I read on the CUDA toolkit documentation (11.3.0) that "Deployment and execution of CUDA applications on x86_32 is still supported, but is limited to use with GeForce GPUs."
This looks in conflict with the fact that I was able to run a 32-bit app on my Tesla T4. (I verified that the code was actually running on the GPU and the app was 32-bit).
Have I misinterpreted the documentation? Why am I able to run 32-bit apps on a Tesla GPU?
(I'm running Visual studio 2017 on Windows 10)
It's a question of what is supported.
Other things may work, or they may not.
Related
I have a machine with an NVIDA GTX 1050 Ti GPU (compute capability 6.1), and am trying to profile a kernel in a program I built with CUDA 11.4. My OS distribution is Devuan GNU/Linux 4 Chimaera (~= Debian 11 Bullseye).
NSight Compute starts my program, and shows me API call after API call, but when I get to the first kernel launch, it gives me an error message in the Details column of the API call listing:
Error: Profiling is not supported on this device
Why? What's wrong with my device? Is it a permissions issue?
tl;dr: Nsight Compute no longer supports Pascal GPUs.
Nsight Compute used to support Pascal-microarchitecture GPUs (Compute Capability 6.x) - up until version 2019.5.1. Beginning with 2020, Nsight Compute dropped support for Pascal.
If you're wondering why that is - no reason or justification was given to my knowledge (see also the quote below). This is especially puzzling, or annoying, given the short period of time between the release of post-Pascal GPUs and this dropping of support (as little as 1.5 years if you look at consumer GTX cards).
On the other hand, you may still use the NVIDIA Visual Profiler tool with Pascal cards, so they did throw you entirely under the bus. And you can also download and use Nsight Computer 2019.5.1.
To quote an NVIDIA moderator's statement on the matter on the NVIDIA developer forums:
Pascal support was deprecated, then dropped from Nsight Compute after Nsight Compute 2019.5.1. The profiling tools that support Pascal in the CUDA Toolkit 11.1 and later are nvprof and visual profiler.
I have a Cuda application that was built with Cuda Toolkit 9.0 and running fine on Jetson TX2 board.
I now have a Jetson Xavier board, flashed with Jetpack 4 that installs Cuda Toolkit 10.0 (only 10.0 is available).
What do I need to do if I want to run the same application on Xavier?
Nvidia documentation suggests that as long as I specify the correct target hardware when running nvcc, I should be able to run on future hardwares thanks to JIT compilation. But does this hold for different versions of Cuda toolkit (9 vs 10)?
In theory (and note I don't have access to a Xavier board to test anything), you should be able to run a cross compiled CUDA 9 application (and that might mean both ARM and GPU architecture settings) on a CUDA 10 host.
What you will need to make sure is that you either statically link or copy all the CUDA runtime API library components you require with your application on the Xavier board. Note that there is still an outside chance that those libraries might lack the necessary GPU and ARM features to run correctly on a Xavier system, or more subtle issues like libC incompatibility. That you will have to test for yourself.
I recently upgraded from msvc 2005 to 2015.
I have compiled my code with revision 4.2 of cuda toolkit for year. I'm now learning the hard way that there is no forward compatibility betweend visual and cuda, however Google shows that some trick exists to force the compilation (messing up with .props and .targets files).
From what I understand, cuda 4.2 is a no-go. nvcc seems to have an hardcoded check on the msvc revision.
My questions are:
is there a way to compile with cuda 5.x or 6.x?
worst case scenario is that I have to update to cuda 7.5, does it even work?
Thanks for your help.
Update: CUDA 8RC supports VS2015 Update 1 officially (not update 2).
For CUDA toolkits prior to CUDA 8RC, none officially list MSVC 2015 as a supported environment, including CUDA 7.5 (the most recent production toolkit, at the moment).
For recent CUDA toolkits, the official support matrix is given in the windows getting started guide or installation guide which you would have to review for each toolkit version, to find the support for that version.
Since support for a VS version means that the CUDA toolkit will make changes to the VS environment (e.g. installing CUDA build customization rules, what you refer to as "messing with .props and .targets") and also provide appropriate project definition files for each of the cuda sample projects, if you wanted to work around this, you would have to duplicate those functions yourself. There might be non-standard ways to do this, but you would be operating in unsupported territory.
CUDA 8 is the first version to support MSVC 2015, including the community edition (with the exception of cross compiling). At the time of writing this, CUDA 8 is available as a release candidate if you are signed up for the NVIDIA "Accelerated Computing Developer Program".
I have a Dell XPS L502 with the Nvidia 525M graphics card. I am only interested in using the gpgpu capabilities of the card for now.
I installed Ubuntu 12.04 as a dual boot with the Windows 7 that came with the machine and followed several installation procedures for installing the CUDA driver and developer kit from Nvidia ( many re-installs of Ubuntu ). In all cases the display drops to 640x480 resolution. Best I can determine this has something to do with Optimus technology and Linux. I tried Bumblebee to no avail.
I really don't care about using the NVidia card to drive the display. Is there any way that I can just install the NVidia drivers so that a program can use the CUDA capabilities of the graphics card and I still get the full resolution on the display?
I had a similar issue with my Alienware M11xR2, and posted the solution on the NVIDIA Forums. Unfortunately the forums are down at the moment but essentially the process is as follows:
Install the Nvidia Drivers, but when prompted to modify your X11 Config, select 'No'. This is because the Nvidia card cannot be used as a display device.
Install the CUDA SDK and run one of the samples as root. I found this to be a necessary step. After this you should be able to execute further CUDA programs as a normal user.
Hope that helps.
With the new release of CUDA 5 the, comes the installation guide, there you have just one file that installs drivers, toolkit and sdk (even nvidia nsight). And one thing that got my attention is that you also have optimus options in the installation process.
I also have and Alienware M14x, and i understand your problem, but i also wanted the drivers to work for me, so i didn't try too hard on that.
Maybe you could give that a try and comment with the rest of us.
Here you can look for the CUDA 5 release candidate: CUDA 5
and here is the installation guide (maybe give this a read first): CUDA 5 Starting Guide for Linux.
So I have successfully installed the CUDA toolkit and GPU computing SDK on a Mac Pro running OS X version 10.6.6. The sample CUDA programs provided with the SDK as well as some programs of my own work well. However, when I run any of these CUDA programs through the NVIDIA Visual Profiler (the executable is called computeprof), I always get the following error upon launch:
"Unable to initialize the Profiling in Start/Stop mode"
NVIDIA's documentation does not mention this error, and Googling shows a single post in the NVIDIA forums in which several people have run into this problem recently (since October 2010) but no solutions.
Any information on this error message would be greatly appreciated.
If Visual Profiler v4.0 isn't working for you, there's a new CUDA release out (v4.1) and it includes a completely new & re-designed Visual Profiler.
The new NVIDIA Visual Profiler (v4.1) supports automated performance analysis to identify performance improvement opportunities in your application. It also links directly to the most useful sections of the Best Practices Guide for the issues it detects. And the Visual Profiler is available for free as part of the CUDA Toolkit on NVIDIA's developer web site: http://www.nvidia.com/getcuda.
If you experience any problems, please file a bug via your (free) NVIDIA registered developer account so the team working on the Visual Profiler can figure out the problem.
Are you using CUDA4.0?
I had problem with CUDA 4.0 and visual profiler (I use a Linux system). But it works fine with CUDA 3.2.