I run code using nvcc command and it gave correct output but when I run the same code on the nsight eclipse it gave wrong output. Any one have any idea why is this behavior.
Finally I found there is problem in one of the array allocation.While the command line doesn't make any problem the nsight does.
Nsight EE builds the projects by generating make files based on the project settings and by invoking the OS make utility to build the project. It is using nvcc compiler found in the PATH but it relies on some newer options introduced in NVCC compiler 5.0 (that is a part of the same toolkit distribution).
Please do a clean rebuild in Nsight Eclipse - it will print out the command lines used to build your application. Then you can compare that command line with the one you use outside. Possible differences are:
Nsight specifies debug flags and optimization flag when building in debug and release modes.
By default, Nsight sets the new project to build for the hardware detected on your system. NVCC default is SM 1.0.
Make sure the compiler used by Nsight and from the command line are one and the same. It is possible that you have different compilers (e.g. 4.x and 5.0) installed on your system that may generate a slightly different code.
In any case, it is likely your code has some bug that manifests itself under different compilation settings. I would recommend running CUDA memcheck on you program to ensure there is no hidden bugs.
Related
I am doing an experiment on a chest x-ray Project. and I want multiple versions of the CUDA toolkit but the problem is that my system put the latest version which I installed lastly is appearing.
Is it possible to run any of CUDA like 9.0, 10.2, 11.0 as required to GitHub code?
I have done all the initial steps like path added to an environment variable and added CUDNN copied file and added to the environment.
Now the problem is that I want to use Cuda 9.0 as per my code but my default setting put cuda.11.0 what is the solution or script to switch easily between these version
You may set CUDA_PATH_V9_0, CUDA_PATH_V10_0, etc properly, then set CUDA_PATH to any one of them (e.g. CUDA_PATH=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v9.0).
Then in your VS project, set your cuda library path using the CUDA_PATH (e.g. $CUDA_PATH\lib).
To switch, just set the CUDA_PATH to another version, and clean & rebuild your VS project(s).
I've started a CUDA application in the new CLion 2020.1 version. Although I can compile and run it, I am not able to debug it, not even the host code. Specifically, debug does not stop at breakpoints, even though I am running the debug build. I'm not encountering this issue with running a regular C project in CLion 2020.1. I don't receive any error message of any kind. Here is my CMakeLists.txt file:
# Setup the CUDA compiler
set(CMAKE_CUDA_COMPILER /usr/local/cuda-10.2/bin/nvcc)
# Setup the host compiler
set(CMAKE_CUDA_HOST_COMPILER /usr/bin/g++-8)
# CMAKE minimum required version
cmake_minimum_required(VERSION 3.16)
project(PageRank_GPU CUDA)
set(CMAKE_CUDA_STANDARD 14)
add_executable(PageRank_GPU main.cu graph.cu graph.cuh vertex.cuh error.cuh parser.cu parser.cuh)
set_target_properties(
PageRank_GPU
PROPERTIES
CUDA_SEPARABLE_COMPILATION ON)
Reporting that the issue has disappeared after playing around in the project settings a bit. Specifically, under Build, Execution, Deployment then Toolchain, I set the C and C++ compilers to gcc-8 and g++-8 respectively (even though I am specifying the compiler in the CMakeLists.txt file) and under CMake, I set the toolchain to "Default" (the one I just modified) instead of "Use Default". After doing that, the debugger stops at breakpoints and I am able to step through my code. I don't understand what happened because, even after reverting the changes, I cannot make the problem re-appear.
My problem is that I cannot compile a CUDA example. I believe I've got CUDA 4.0 installed correctly ( I need the old version b/c I'm trying to run GPGPU-Sim). I downloaded an NVIDIA cuda sample, namely conjugateGradient. If I cd to it and run
make
it doesn't work:
macair93278:7_CUDALibraries r8t$ cd conjugateGradient/
macair93278:conjugateGradient r8t$ ls
Makefile main.cpp
macair93278:conjugateGradient r8t$ make
Makefile:36: findcudalib.mk: No such file or directory
make: *** No rule to make target `findcudalib.mk'. Stop.
I've changed my path so that running
nvcc -V
doesn't produce an error, but gives me the version. So I think that's right.
Thanks for any help.
-bb
findcudalib.mk is missing because the individual sample you downloaded is not designed to be a complete, standalone sample. It requires a framework of other files and probably other libraries that need to be built around it.
To fix this, download the CUDA 4.0 SDK (GPU Computing SDK) from here.
Install that package. Once you have installed it, and assuming your CUDA install is otherwise intact, you should be able to change into the toplevel directory and issue make. This will build all the samples. For convenience, you may wish to issue make -k.
I'we been writing some simple cuda program (I'm student so I need to practice), and the thing is I can compile it with nvcc from terminal (using Kubuntu 12.04LTS) and then execute it with optirun ./a.out (hardver is geforce gt 525m on dell inspiron) and everything works fine. The major problem is that I can't do anything from Nsight. When I try to start debug version of code the message is "Launch failed! Binaries not found!". I think it's about running command with optirun but I'm not sure. Any similar experiences? Thanks, for helping in advance folks. :)
As this was the first post I found when searching for "nsight optirun" I just wanted to wanted to write down the steps I took to make it working for me.
Go to Run -> Debug Configurations -> Debugger
Find the textbox for CUDA GDB executable (in my case it was set to "${cuda_bin}/cuda-gdb")
Prepend "optirun --no-xorg", in my case it was then "optirun --no-xorg ${cuda_bin}/cuda-gdb"
The "--no-xorg" option might not be required or even counterproductive if you have an OpenGL window as it prevents any of that to appear. For my scientific code however it is required as it prevents me from running into kernel timeouts.
Happy bug hunting.
We tested Nsight on Optimus systems without optirun - see "Install the cuda toolkit" in CUDA Toolkit Getting Started on using CUDA toolkit on the Optimus system. We have not tried optirun with Nsight EE.
If you still need to use optirun for debugging, you can try making a shell script that uses optirun to start cuda-gdb and set that shell script as cuda-gdb executable in the debug configuration properties.
The simplest thing to do is to run eclipse with optirun, that will also run your app properly.
I'we been writing some simple cuda program (I'm student so I need to practice), and the thing is I can compile it with nvcc from terminal (using Kubuntu 12.04LTS) and then execute it with optirun ./a.out (hardver is geforce gt 525m on dell inspiron) and everything works fine. The major problem is that I can't do anything from Nsight. When I try to start debug version of code the message is "Launch failed! Binaries not found!". I think it's about running command with optirun but I'm not sure. Any similar experiences? Thanks, for helping in advance folks. :)
As this was the first post I found when searching for "nsight optirun" I just wanted to wanted to write down the steps I took to make it working for me.
Go to Run -> Debug Configurations -> Debugger
Find the textbox for CUDA GDB executable (in my case it was set to "${cuda_bin}/cuda-gdb")
Prepend "optirun --no-xorg", in my case it was then "optirun --no-xorg ${cuda_bin}/cuda-gdb"
The "--no-xorg" option might not be required or even counterproductive if you have an OpenGL window as it prevents any of that to appear. For my scientific code however it is required as it prevents me from running into kernel timeouts.
Happy bug hunting.
We tested Nsight on Optimus systems without optirun - see "Install the cuda toolkit" in CUDA Toolkit Getting Started on using CUDA toolkit on the Optimus system. We have not tried optirun with Nsight EE.
If you still need to use optirun for debugging, you can try making a shell script that uses optirun to start cuda-gdb and set that shell script as cuda-gdb executable in the debug configuration properties.
The simplest thing to do is to run eclipse with optirun, that will also run your app properly.