I have multiple MIPS platforms with different CPUs and different kernel and uclibc versions
I'm want to compile 'Hello World' program with single toolchain that will run on all of the devices.
I'm building the toolchain using crosstool-ng with the following configuration:
MIPS1 arch type (-march=mips1)
soft FPU (should work on devices w/wo hardware FPU)
static executable (to avoid libraries dependencies failures)
old kernel version (should be supported by devices with newer kernel)
Am I missing something?
I still have devices that the program is working only when using their dedicated toolchain (RTL819xD for example)
Thanks
Related
I'm compiling the source code by using pgf95 (Fortran compiler).
If I use cuda 10.0, it successfully compiles the source code.
However, If I use cuda 10.1, it fails showing that 'cannot find libcublasLt.so'.
When I scan the directory cuda-10.0/lib64, cuda-10.1/lib64, both do not have the file starting with 'libcublasLt'.
How can I solve this issue?
libcublasLt.so is the library that provides the implementation for the cublasLt API which is defined here. It just happens to be a separate shared object from libcublas.so
In the past (e.g. CUDA 10.0 and prior), most CUDA libraries were installed in /usr/local/cuda/lib64 (or similar) by default (on linux). At about the CUDA 10.1 timeframe, it was decided that some libraries would be installed in different places. CUDA 10.1 is also where the cublasLt API and library were introduced. This affected some cublas libraries and is discussed in the CUDA 10.1 release notes here (both the introduction of the cublasLt library, as well as the change in library locations).
So there are 2 possibilities here (for CUDA 10.1, CUDA 10.2):
libcublasLt.so is on your machine, but it is simply not where you were expecting to find it.
libcublasLt.so is not on your machine. This means you are working with CUDA version prior to the introduction of the cublasLt API (i.e. 10.0 or prior), or you have a broken install.
So, assuming you are working with CUDA 10.1 or CUDA 10.2, the first step is to locate/determine whether libcublasLt.so is on your machine or not. You can use a linux utility like find or locate to accomplish that. They should have man pages available for you.
If you can find it, then you need to provide the path to it, via a linker spec (e.g. -L/path/to/libcublasLt.so/
If you can't find it, then either you are working with an older version of CUDA (10.0 or prior), or you need to reinstall CUDA.
I believe by the time you get to CUDA 11.0, the CUDA packages put the cublas libraries back in /usr/local/cuda/lib64 with the other libraries. YMMV.
I am trying to load few modules onto Tizen on my MIPS-based platform. Currently, I am using sourcery codebench gnu linux compiler. The libc.so files it uses have version 2.17 which libc.so file on my platform has version 2.13. I need a toolchain which has a version less than or equal to 2.13 and supports MIPS.
Thanks,
Atchyut Sreekar
few options:
talk to the Tizen people to see if they have pre-compiled toolchains that match your system
build the code directly on the device
use crosstool-ng to build a new cross-compiler but with an old glibc version
upgrade your system because glibc-2.13 (and glibc-2.17 for that matter) are ridiculously old and have a large number of known security vulnerabilities including remote exploits. developing & deploying anything based on those glibc versions is a terrible terrible mistake.
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 have an i386 binary that I would like to run on my STB with embedded linux.
How to run the i386 binary (compiled on Ubuntu / compiler : i486-linux-gnu-libusb) on MIPS arch platform (set-top box)?
You need an emulator. The most well-known emulators are qemu and bochs which are both open-source
However emulation is slow by nature, so it's only used for non-performance-critical applications that no source code is available. Real-time software like decoders in a set-top-box definitely isn't suitable to execute under emulation. You need to rebuild the software to MIPS target
See also
How to run a MIPS binary on x86 platform?
How can I execute MIPS assembly programs on an x86 linux?
I'm trying to do some CUDA development on a PC without CUDA-capable GPU via emulation mode. The OS is Linux Mint Debian (can be considered Debian testing for all practical purposes) 32bit (2.6.32-5-686 kernel). Here's what I did so far:
Grabbed the CUDA Toolkit 32 bit and SDK for Ubuntu from http://developer.nvidia.com/cuda-toolkit-40
Installed the CUDA Toolkit in /usr/local/cuda/lib
Added the paths to bashrc
echo "# CUDA stuff
PATH=\$PATH:/usr/local/cuda/bin
LD_LIBRARY_PATH=\$LD_LIBRARY_PATH:/usr/local/cuda/lib
export PATH
export LD_LIBRARY_PATH" >> ~/.bashrc
Added the path to /etc/ld.so.conf.d/cuda.conf:
/usr/local/cuda/lib
Executed "sudo ldconfig"
Restarted the session
Then installed the SDK in /home/user/NVIDIA_GPU_Computing_SDK folder
When I got to NVIDIA_GPU_Computing_SDK/C and type "make emu=1" to compile the examples I get:
nvcc warning : option 'device-emulation' has been deprecated and is ignored
/usr/bin/ld: cannot find -lcudartemu
/usr/bin/ld: cannot find -lcudartemu
collect2: ld returned 1 exit status
Seems like a library missing (rt = runtime ?). There is libcudart3 in the package manager, but wants a whole bunch of nvidia stuff as a dependency, including drivers and I don't even have an NVIDIA card on this machine. Also apparently the GPU emulation is now deprecated... Does anybody have some experience with CUDA emulation?
There is no emulation in CUDA any more. It was deprecated and removed during the 3.x release cycle. There is no emulation support beyond CUDA 3.1 IIRC. Certainly there is nothing you can do in CUDA 4.0.
On Linux, your best bet is to try gpuocelot, which provides a PTX level emulation on x86 processors and a reimplementation of the CUDA APIs.
Although I agree with the suggestion to try Ocelot, when I was in the same boat I found it easiest to go on eBay and get a cheap CUDA capable card to use for testing (I think I paid < $40). If you have the ability to open the hardware (I realize this isn't an option for some people) and to install drivers, that's what I'd suggest.