CUDA code hang on Windows 10 - cuda

I recently got a new machine with dual Quadro P5000 GPUs and Windows 10.
However, my CUDA processes sometimes just hang there and GPU usage drops to 0%.
I've tried CUDA 9.0 and CUDA 8.0, and both gave me same behavior.
I never had this issue on my previous machine which has Windows 7/CUDA 8.0. I am not sure what happened. Does anyone know how to solve this issue?
Thank you!

I just found out it is due to "QuickEdit" feature on Windows 10...
"...whenever you click on a command window in windows 10, it immediately halts the application process when it attempts to write to the console...."
The solution is here:
Why is my command prompt freezing on windows 10?
Thanks!

Related

--disable-gpu-vsync does not work in chromium with NVIDIA GTX 960?

I am using NVIDIA GTX 960 gpu in my pc with windows 10 as the operation system. I have been trying to measure the actual fps value in one of my Three.js application. So i decided to run Chromium with flag --disable-gpu-vsync. Unfortunately it didnt work. The fps is still capped at 60. I have tried to disable vsync from the graphics driver without any success.
On the other hand, --disable-gpu-vsync worked at my worked pc with NVIDIA GTX 750 and Windows 7.
My question is, why isn't it working? Am i missing something?
Thanks in advance.
After some search, i have found that Windows 10 forces the v-sync on even if it is disabled.

"no CUDA-capable device is detected" with CUDA-capable GPU installed Win7

I have installed cuda.7.0.28 into my laptop. I tried to run one of the sample file. I ran deviceQuery project and got this message:
cudaGetDeviceCount returned 38
-> no CUDA-capable device is detected
Result = FAIL
Then, I ran nvidia-smi.exe file and got this message:
As you see, it is written that "Not Supported". What should I do?
nvidia-smi returning 'not supported' does not necessarily mean that your GPU does not have the ability to run CUDA code. It means that you don't have the ability to see the active CUDA process name using nvidia-smi.
Cuda-z might be of help here. Take a look at what it is here: http://cuda-z.sourceforge.net/
Also, I have to say I had quite a few problems getting CUDA running on Windows. If you really need to run it on Windows, make sure you go through this first: http://docs.nvidia.com/cuda/cuda-getting-started-guide-for-microsoft-windows/#axzz3cNkYKZDP
Have you tried to run it on linux on the same machine? It was much easier to get it workinge.
NVIDIA now provide a toolkit to install CUDA on windows (Linux or Mac also). It does a handy check of your system, to see if it meets necessary requirements for CUDA if you are unsure about your GPU
https://developer.nvidia.com/cuda-80-ga2-download-archive
I've noticed that when my nvidia driver is updated during the system package update process (on Ubuntu) that I'll get this message. It is resolved by a reboot, or likely an X restart although I haven't tried that.
This was disconcerting the first time it happened since it was one of those "Hey! My code just ran fine. WTF happened?" moments.

CUDA samples cause machine to crash

I was planning on starting to use CUDA on a machine with Kubuntu 12.04 LTS and a Quadro card. I installed CUDA 5.5 using the .deb from here, and the installation seems to have gone fine. Then I built the CUDA samples, again everything went fine.
When I run the samples in sequence, however, some of them botch my display, and others simply crash my computer.
What causes the crash? How can I fix it?
I'll mention that my NVidia card is the only display adapter the machine has, but that shouldn't make CUDA crash and burn.
The problem was due to the X server using the FOSS nouveau drivers. These are known to conflict with NVidia's way of accessing the card. When I restarted X (actually, I restarted the machine), the samples did run and work properly.
Not all the samples are runnable if you just installed CUDA on a clean ubuntu system. Some of them require additional libraries, and some of them require particular CC versions.
You could read the CUDA sample document of those crashed samples for more information.
http://docs.nvidia.com/cuda/cuda-samples/index.html

CUDA on Windows and Linux

I'm trying to set up a cuda development environment under windows, and lurked many cuda-tagged posts, but few things are still unclear:
Can I debug cuda applications under windows without the need of a second video card, using nsight and VS2010 express?
Can I debug cuda applications under linux without the need of a second video card, AND without shut down the graphical interface?
Answered thousands of times, but perhaps something has changed, so I ask again just to be sure: Can I develop under windows without installing a cuda-enabled video card? There is some kind of emeulator? (Ocelot for windows is practically inexistent).
Thanks.
Can I debug cuda applications under windows without the need of a second video card, using nsight and VS2010 express?
You can apparently debug with a single video card, but nsight requires vs2010 professional (not express edition)
https://developer.nvidia.com/nsight-visual-studio-edition-requirements
Can I debug cuda applications under linux without the need of a second video card, AND without shut down the graphical interface?
I don't think so, from the eclipse nsight docs (http://docs.nvidia.com/cuda/nsight-eclipse-edition-getting-started-guide/index.html#linux-requirements):
"A GPU that is running X11 (on Linux) or Aqua (on Mac) cannot be used to debug a CUDA application and will be hidden from the application ran in the debugger. Such GPU can still be used for profiling GPU applications."
Answered thousands of times, but perhaps something has changed, so I ask again just to be sure: Can I develop under windows without installing a cuda-enabled video card? There is some kind of emeulator? (Ocelot for windows is practically inexistent).
no, if you want to use cuda, you'd be best off just getting a cheap cuda-enabled card (e.g. a GTX 650 is ~$100 and is the most recent (kepler) architecture)

Debugger in CUDA 5

Nvidia has released extended eclipse for CUDA 5. They have Nsight plugin for VS2010 also. In VS2010 we can stop program execution at breakpoint in kernel but how to achieve this functionality in eclipse on Linux? I don't see any nsight specific keys to stop execution. I tried changing perspective but it debugs as a normal C/C++ application. I'm using Tesla C2070, Intel Xeon 8 core machine with Linux.
I'm from Nsight Eclipse Edition team.
Our goal is specifically for the application to be debugged as a normal C/C++ application. This means that you can set breakpoints, use "run to line", etc. regardless of whether you debug host or device code.
Basically, the process is quite standard for Eclipse:
Create a project (you can also import existing executable)
Click debug button
Debugger will run and by default will break in the main function. Note that no device code posted on the device so you will only see the host thread.
Set a breakpoint in the device code and hit resume (note that Breakpoints view toolbar also allows you setting breakpoint on any CUDA kernel launch)
Debugger will break when device code reaches the breakpoint. You can inspect your application state using visual debugger UI.
Couple things, and not sure which solved the issue. Drivers updated to latest ones with RC5.0, but I chose to run VNC server instead of native X server. Then the CUDA card(s) are dedicated to my apps and debugging, and it works like a charm, and now accessible from everywhere.
Eugene,
I just installed Cuda 5, and I wasn't able to break in any kernel code. It was a clean install of centos 5.5, with a fresh download of cuda-5, and i am running on a asus g71x laptop which has a gtx260m installed.
I thought maybe you cant run display and dedbug on one device still, so i switched to non-nv x display, but still had same issue, cant stop in the kernel code.
Have you tried CUDA 5.0 RC1? It is available now. You can download and try it. And I have tried the Nsight in it, it works well for debugging.
Best regards!
The 304.43 NVIDIA Driver does not let users other than root debug their CUDA application.
That problem is not present in any past or future public releases. The CUDA documentation recommends using only drivers listed in the CUDA DevZone. The 304.43 driver is not one of them.
That may or may not be the issue you are hitting. But I thought it was worth mentioning.