My run time system gives an error "CUDA driver version is insufficient for CUDA runtime version" when I try to run CUDA programs on Mac OS X 10.6.8 installed with CUDA ToolKit 5.0 (CUDA driver: 5.0.45) and GPU driver: 1.6.36.10 for GeForce 900M. I was unable to locate the correct (updated) GPU drivers for GeForce 900M at NVIDIA site. Kindly suggest a solution.
A given CUDA version (e.g. 5.0) has a minimum GPU driver version associated with it. Any newer version should work, but versions older than the minimum driver version will give an error, as you are seeing.
based on my memory:
cuda 4.0: 270.41.19
cuda 5.0: 304.54
cuda 5.5: 319.37
The above may be approximate, but it gives you an idea. For CUDA 4.0, for example, any GPU driver that is 270.41.19 or newer should work. An older driver (like 256.02) would not work. I don't recall the minimum driver versions for other CUDA versions, but it's not difficult to determine, by visiting the various CUDA download pages.
The most recent driver for your platform appears to be 256.02. Even CUDA 4.0 requires 270.41.19 or newer. So the most recent CUDA version you could use with 256.02 would be CUDA 3.2 The solution in that case, would be to upgrade your GPU driver to 256.02, and remove the CUDA 5.0 toolkit and install CUDA 3.2.
CUDA 3.2 is pretty old, so there will be many features that will be unavailable in that version. You'll want to have appropriate versions of the documentation, which will be installed on your machine along with the CUDA toolkit (e.g. in /usr/local/cuda/doc or similar)
Related
Not a duplicate of this question
When downloading NVIDIA GPU drivers, I've also been asked for some time which CUDA toolkit I prefer.
Now, what does this choice imply when downloading a driver?
As far as I know, different CUDA toolkits have different minimum drivers supporting them (also stated in the release notes), but what does this choice at the driver download page imply?
Generally speaking, there is a backwards compatibility strategy for drivers with respect to CUDA toolkits. For example, the latest driver should work with any older CUDA toolkit. An older driver may not work with a newer CUDA toolkit.
That is a general statement of compatibility. You can find it expressed here (e.g. table 1) also.
However, each CUDA toolkit ships with a particular driver branch. For example CUDA 10.1 ships with a 418.xx driver branch (this corresponds to the version of the GPU driver that is bundled with the CUDA toolkit installer).
So even though a 430.xx driver is compatible with and should work with CUDA 10.1, that isn't actually the driver branch that ships with CUDA 10.1
The dropdown allows you to select a driver that is in the same branch as the driver that particular CUDA toolkit was shipped with and has the highest test coverage with.
The hardware seems to newer than the highest-support hardware of the driver version of the lower toolkit. Is it possible for this newer hardware with the newer driver, but with the lower cuda toolkit?
For example,
the hardware is NVIDIA GTS 450,
the cuda toolkit is cuda 2.3, because the driver of cuda 2.3 seems not to support the GTS 450, so I want to install a newer driver, but the toolkit is still cuda 2.3.
Does this work?
In general, older CUDA toolkits should be compatible with newer GPU drivers. CUDA toolkit 2.3 is very old however, so I don't know what other issues you may run into. I would suggest updating to a newer CUDA toolkit as well.
I have recently installed cuda 6.0 with a view of performance increment in windows 7 . the toolkit installer has display driver installer along with it and it installed display driver version named as 9.18.13.4062 . is this version mean 340.62???
Also it is mentioned that driver version 340.29 with cuda increases performance according to this link
does 340.xx series have the same performance ?? I couldnot get the version 340.29 driver. where can i download it from???
340.62 is the Windows GPU driver that ships with the CUDA 6.5 (windows) installer.
340.29 is the Linux GPU driver that ships with the CUDA 6.5 (linux) installer.
The link you have provided is referring to linux. 340.62 and 340.29 should be comparable, as much as "comparable" can be stated about a windows platform vs. a linux platform
Regarding the performance in the article linked, CUDA 6.5 (i.e. not just the driver) has significant performance increases in various libraries and in the compiler as well.
To get an idea of these performance increases, there is a webinar you can attend tomorrow (wednesday, September 17th) by following the link here.
I installed NVIDIA driver come with the Tesla c2075 card rather than driver present in cuda 5.0
The driver has version NVIDIA-Linux-x86_64-275.21.run. Somewhere I read that driver installation gives problem in running CUDA programs is it due to that or something else
That driver is too old for cuda 5. cuda 5 requires driver 304.54 or newer.
Use the cuda driver (304.54) that comes in the cuda 5 package. It will work fine on your tesla C2075.
Or if you want the latest driver, it is here.
Also, if you do cuda error checking on your cuda api calls (like cudaGetDeviceCount) you will get more information about what is going wrong.
I get the error -
cutilCheckMsg() CUTIL CUDA error : Kernel execution failed
: CUDA version is insufficient for CUDART version.
when I run the sample code. The code however builds successfully
Details of the environment Im running the program -
Windows XP with NO NVIDIA driver
Visual Studio 2008 Express Edition
Cuda toolkit, sdk 3.0
Emulation mode
Here is a similar question asked on SO before but in that case the person had NVIDIA card. I do not have NVIDIA card on my machine. - CUDA driver version is insufficient for CUDA runtime version
Please suggest a solution
Currently the only way to run CUDA code without a GPU is to use CUDA x86 from PGI. Emulation mode was dropped from CUDA several versions ago (current version is CUDA 4.2).