Is there any way to install only the nvcc compiler without installing cuda toolkit?
I want this because I want to compile the cuda program just for syntax check.
Please suggest if there are any other ways for cuda syntax checking
As far I as know, the smallest level of installation granularity in current CUDA distributions is the entire toolkit. There is no way to just install nvcc (and in reality that implies installing a number of binary components beyond the compiler driver, plus all the toolchain header files).
Related
I used below command to build binary for nvidia GPU:
clang++ -fsycl -fsycl-targets=nvptx64-nvidia-cuda simple-sycl-app.cpp -o simple-sycl-app-cuda
But got below error message:
clang++: error: cannot find 'libspirv-nvptx64--nvidiacl.bc'; provide path to libspirv library via '-fsycl-libspirv-path', or pass '-fno-sycl-libspirv' to build without linking with libspirv
I searched in both intel oneAPI installation path and cuda toolkit path, but cannot find the spirv-nvptx64-nvidiacl.bc.
Anyone knows where to find libspirv-nvptx64—nvidiacl.bc?
It looks like you are trying to compile using the DPC++ compiler for Nvidia GPUs.
This option is not included in the oneAPI release installations from the Intel website. At the moment you will need to compile the DPC++ LLVM project with this enabled to be able to use the appropriate flag to target Nvidia devices.
You can follow the instructions on this page to compile the project and then it explains how to use the ptx target. In the future Codeplay, the company I work for, intends to publish release binaries that include the ptx compiler option.
How can I learn maximum compute capability of devices for which I can compile code with the compiler from a given version of CUDA toolkit?
Suppose, I have cuda6.5 toolkit. Is nvcc from there able to compile for GTX GeForce 970 (compute capability 5.2)?
One approach would be trial and error - launch test compile commands with the compute capabilities you want. If you get an error, that toolkit version does not support that compute capability:
$ nvcc -arch=sm_20 t10.cu -o t10
$ nvcc -arch=sm_52 t10.cu -o t10
nvcc fatal : Value 'sm_52' is not defined for option 'gpu-architecture'
$
Another approach would be to read the programming guide document that ships with each toolkit and is installed (e.g. on linux) in /usr/local/cuda/doc. Table 12 of that doc will list the available compute capabilities supported by that compiler version.
I'm sure there are other approaches as well. You could probably grep through the header files and figure it out.
You compile the CUDA 7.0 samples with the CUDA 6.5 toolkit. It uses cc5.2 in the make. That'd be the fastest way to find out. Probably found out already, so it'd be nice if you'd tell everyone else the specific version number you discovered worked with cc5.2 for us other lazy people. :)
I am installing CUDA on Ubuntu 14.04 and have a Maxwell card (GTX 9** series) and I think I have installed everything properly with the toolkit as I can compile my samples. However, I read that in places that I should install the SDK (This appears to be talked about with the sdk 4). I am not sure if the toolkit and sdk are different? As I have a later 9 series card does that mean I have CUDA 6 running? Here is my nvcc version
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2014 NVIDIA Corporation
Built on Wed_Aug_27_10:36:36_CDT_2014
Cuda compilation tools, release 6.5, V6.5.16
I am following a book and I need to include <cutil.h> and I can't find that file in the includes anywhere where I installed it.
I followed this guide provided by nvidia and as I have done what they say this is why I am confused http://developer.download.nvidia.com/compute/cuda/6_5/rel/docs/CUDA_Getting_Started_Linux.pdf
Thanks for help
CUDA Toolkit is a software package that has different components. The main pieces are:
CUDA SDK (The compiler, NVCC, libraries for developing CUDA software, and CUDA samples)
GUI Tools (such as Eclipse Nsight for Linux/OS X or Visual Studio Nsight for Windows)
Nvidia Driver (system driver for driving the card)
It has also many other components such as CUDA-debugger, profiler, memory checker, etc.
The fact that you are able to compile and run samples means that you probably installed the Toolkit fully and have the SDK, the driver, and the Samples at least.
As for the cutil.h, doing a search in my CUDA 6.5 installation with find -L . -iname "cutil.h" yielded no results. Also looking at other related questions on SO, it seems like this header file does not exist in CUDA installations anymore (since CUDA 5.0). However, looking at the samples, you can find some newer utility headers such as helper_cuda.h being in use. Helpers like these should be located in somewhere like /usr/local/cuda/samples/common/inc in your OS. helper_cuda.h is a header I almost always include in my CUDA programs since I find utility functions such as checkCudaErrors() very useful.
If you are following a book, my recommendation is; try to compile the code, and whenever you get an error saying a utility function is missing, do a grep search in the header files included in samples/common/inc. You will most probably find the missing utility functions there and then you can include the necessary headers accordingly.
I am on Ubuntu 12.04 LTS and have installed CUDA 5.5. I understand that without any CUDA/GPGPU elements in the code, nvcc behaves as a C/C++ compiler -- more like gcc, however is there any exception to this rule ? if not, then can I use nvcc as gcc for non-CUDA C/C++ codes ?
No, nvcc doesn't behave like a C/C++ compiler for host code. What it does is the following:
separate device from host code into two separate files
compile device code (with nvcc, cudafe, ptxas)
invoke gcc for host code
If no device code exists, nothing is done in steps 1) and 2). So nvcc is actually no compiler, it is a compiler driver which invokes the right compilers for every part in the right order. To answer your question, if you use nvcc to compile host code only, you still use gcc.
It doesn't accept options to suppress warnings ( -W*)
with a very simple code, hello world, the breakpoint is not working.
I can't write the exact comment since it's not written in English,
but it's like 'the symbols of this document are not loaded' or something.
there's not cuda codes, just only one line printf in main function.
The working environment is windows7 64bit, vc++2008 sp1, cuda toolkit 3.1 64bits.
Please give me some explanation on this. :)
So this is just a host application (i.e. nothing to do with CUDA) doing printf that you can't debug? Have you selected "Debug" as the configuration instead of "Release"?
Are you trying to use a Visual Studio breakpoint to stop in your CUDA device code (.cu)? If that is the case, then I'm pretty sure that you can't do that. NVIDIA has released Parallel NSIGHT, which should allow you to do debugging of CUDA device code (.cu), though I don't have much experience with it myself.
Did you compile with -g -G options as noted in the documentation?
NVCC, the NVIDIA CUDA compiler driver, provides a mechanism for generating the debugging information necessary for CUDA-GDB to work properly. The -g -G option pair must be passed to NVCC when an application is compiled for ease of debugging with CUDA-GDB; for example,
nvcc -g -G foo.cu -o foo
here: https://docs.nvidia.com/cuda/cuda-gdb/index.html