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  • How to solve CUDA crash when run CUDA example fluidsGL?

    - by sam
    I use ubuntu 12.04 64 bits with GTX560Ti. I install CUDA by following instruction: wget http: //developer.download.nvidia.com/compute/cuda/4_2/rel/toolkit/cudatoolkit_4.2.9_lin ux_64_ubuntu11.04.run wget http: //developer.download.nvidia.com/compute/cuda/4_2/rel/drivers/devdriver_4.2_linux _64_295.41.run wget http: //developer.download.nvidia.com/compute/cuda/4_2/rel/sdk/gpucomputingsdk_4.2.9 _linux.run chmod +x cudatoolkit_4.2.9_linux_64_ubuntu11.04.run sudo ./cudatoolkit_4.2.9_linux_64_ubuntu11.04.run echo "/usr/local/cuda/lib64" > ~/cuda.conf echo "/usr/local/cuda/lib" >> ~/cuda.conf sudo mv ~/cuda.conf /etc/ld.so.conf.d/cuda.conf sudo ldconfig echo 'export PATH=$PATH:/usr/local/cuda/bin' >> ~/.bashrc chmod +x gpucomputingsdk_4.2.9_linux.run ./gpucomputingsdk_4.2.9_linux.run sudo apt-get install build-essential libx11-dev libglu1-mesa-dev freeg lut3-dev libxi-dev libxmu-dev gcc-4.4 g++-4.4 sed 's/g++ -fPIC/g++-4.4 -fPIC/g' ~/NV IDIA_GPU_Computing_SDK/C/common/common.mk > ~/NVIDIA_GPU_Computing_SDK/C/common/common.mk.bak; mv ~/NVIDIA_GPU_Computing_SDK/C/common/common.mk.bak ~/NVIDIA_GPU_Computing_SDK/C/common/common.mk sed 's/gcc -fPIC/gcc-4.4 -fPIC/g' ~/NV IDIA_GPU_Computing_SDK/C/common/common.mk > ~/NVIDIA_GPU_Computing_SDK/C/common/common.mk.bak; mv ~/NVIDIA_GPU_Computing_SDK/C/common/common.mk.bak ~/NVIDIA_GPU_Computing_SDK/C/common/common.mk sed 's/-L$(SHAREDDIR)\/lib/-L$(SHAREDDIR)\/lib -L\/u sr\/lib\/nvidia-current/g' ~/NVIDIA_GPU_Computing_SDK/C/common/common.mk > ~/NVIDIA_GPU_Computing_SDK/C/common/common.mk.bak; mv ~/NVIDIA_GPU_Computing_SDK/C/common/common.mk.bak ~/NVIDIA_GPU_Computing_SDK/C/common/common.mk sed 's/-L$(SHAREDDIR)\/lib -L\/usr\/lib\/nvidia-current $(NV CUVIDLIB)/-L$(SHAREDDIR)\/lib $(NVCUVIDLIB)/g' ~/NVIDIA_GPU_Computing_SDK/C/common/common.mk > ~/NVIDIA_GPU_Computing_SDK/C/common/common.mk.bak; mv ~/NVIDIA_GPU_Computing_SDK/C/common/common.mk.bak ~/NVIDIA_GPU_Computing_SDK/C/common/common.mk After I run ~/NVIDIA_GPU_Computing_SDK/C/bin/linux/release/./fluidsGL It got stuck even mouse or keyboard couldn't move. How to solve it? Thank you~

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  • CUDA Driver API vs. CUDA runtime

    - by Morten Christiansen
    When writing CUDA applications, you can either work at the driver level or at the runtime level as illustrated on this image (The libraries are CUFFT and CUBLAS for advanced math): I assume the tradeoff between the two are increased performance for the low-evel API but at the cost of increased complexity of code. What are the concrete differences and are there any significant things which you cannot do with the high-level API? I am using CUDA.net for interop with C# and it is built as a copy of the driver API. This encourages writing a lot of rather complex code in C# while the C++ equivalent would be more simple using the runtime API. Is there anything to win by doing it this way? The one benefit I can see is that it is easier to integrate intelligent error handling with the rest of the C# code.

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  • CUDA & MSI GT60 with Optimus enabled GTX670M?

    - by user1076693
    I have a MSI GT60 Laptop with an Optimus enabled GTX 670M GPU, and I have been trying to get CUDA going in Ubuntu 12.04 environment. I realize that Optimus is not supported in Linux, but I have read the following post suggesting that CUDA works for hybrid GPUs. How can I get nVidia CUDA or OpenCL working on a laptop with nVidia discrete card/Intel Integrated Graphics? I installed the NVIDIA driver via sudo add-apt-repository ppa:ubuntu-x-swat/x-updates sudo apt-get update sudo apt-get install nvidia-current The resulting driver version is 302.17, and supposedly GTX 670M is supported since 295.59. I also downloaded CUDA 4.2 from the NVIDIA site, and compiled it against nvidia-current libraries. Unfortunately, when I run deviceQuery in the CUDA SDK, I get the following output cudaGetDeviceCount returned 38 -> no CUDA-capable device is detected Checking /proc/driver/nvidia/gpus/0/information gives the following Model: GeForce GTX 670M IRQ: 16 GPU UUID: GPU-????????-????-????-????-???????????? Video BIOS: ??.??.??.??.?? Bus Type: PCI-E DMA Size: 32 bits DMA Mask: 0xffffffffff Bus Location: 0000:01.00.0 Here is the output of "lspci | grep VGA" 00:02.0 VGA compatible controller: Intel Corporation Ivy Bridge Graphics Controller (rev 09) 01:00.0 VGA compatible controller: NVIDIA Corporation Device 1213 (rev ff) So... what am I doing wrong? Thanks!

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  • Updating a Cuda 4.0 project to Cuda 4.2

    - by aljndrrr
    I have a VS2010 project that was tested with CUDA 4.0, today I installed CUDA 4.2 and I want to update this project, the problem is that when I try to run the project it asks me for cudart32_40_17.dll, but since this is CUDA 4.2 I only have on my folders (C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v4.2\bin) cudart32_42_9.dll. I already set the Build Customizations to Cuda 4.2 and it compiles without any problem, the only problem is when I try to run it, the app asks me for the previous version of the dll. Is there a way to especify that the project must use cudart32_42_9.dll?

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  • Cuda driver, CPU/GPU performances issue

    - by elect
    I implemented a RNS Montgomery exponentiation in Cuda and on cpu for comparison. Everything nice everything fine. It runs on just one SM. However I am going to tell you some strange regression in both cpu/gpu performances. During the devoloping, about two month ago, I was using Cuda 5 preview on Ubuntu 11.04 64b. In this time, I reach the following performances: cpu 460ms gpu 120ms Then one day when I turn on the pc, the graphical environment didnt start. I dont know which was the problem, however I switched to the console and installed again the Cuda driver. At the following boot performances changed: cpu 310ms gpu 80ms I was like Q.Q...uhm ok, nice to see this, but I was wondering how that could be possible However, I went then in holiday for 10 days and I continued developing and optimizing on my notebook (but not the same part of the code, some additional stuff) When I was back, I just updated the source files, and performances came back to 460/120ms.. I couldnt believe it, I tried to install Cuda 5 RC, updating the video driver too... nothing changed... I checked Debug/Release, Cuda computability, but the problem seems being somewhere else.. Looking around the net I found this, I am pretty sure it must have something to do with the driver, because the performance change affected both cpu and gpu Do you have some tips/ideas/suggestions?

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  • CUDA on GeForce 8600GT

    - by viswanathgs
    I have got the cuda driver, toolkit and sdk installed in Ubuntu 10.04. I'm using nVidia Geforce 8600 GT card. Official website says my card is CUDA supported. But on running the deviceQuery that comes with the cuda sdk, I'm getting the following output. ./deviceQuery Starting... CUDA Device Query (Runtime API) version (CUDART static linking) There is no device supporting CUDA deviceQuery, CUDA Driver = CUDART, CUDA Driver Version = 134566327, CUDA Runtime Version = 0.0, NumDevs = 0 PASSED Press <Enter> to Quit... So, is GeForce 8600GT actually not CUDA supported, or is the problem with something else? Thanks.

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  • Context migration in CUDA.NET

    - by Vyacheslav
    I'm currently using CUDA.NET library by GASS. I need to initialize cuda arrays (actually cublas vectors, but it doesn't matters) in one CPU thread and use them in other CPU thread. But CUDA context which holding all initialized arrays and loaded functions, can be attached to only one CPU thread. There is mechanism called context migration API to detach context from one thread and attach it to another. But i don't how to properly use it in CUDA.NET. I tried something like this: class Program { private static float[] vector1, vector2; private static CUDA cuda; private static CUBLAS cublas; private static CUdeviceptr ptr; static void Main(string[] args) { cuda = new CUDA(false); cublas = new CUBLAS(cuda); cuda.Init(); cuda.CreateContext(0); AllocateVectors(); cuda.DetachContext(); CUcontext context = cuda.PopCurrentContext(); GetVectorFromDeviceAsync(context); } private static void AllocateVectors() { vector1 = new float[]{1f, 2f, 3f, 4f, 5f}; ptr = cublas.Allocate(vector1.Length, sizeof (float)); cublas.SetVector(vector1, ptr); vector2 = new float[5]; } private static void GetVectorFromDevice(object objContext) { CUcontext localContext = (CUcontext) objContext; cuda.PushCurrentContext(localContext); cuda.AttachContext(localContext); //change vector somehow vector1[0] = -1; //copy changed vector to device cublas.SetVector(vector1, ptr); cublas.GetVector(ptr, vector2); CUDADriver.cuCtxPopCurrent(ref localContext); } private static void GetVectorFromDeviceAsync(CUcontext cUcontext) { Thread thread = new Thread(GetVectorFromDevice); thread.IsBackground = false; thread.Start(cUcontext); } } But execution fails on attempt to copy changed vector to device because context is not attached? Any ideas how i can get it work?

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  • Cuda vs OpenCL - opinions

    - by Martin Beckett
    Interested in peoples opinions of Cuda vs openCL following NVidia's Cuda4 release. I had originally gone with openCL since cross platform, open standards are a good thing(tm). I assumed NVidia would fall into line as they had done with openGL. But having talked to some NVidia people, they (naturaly) claim that they will concentrate on CUDA and openCL is hampered by having committees and having to please everyone - like openGL. And with the new tools and libs in CUDA it's hard to argue with that. -I'm in a fairly technical market so I can require the users to have particular HW.

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  • Cuda GeForce GT 555m (on Ubuntu 12.04 (Virtual Box))

    - by bobby
    I am running Ubuntu 12.04 in a Virtual Box as guest OS. Today I have tried to enable all functions of my graphic card under Ubuntu. But all my efforts were off the mark... because my experience with Linux is relatively small... I have tried the procedure which is described as in http://sn0v.wordpress.com/2012/05/11/installing-cuda-on-ubuntu-12-04/. Running the cuda-filepack always lead to an error like "installing driver canceled". Then I have tried to install the Bumblebee project. But I always get the error that the bumblebee daemon is not started. After some internet research I found a test-command lspci -nn | grep '[030[02]]' which results in 00:02.0 VGA compatible controller [0300]: InnoTek ... [80ee:beef] I've been trying to activate the card you for hours without success. Could you please give me some hints how to activate CUDA? Kind regards

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  • Installing CUDA on Ubuntu 12.04 with nvidia driver 295.59

    - by johnmcd
    I have been trying to get cuda to run on a nvidia gt 650m based laptop. I am running Ubuntu 12.04 with the nvidia 295.59 driver. Also, my laptop uses Optimus so I have install the driver via bumblebee. Bumblebee is not working correctly yet -- however I believe it is possible to install CUDA independently. To install CUDA I have followed the instructions detailed here: How can I get nVidia CUDA or OpenCL working on a laptop with nVidia discrete card/Intel Integrated Graphics? However I am still running into problem building the sdk. I made the changes specified at the above link in common.mk, but I got the following (snippet) from the build process: make[2]: Entering directory `/home/john/NVIDIA_GPU_Computing_SDK/C/src/fluidsGL' /usr/bin/ld: warning: libnvidia-tls.so.302.17, needed by /usr/lib/nvidia-current/libGL.so, not found (try using -rpath or -rpath-link) /usr/bin/ld: warning: libnvidia-glcore.so.302.17, needed by /usr/lib/nvidia-current/libGL.so, not found (try using -rpath or -rpath-link) /usr/lib/nvidia-current/libGL.so: undefined reference to `_nv018tls' /usr/lib/nvidia-current/libGL.so: undefined reference to `_nv012glcore' /usr/lib/nvidia-current/libGL.so: undefined reference to `_nv017glcore' /usr/lib/nvidia-current/libGL.so: undefined reference to `_nv012tls' /usr/lib/nvidia-current/libGL.so: undefined reference to `_nv015tls' /usr/lib/nvidia-current/libGL.so: undefined reference to `_nv019tls' /usr/lib/nvidia-current/libGL.so: undefined reference to `_nv000glcore' /usr/lib/nvidia-current/libGL.so: undefined reference to `_nv017tls' /usr/lib/nvidia-current/libGL.so: undefined reference to `_nv013tls' /usr/lib/nvidia-current/libGL.so: undefined reference to `_nv013glcore' /usr/lib/nvidia-current/libGL.so: undefined reference to `_nv018glcore' /usr/lib/nvidia-current/libGL.so: undefined reference to `_nv022tls' /usr/lib/nvidia-current/libGL.so: undefined reference to `_nv007tls' /usr/lib/nvidia-current/libGL.so: undefined reference to `_nv009tls' /usr/lib/nvidia-current/libGL.so: undefined reference to `_nv020tls' /usr/lib/nvidia-current/libGL.so: undefined reference to `_nv014glcore' /usr/lib/nvidia-current/libGL.so: undefined reference to `_nv015glcore' /usr/lib/nvidia-current/libGL.so: undefined reference to `_nv016tls' /usr/lib/nvidia-current/libGL.so: undefined reference to `_nv001glcore' /usr/lib/nvidia-current/libGL.so: undefined reference to `_nv006tls' /usr/lib/nvidia-current/libGL.so: undefined reference to `_nv021tls' /usr/lib/nvidia-current/libGL.so: undefined reference to `_nv011tls' /usr/lib/nvidia-current/libGL.so: undefined reference to `_nv020glcore' /usr/lib/nvidia-current/libGL.so: undefined reference to `_nv019glcore' /usr/lib/nvidia-current/libGL.so: undefined reference to `_nv002glcore' /usr/lib/nvidia-current/libGL.so: undefined reference to `_nv021glcore' /usr/lib/nvidia-current/libGL.so: undefined reference to `_nv014tls' collect2: ld returned 1 exit status make[2]: *** [../../bin/linux/release/fluidsGL] Error 1 make[2]: Leaving directory `/home/john/NVIDIA_GPU_Computing_SDK/C/src/fluidsGL' make[1]: *** [src/fluidsGL/Makefile.ph_build] Error 2 make[1]: Leaving directory `/home/john/NVIDIA_GPU_Computing_SDK/C' make: *** [all] Error 2 The libraries that ld warns about are on my system and are installed on the system: $ locate libnvidia-tls.so.302.17 libnvidia-glcore.so.302.17 /usr/lib/nvidia-current/libnvidia-glcore.so.302.17 /usr/lib/nvidia-current/libnvidia-tls.so.302.17 /usr/lib/nvidia-current/tls/libnvidia-tls.so.302.17 /usr/lib32/nvidia-current/libnvidia-glcore.so.302.17 /usr/lib32/nvidia-current/libnvidia-tls.so.302.17 /usr/lib32/nvidia-current/tls/libnvidia-tls.so.302.17 however /usr/lib/nvidia-current and /usr/lib32/nvidia-current are not being picked up by ldconfig. I have tried adding them by adding a file to /etc/ld.so.conf.d/ which gets past this error, however now I am getting the following error: make[2]: Entering directory `/home/john/NVIDIA_GPU_Computing_SDK/C/src/deviceQueryDrv' cc1plus: warning: command line option ‘-Wimplicit’ is valid for C/ObjC but not for C++ [enabled by default] obj/x86_64/release/deviceQueryDrv.cpp.o: In function `main': deviceQueryDrv.cpp:(.text.startup+0x5f): undefined reference to `cuInit' deviceQueryDrv.cpp:(.text.startup+0x99): undefined reference to `cuDeviceGetCount' deviceQueryDrv.cpp:(.text.startup+0x10b): undefined reference to `cuDeviceComputeCapability' deviceQueryDrv.cpp:(.text.startup+0x127): undefined reference to `cuDeviceGetName' deviceQueryDrv.cpp:(.text.startup+0x16a): undefined reference to `cuDriverGetVersion' deviceQueryDrv.cpp:(.text.startup+0x1f0): undefined reference to `cuDeviceTotalMem_v2' deviceQueryDrv.cpp:(.text.startup+0x262): undefined reference to `cuDeviceGetAttribute' deviceQueryDrv.cpp:(.text.startup+0x457): undefined reference to `cuDeviceGetAttribute' deviceQueryDrv.cpp:(.text.startup+0x4bc): undefined reference to `cuDeviceGetAttribute' deviceQueryDrv.cpp:(.text.startup+0x502): undefined reference to `cuDeviceGetAttribute' deviceQueryDrv.cpp:(.text.startup+0x533): undefined reference to `cuDeviceGetAttribute' obj/x86_64/release/deviceQueryDrv.cpp.o:deviceQueryDrv.cpp:(.text.startup+0x55e): more undefined references to `cuDeviceGetAttribute' follow collect2: ld returned 1 exit status make[2]: *** [../../bin/linux/release/deviceQueryDrv] Error 1 make[2]: Leaving directory `/home/john/NVIDIA_GPU_Computing_SDK/C/src/deviceQueryDrv' make[1]: *** [src/deviceQueryDrv/Makefile.ph_build] Error 2 make[1]: Leaving directory `/home/john/NVIDIA_GPU_Computing_SDK/C' make: *** [all] Error 2 I would appreciate any help that anyone can provide me with. If I can provide any further information please let me know. Thanks.

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  • Error while compiling Cuda Accelerated Linpack hpl_2.0_FERMI

    - by ghostrustam
    I use Ubuntu 11.04 x86_64 CUDA 4.0 OpenMpi 1.4stable MKL When I compile, I get this error: ar r -L/home/limksadmin/hpl-2.0_FERMI_v13/lib/CUDA/libhpl.a HPL_dlacpy.o HPL_dlatcpy.o HPL_fprintf.o HPL_warn.o HPL_abort.o HPL_dlaprnt.o HPL_dlange.o HPL_dlamch.o ar: -L/home/limksadmin/hpl-2.0_FERMI_v13/lib/CUDA/libhpl.a: No such file or directory make[2]: *** [lib.grd] Error 9 make[2]: Leaving directory `/home/limksadmin/hpl-2.0_FERMI_v13/src/auxil/CUDA' make[1]: *** [build_src] Error 2 make[1]: Leaving directory `/home/limksadmin/hpl-2.0_FERMI_v13' make: *** [build] Error 2 Make.CUDA: LAdir = /opt/intel/mkl/lib/intel64 LAlib = -L $(TOPdir)/src/cuda -ldgemm -L/usr/local/cuda/lib64 -lcuda -lcudart -lcublas -L$(LAdir) -lmkl_intel_lp64 -lmkl_intel_thread -lmkl_core -liomp5 MPdir = /usr/local/mpi/openmpi MPinc = -I$(MPdir)/include MPlib = -L$(MPdir)/lib/libmpi.so CC = /usr/local/mpi/openmpi/bin/mpicc What could be the problem?

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  • CUDA instructions ask to stop GDM but it doesn't exist

    - by Gabs
    I am trying to install and run some CUDA exemples in Ubuntu 12.04. First of all, I downloaded all .run files from http://developer.nvidia.com/cuda-downloads, then followed the instructions at http://developer.nvidia.com/nvidia-gpu-computing-, until I got hung up on the first step: Exit the GUI if you are in a GUI environment by pressing Ctrl-Alt-Backspace. Some distributions require you to press this sequence twice in a row; others have disabled it altogether in favor of a command such as sudo /etc/init.d/gdm stop . Still others require changing the system runlevel using a command such as /sbin/init 3 to exit the GUI. When I type the command sudo /etc/init.d/gdmstop, it returns: gdm command not found Can anybody help me exit my GUI in order to continue? Thank you in advance.

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  • Is there a way to run CUDA applications with the CUDA device being a secondary adapter?

    - by Slartibartfast
    I've been trying to run a CUDA program on a remote computer which has Windows 7 installed. The GPU is GeForce GTX 480. One of the problems I've been facing is that, the computer has two adapters, 1) Standard VGA Adapter 2) NVIDIA GeForce GTX 480 Even though this shows in the device manager. The desktop uses the standard VGA Adapter. I'm assuming this is because the Standard VGA is the primary adapter. Also the device manager shows that the monitor is connected to the standard VGA Adapter. In this scenario if i try to run any CUDA application it fails to recognise a CUDA capable device. Is it necessary for the NVIDIA adapter to be the primary one? Or is there any way to use CUDA when the graphics card is a secondary adapter. I've seen a few posts in the NVIDIA forums on this before, one suggests using another low cost NVIDIA card as the primary adapter, but that is currently not an option. I couldn't find any other solutions. Thanks I tried running the deviceQuery test from the NVIDIA GPU Computing Samples. This was the result i obtained CUDA Device Query (Runtime API) version (CUDART static linking) cudaGetDeviceCount FAILED CUDA Driver and Runtime version may be mismatched FAILED The driver version I'm using is 263.06. The CUDA version is 3.2 I ran the same test on my desktop which also has windows 7 and a GeForce GTX 465. The CUDA toolkit version is 3.2. The driver version was the same and the test passed, although it failed with an older driver.

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  • I attempted to install cuda drivers, and now almost everything is broken

    - by Nathan
    I tried to install CUDA tookit 5.0 on ubuntu 12.04 and the installation proceeded OK. After rebooting however, all I get is a terminal login. I've attempted to start the display manager with sudo start lightdm and it says all OK, but just hangs the prompt when it finishes loading without ever starting any display manager. sudo start gdm just flickers and goes back to the prompt. There is no network connection on the machine either. It usually connects to a wireless network with remembered credentials. What can I do to recover the machine?

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  • CUDA compare arrays

    - by user315511
    Hello. Trying to make an app that will compare 1-to-multiple bitmaps. there is one reference bitmap and multiple other bitmaps. Result from each compare should be new bitmap with diffs. Maybe comparing bitmaps rather as textures than arrays? My biggest problem is making kernel accept more than one input pointer, and how to compare the data.. extern "C" __global__ void compare(float *odata, float *idata, int width, int height) works and following does not (i call the function with enough params) extern "C" __global__ void compare(float *odata, float *idata, float *idata2, int width, int height)

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  • Dual monitor in Ubuntu 12.04 + Nvidia GPU with CUDA drivers?

    - by Aphex
    I'm thinking about setting up dual monitors on my desktop PC, running Ubuntu 12.04 with a Nvidia GTX 570. I use the GPU for CUDA programming so it's set up with the CUDA drivers. Is it possible/easy to set up dual monitors with this configuration? The only questions I saw related to this were for GPUs without cuda drivers. If anyone knows how dual monitors work with CUDA drivers, it would be much appreciated. It was enough of a pain getting everything running with the GPU and CUDA in the first place, I'd hate to ruin it all by attempting dual monitors.

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  • CUDA not working in 64 bit windows 7

    - by Programmer
    I have cuda toolkit 4.0 installed in a 64 bit windows 7. I try building my cuda code, #include<iostream> #include"cuda_runtime.h" #include"cuda.h" __global__ void kernel(){ } int main(){ kernel<<<1,1>>>(); int c = 0; cudaGetDeviceCount(&c); cudaDeviceProp prop; cudaGetDeviceProperties(&prop, 0); std::cout<<"the name is"<<prop.name; std::cout<<"Hello World!"<<c<<std::endl; system("pause"); return 0; } but operation fails. Below is the build log: Build Log Rebuild started: Project: god, Configuration: Debug|Win32 Command Lines Creating temporary file "c:\Users\t-sudhk\Documents\Visual Studio 2008\Projects\god\god\Debug\BAT0000482007500.bat" with contents [ @echo off echo "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v4.0\bin\nvcc.exe" -gencode=arch=compute_10,code=\"sm_10,compute_10\" -gencode=arch=compute_20,code=\"sm_20,compute_20\" --machine 32 -ccbin "C:\Program Files (x86)\Microsoft Visual Studio 9.0\VC\bin" -Xcompiler "/EHsc /W3 /nologo /O2 /Zi /MT " -I"C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v4.0\include" -maxrregcount=0 --compile -o "Debug/sample.cu.obj" sample.cu "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v4.0\bin\nvcc.exe" -gencode=arch=compute_10,code=\"sm_10,compute_10\" -gencode=arch=compute_20,code=\"sm_20,compute_20\" --machine 32 -ccbin "C:\Program Files (x86)\Microsoft Visual Studio 9.0\VC\bin" -Xcompiler "/EHsc /W3 /nologo /O2 /Zi /MT " -I"C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v4.0\include" -maxrregcount=0 --compile -o "Debug/sample.cu.obj" "c:\Users\t-sudhk\Documents\Visual Studio 2008\Projects\god\god\sample.cu" if errorlevel 1 goto VCReportError goto VCEnd :VCReportError echo Project : error PRJ0019: A tool returned an error code from "Compiling with CUDA Build Rule..." exit 1 :VCEnd ] Creating command line """c:\Users\t-sudhk\Documents\Visual Studio 2008\Projects\god\god\Debug\BAT0000482007500.bat""" Creating temporary file "c:\Users\t-sudhk\Documents\Visual Studio 2008\Projects\god\god\Debug\RSP0000492007500.rsp" with contents [ /OUT:"C:\Users\t-sudhk\Documents\Visual Studio 2008\Projects\god\Debug\god.exe" /LIBPATH:"C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v4.0\lib\x64" /MANIFEST /MANIFESTFILE:"Debug\god.exe.intermediate.manifest" /MANIFESTUAC:"level='asInvoker' uiAccess='false'" /DEBUG /PDB:"C:\Users\t-sudhk\Documents\Visual Studio 2008\Projects\god\Debug\god.pdb" /DYNAMICBASE /NXCOMPAT /MACHINE:X86 cudart.lib cuda.lib kernel32.lib user32.lib gdi32.lib winspool.lib comdlg32.lib advapi32.lib shell32.lib ole32.lib oleaut32.lib uuid.lib odbc32.lib odbccp32.lib ".\Debug\sample.cu.obj" ] Creating command line "link.exe @"c:\Users\t-sudhk\Documents\Visual Studio 2008\Projects\god\god\Debug\RSP0000492007500.rsp" /NOLOGO /ERRORREPORT:PROMPT" Output Window Compiling with CUDA Build Rule... "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v4.0\bin\nvcc.exe" -gencode=arch=compute_10,code=\"sm_10,compute_10\" -gencode=arch=compute_20,code=\"sm_20,compute_20\" --machine 32 -ccbin "C:\Program Files (x86)\Microsoft Visual Studio 9.0\VC\bin" -Xcompiler "/EHsc /W3 /nologo /O2 /Zi /MT " -I"C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v4.0\include" -maxrregcount=0 --compile -o "Debug/sample.cu.obj" sample.cu sample.cu sample.cu.obj : error LNK2019: unresolved external symbol _cudaLaunch@4 referenced in function "enum cudaError cdecl cudaLaunch(char *)" (??$cudaLaunch@D@@YA?AW4cudaError@@PAD@Z) sample.cu.obj : error LNK2019: unresolved external symbol ___cudaRegisterFunction@40 referenced in function "void __cdecl _sti_cudaRegisterAll_52_tmpxft_00001c68_00000000_8_sample_compute_10_cpp1_ii_b81a68a1(void)" (?sti__cudaRegisterAll_52_tmpxft_00001c68_00000000_8_sample_compute_10_cpp1_ii_b81a68a1@@YAXXZ) sample.cu.obj : error LNK2019: unresolved external symbol _cudaRegisterFatBinary@4 referenced in function "void __cdecl _sti_cudaRegisterAll_52_tmpxft_00001c68_00000000_8_sample_compute_10_cpp1_ii_b81a68a1(void)" (?sti__cudaRegisterAll_52_tmpxft_00001c68_00000000_8_sample_compute_10_cpp1_ii_b81a68a1@@YAXXZ) sample.cu.obj : error LNK2019: unresolved external symbol _cudaGetDeviceProperties@8 referenced in function _main sample.cu.obj : error LNK2019: unresolved external symbol _cudaGetDeviceCount@4 referenced in function _main sample.cu.obj : error LNK2019: unresolved external symbol _cudaConfigureCall@32 referenced in function _main C:\Users\t-sudhk\Documents\Visual Studio 2008\Projects\god\Debug\god.exe : fatal error LNK1120: 7 unresolved externals Results Build log was saved at "file://c:\Users\t-sudhk\Documents\Visual Studio 2008\Projects\god\god\Debug\BuildLog.htm" god - 8 error(s), 0 warning(s) I will be highly obliged if someone could help me. Thanks

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  • cuda install in ubuntu13.10?

    - by hexiangpeng
    the cuda_install_.log show ERROR: Unable to build the NVIDIA kernel module. ERROR: Installation has failed. Please see the file '/var/log/nvidia-installer.log' for details. You may find suggestions on fixing installation problems in the README available on the Linux driver download page at www.nvidia.com. The driver installation is unable to locate the kernel source. Please make sure that the kernel source packages are installed and set up correctly. and the other .log show ^ /tmp/selfgz3964/NVIDIA-Linux-x86-319.37/kernel/nv-i2c.c: In function ‘nv_i2c_del_adapter’: /tmp/selfgz3964/NVIDIA-Linux-x86-319.37/kernel/nv-i2c.c:327:14: error: void value not ignored as it ought to be osstatus = i2c_del_adapter(pI2cAdapter); ^ make[3]: * [/tmp/selfgz3964/NVIDIA-Linux-x86-319.37/kernel/nv-i2c.o] ?? 1 make[2]: * [module/tmp/selfgz3964/NVIDIA-Linux-x86-319.37/kernel] ?? 2 NVIDIA: left KBUILD. nvidia.ko failed to build! make[1]: * [module] ?? 1 make: * [module] ?? 2 - Error. ERROR: Unable to build the NVIDIA kernel module. ERROR: Installation has failed. Please see the file '/var/log/nvidia-installer.log' for details. You may find suggestions on fixing installation problems in the README available on the Linux driver download page at www.nvidia.com. i don't understand

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  • How recovery zip password using CUDA (GPU) ?

    - by marc
    Welcome, How can i recovery zip password on linux using CUDA (GPU). From 2 day's i'm trying using "fcrackzip" but it's too slow. Few months back i saw some application that can use GPU / CUDA and get large performance boost in compare to CPU. If brute-force using cuda is not possible, please tell me what's the best application for dictionary attack, and where can i find best (largest) dictionary. Regards

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  • Debuging CUDA kernels called from .NET code in VS2008, emulation mode

    - by Danny Varod
    CUDA has an option to compile code in emulation mode, which is supported in the .rules file they provide. I have C# .NET 3.5 SP1 code that calls a native dll, using DllImport, the native dll is compiled via VS2008 using nvcc and its function is to transfer memory from and to CUDA and to invoke CUDA kernels. When the CUDA kernels are correct, everything runs fine, but when there is a bug, I can only step in to the code until the title of the kernels and see the parameters they receive. (I enabled debugging native code in the startup-project's debug options.) I have tried compiling with emulation mode, however I get the CUDA error "mixed device execution" when calling the CUDA memcopy host--device. I tried switching the alloc+dealloc+memcopy with their equivalent non-CUDA versions, but then the same error occurs when invoking the kernels. What did I do wrong in my attempt to using the debug-emulation mode? P.S. I tried this on Vista x64 SP1 + VS2008, with the same solution complied in both x86 and x64, neither worked in emulation mode, both worked in non-emulation mode.

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  • Error while compiling Hello world program for CUDA

    - by footy
    I am using Ubuntu 12.10 and have sucessfully installed CUDA 5.0 and its sample kits too. I have also run sudo apt-get install nvidia-cuda-toolkit Below is my hello world program for CUDA: #include <stdio.h> /* Core input/output operations */ #include <stdlib.h> /* Conversions, random numbers, memory allocation, etc. */ #include <math.h> /* Common mathematical functions */ #include <time.h> /* Converting between various date/time formats */ #include <cuda.h> /* CUDA related stuff */ __global__ void kernel(void) { } /* MAIN PROGRAM BEGINS */ int main(void) { /* Dg = 1; Db = 1; Ns = 0; S = 0 */ kernel<<<1,1>>>(); /* PRINT 'HELLO, WORLD!' TO THE SCREEN */ printf("\n Hello, World!\n\n"); /* INDICATE THE TERMINATION OF THE PROGRAM */ return 0; } /* MAIN PROGRAM ENDS */ The following error occurs when I compile it with nvcc -g hello_world_cuda.cu -o hello_world_cuda.x /tmp/tmpxft_000033f1_00000000-13_hello_world_cuda.o: In function `main': /home/adarshakb/Documents/hello_world_cuda.cu:16: undefined reference to `cudaConfigureCall' /tmp/tmpxft_000033f1_00000000-13_hello_world_cuda.o: In function `__cudaUnregisterBinaryUtil': /usr/include/crt/host_runtime.h:172: undefined reference to `__cudaUnregisterFatBinary' /tmp/tmpxft_000033f1_00000000-13_hello_world_cuda.o: In function `__sti____cudaRegisterAll_51_tmpxft_000033f1_00000000_4_hello_world_cuda_cpp1_ii_b81a68a1': /tmp/tmpxft_000033f1_00000000-1_hello_world_cuda.cudafe1.stub.c:1: undefined reference to `__cudaRegisterFatBinary' /tmp/tmpxft_000033f1_00000000-1_hello_world_cuda.cudafe1.stub.c:1: undefined reference to `__cudaRegisterFunction' /tmp/tmpxft_000033f1_00000000-13_hello_world_cuda.o: In function `cudaError cudaLaunch<char>(char*)': /usr/lib/nvidia-cuda-toolkit/include/cuda_runtime.h:958: undefined reference to `cudaLaunch' collect2: ld returned 1 exit status I am also making sure that I use gcc and g++ version 4.4 ( As 4.7 there is some problem with CUDA)

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  • unable to cuda code

    - by cuda-dev
    I'm getting an error when i try to compile and build cuda code Error 1 error C2065: 'threadIdx' : undeclared identifier Error 2 error C2228: left of '.x' must have class/struct/union

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