Nvidia cuda toolkit 8 upgrade#

There are competing models of host toolchain integration, e.g. As a consequence, adjusting CUDA to changes in the host toolchain is non-trivial and requires developer resources.

This is needed to ensure the correct functioning of host device functions (this is identical code that can be built for both host and device), for example. There is an old song by the Rolling Stones which addresses this scenario: You can’t always get what you want.įor better and worse, CUDA requires tight integration with various components of the host toolchain (header files in particular). That is in general what happens in a software stack: If the software lower in the stack gets updated, support for that in the next higher layer of the software stack gets added in the next version, not the version that has been out for year and is done and dusted. It will not support cuda 9 on windows until version 1.5 is releasedĪnalogous situation to CUDA, which added (preliminary) support for MSVC 2017 in the next version, namely CUDA 9. I figured it would only be fair to extend the same approach to the Tensorflow vendor (Google) :-) Maybe I have a quirky sense of humor. But strangely enough, a certain percentage of CUDA programmers starts complaining if a new version of MSVS ships and it is not immediately supported by CUDA. You cant really expect everyone to imediately release a new version of their software just because you release a new version.Įxactly. I am unable to make a remote diagnosis as to why your installation may be inoperable. Installation was smooth and I have not encountered any issues so far.

Nvidia cuda toolkit 8 upgrade#

I downloaded and installed the latest version of it (8.0.61) fairly recently (due to various constraints and dependencies I am unable to upgrade to CUDA 9 at this time). CUDA 8 is still available for download and installation.