As Linux implements microkernel architecture where drivers are treated as plugins, they must be compatible with the kernel which they are going to be plugged into. Thus, CPU and GPU need to talk to each other and such communication is done via driver. It allows to create a heterogeneous computing architecture, where CPU acts as a supervisor and GPU takes role of a workhorse. Manage kernel versionĬUDA is a device architecture which is implemented inside GPU.
OPENGL NVIDIA CUDA TOOLKIT 9 INSTALL
If your existing installation differs from the recommended one, you must be able to decide whether you are OK to upgrade/downgrade your kernel and whether it’s possible for you to install required version of gcc. So, pay special attention to supported versions of kernel and gcc. However it is easy to lull your vigilance if you are working basically with software in the modern world of constant changes and updates. This might be obvious that everyone should get familiar with system requirements before installing anything on a target system.
Official installation guide for Linux defines system requirements which you must conform to make things work.
Actually, it’s not a rocket science, but there are certain points which require extra attention and those points are completely distributive-independent.
Target environment of this guideline is CUDA 9.1 and Ubuntu 17.10, however it can be applicable to other systems. This article aims to be a guideline for installation of CUDA Toolkit on Linux.
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