The third thing you may need to consider is compiler compatibility.
CUDA Version Minimum Compute Capability Default Compute Capability
WINDOWS NVIDIA CUDA DRIVERS INSTALL
This in turn means that I need to install an nVidia driver that is compatible with my CUDA version. For instance, my laptop has an nVidia CUDA 2.1 GPU, which means I can't install a CUDA toolkit more recent than CUDA 8.0 GA2. A GPU will support a specific compute version, and if your CUDA version minimum compute capability is higher than that supported by your GPU, your code will not compile or run. The other half is the Compute Capability. The driver version is only half of the compatibility equation. The general support matrix is contained in the linux install guide for the specific CUDA version of interest.įor reference, on linux, the previous CUDA toolkits required the following minimum driver versions: For versions newer than 11.0, refer to the table in the release notes linked belowĪ portion of this table is maintained as Table 3 here in the release notes. Not all distros are supported on every CUDA toolkit version. Note that any given CUDA toolkit has specific Linux distros (including version number) that are supported. Older CUDA toolkits are available for download here. Starting with CUDA 9.x, older CUDA GPUs of compute capability 2.x are also not supported.
WINDOWS NVIDIA CUDA DRIVERS HOW TO
Note that CUDA 7 will not be usable with older CUDA GPUs of compute capability 1.x. NVIDIA graphics cards require NVIDIA Driver (440.64 or later) and CUDA Toolkit (9.0 or later) Thus, we will consider how to install drivers, CUDA and other software necessary for Hashcat to work. This is not necessary if you want to use CUDA 7, you can just use the runfile installer method which has all the necessary components including an appropriate driver (346.46). CUDA installation instructions are in the 'Release notes for CUDA SDK' under both Windows and Linux. I believe you are picking up a 304.xx driver via a specific (ie. If you want to reinstall ubuntu to create a clean setup, the linux getting started guide has all the instructions needed to set up CUDA if that is your intent. 304.xx is a driver that will support CUDA 5 and previous (does not support newer CUDA versions.)
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