So i need to compile a shellcode written in C for a project, that need to be compiled in MIPSBE using buildroot toolchain for compile mipsel-buildroot-linux-uclibc-gcc-10.3.0.
So what build root configuration should i choose for CPU model for MIPS 24kc V5.5.
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.
I was trying to run nvcc -V to check cuda version but I got the following error message.
Command 'nvcc' not found, but can be installed with:
sudo apt install nvidia-cuda-toolkit
But gpu acceleration is working fine for training models on cuda. Is there another way to find out cuda compiler tools version. I know nvidia-smi doesn't give the right version.
Is there a way to install or configure nvcc. So I don't have to install a whole new toolkit.
Most of the time, nvcc and other CUDA SDK binaries are not in the environment variable PATH. Check the installation path of CUDA; if it is installed under /usr/local/cuda, add its bin folder to the PATH variable in your ~/.bashrc:
export CUDA_HOME=/usr/local/cuda
export PATH=${CUDA_HOME}/bin:${PATH}
export LD_LIBRARY_PATH=${CUDA_HOME}/lib64:$LD_LIBRARY_PATH
You can apply the changes with source ~/.bashrc, or the next time you log in, everything is set automatically.
As #pQB and #talonmies above mentioned you only need to install the GPU drivers (Versioned 430-470 these days) to use PyTorch. If you are using your GPU display port you should be fine.
For Cuda compilation tools you need to install the whole toolkit, which includes the driver as well. If installing manually from CLI the downloaded file, CLI will give you the option to choose the components to install or skip.
Generally, it is recommended to install the compilation tools (which are system wide) and GPU drivers together because it avoids compatibility issues.
Append:
export PATH="/usr/local/cuda/bin:$PATH"
export LD_LIBRARY_PATH="/usr/local/cuda/lib64:$LD_LIBRARY_PATH"
to
~/.bashrc
Note: your path to cuda may include a version so navigate to /usr/local/ and check for cudaXX.XX and modify the command to point to that in ~/.bashrc
I would like to use Xcode under Mac OS X to compile and run a program written in a language that is not supported, e.g. Fortran. Assuming I have a compiler installed, e.g. gfortran or ifort, what are the steps in the Xcode project settings to make it possible to compile and run the program?
I have created an new, empty project since Fortran is not supported (only C,C++,Objective-C and Swift are selectable in a command line tool application). I created a simple Fortran file. But now I guess I have to add several things to the Builds tab in the project settings to make it compile and run (it works from the command line). What are these steps?
Add an external build system target to your project. External build system targets/projects let you build projects in languages Xcode doesn't natively support. The external build system target/project is in the Other section under OS X on the left side of the assistant. When you click the Next button, you'll be asked for the location of the build tool. Enter the path to your Fortran compiler. When you build the project, Xcode will use the Fortran compiler to do the building.
CUDA programming guide states that:
the driver API is backward compatible, meaning that applications, plug-ins, and libraries (including the C runtime) compiled against a particular version of the driver API will continue to work on subsequent device driver releases
I understand this as that, if my code was compiled on CUDA4, the binary will run on CUDA5. However, it turned out that running the CUDA5-compiled binary on CUDA5 led to:
error while loading shared libraries: libcudart.so.4: cannot open shared object file: No such file or directory
Note that I am using the "module" facility in Linux to switch in between different cuda versions, i.e.
module load cuda4
compile
module unload cuda4
module load cuda5
run
It is the developers responsibility to package libcudart.so.4 with the application. The module command is likely changing your LD_LIBRARY_PATH or your PATH variable so LDD is not finding libcudart.so.4. I recommend you add a post build step to copy the required .so into your application directory.
ATTACHMENT A in EULA.txt at the root of the CUDA Toolkit directory lists the Redistributable Software. This includes libcudart.so (and variations that have version number information embedded in the file name). This also includes libcufft, libcublas, ...
Hi all I have installed buildroot toolchain and am able to compile simple "Hello World" program which runs on uClibc based chroot. However I am confused how to do so for programs that use ./configure as how to ask it to use the uclibc based toolchain and not the glibc based toolchain present in my system.
My OS is Fedora and it is i386 based machine.I want to compile programs using uClibc for the same platform.
buildroot contains the package directory where there are numerous examples how to do it
Just set CC=PATH_TO_BUILDROOT_UCLIBC_GCC etc.
And you don't need to use chroot:
xxx/buildrootxxx/output/host/bin/xxxxx-gcc works fine, it would search the headers and libs in its own directory (like xxx/buildrootxxx/output/host/arm-buildroot-linux-uclibcgnueabi/sysroot/usr/*)