information.

OpenCL Loaders

It may be necessary to check for additional packages that may be conflicting with our setup. Let's first check to see what OpenCL Loader we have installed. The NVIDIA OpenCL Loader and the generic OpenCL Loader will both work for our system.

If mesa-opencl-icd is installed, we should remove it:

Since we have determined that we have a compatible ICD loader installed, we can easily determine which loader is currently being used.

As expected, our setup is using the open source loader that was installed earlier. Now, let's get some detailed information about the system.

Querying GPU Information

We'll use nvidia-smi once again, but with a much more verbose output.

It looks like our GPU is being recognized correctly, so let's use glxinfo to determine if 3D Rendering is enabled.

The combination of these tools should assist the troubleshooting process greatly. If you still experience issues, we recommend searching for similar setups and any nuances that may affect your specific system.