parallel-processing,opencl,gpu,nvidia
Error codes are defined in <CL/cl.h> Error -45 is CL_INVALID_PROGRAM_EXECUTABLE. According to Khronos it means that "there is no successfully built executable for program". There is unnecessary inclusion at first raw of your kernel source. Delete it: #include <CL\cl.h> OpenCL C doesn't allow to include regular C/C++ headers. Only OpenCL...
You have to use the extension mechanism to query the function pointer in runtime, trying to directly link to a glX extension function is not guaranteed to work. Note that I assume you want glXSwapIntervalEXT instead of the glXSwapBufferEXT since the latter doesn't exist and the former is the only...
There are at least two gigantic, basic problems in this code, neither of which has anything to do with CUDA: histSize = sizeof(unsigned int) * xMax/cellWidth * yMax/cellHeight * numColors; //.... h = (unsigned int*) malloc(histSize); //..... for(i=0; i<histSize; i++) h[i]=0; // <-- buffer oveflow which is probably killing the...
android,nvidia,android-sensors
So.. I just found out where the problem was coming from. The magnetic cover of my tablet was messing with the magnetometer, resulting in the Game Rotation Vector sensor and the magnetic field sensor not sending data. I can't believe I spent hours scratching my head to fix this problem...
In your solution every NxN block of the matrix is being processed by separate NxN block of threads. In effect every individual thread does very little work, so overhead dominates actual computation. You could improve it by having thread blocks process more than one matrix block. But there is a...
c,memory-management,cuda,gpgpu,nvidia
In a UVA system, the runtime API function cudaPointerGetAttributes can provide additional information about pointers that are allocated with a runtime API function such as cudaMalloc or cudaHostAlloc. As discussed here, we can inferentially determine that the pointer must have been allocated by a non-CUDA function (e.g. malloc) if the...
A GPU context is described here. It represents all the state (data, variables, conditions, etc.) that are collectively required and instantiated to perform certain tasks (e.g. CUDA compute, graphics, H.264 encode, etc). A CUDA context is instantiated to perform CUDA compute activities on the GPU, either implicitly by the CUDA...
Your WPF app is a managed binary, and Nsight don't support launch managed files for Graphics debug. Thanks An...
c++,opengl,textures,nvidia,framebuffer
Im really out of ideas what I can do to make it work... Your OpenGL implementation tells you, that the configuration you choose is not supported. You have to accept that. The OpenGL specification does not require that particular combination of formats to be supported by all implementation, so...
You should read section J.2.2 of the programming guide (and preferably all of appendix J). With Unified Memory, memory allocated using cudaMallocManaged is by default attached to all streams ("global") and we must modify this in order to make effective use of streams, e.g. for compute/copy overlap. We can do...
You've got a situation here that is going to require relocatable device code linking (aka separate compilation/linking), but your Makefile is not set up properly for that. There are a number of situations that may require separate compilation and linking. One example, which is present in your project, is when...
Hyper-Q cannot be turned on/off. This is a hardware feature of Kepler cc3.5 and newer GPUs. The CUDA MPS server can be turned on/off. The method of turning it on and off is described in section 4.1.1 of the documentation. In a nutshell, excerpting: nvidia-cuda-mps-control -d # Start daemon as...
c++,visual-studio,opencv,nvidia,pdb
You can disable symbol loading for a module thus: (From https://msdn.microsoft.com/en-us/library/4c8f14c9.aspx) To change symbol load behavior for a specific module In the Modules window, right-click the module. Point to Automatic Symbol Load Settings and then click Always Load Manually or Default. Changes do not take effect until you restart the...
You are setting the wrong version macro to the SPS/PPS structure. I don't have my NVIDIA code by hand, so I'll try to Google the right macro but rule of the thumb is that each structure has a specific version macro (ans you are using NV_ENC_INITIALIZE_PARAMS for the SPS/PPS structure...
I think you have a basic vector manipulation error, having nothing to do with CUDA or Thrust. This creates a vector of length num_simulations: thrust::host_vector<Simulation> hv_simulations(num_simulations); This then appends another element to the end of the existing vector: hv_simulations.push_back(sim1); You can fix this by creating an empty vector: thrust::host_vector<Simulation> hv_simulations;...
Regarding this statement: Note: commom/inc is the folder provided by Nvidia in order to make Cuda compile correctly. That's a mischaracterization. The referenced files (cutil.h and cutil_math.h) and macros (e.g. CUT_CHECK_ERROR) were provided in fairly old CUDA releases (prior to CUDA 5.0) as part of the cuda sample codes that...
cuda,nvidia,nsight,amd-processor
Some of the NVIDIA CUDA samples that involve graphics, such as the Mandelbrot sample, implement an efficient rendering strategy: they bind OpenGL data structures - Pixel Vertex Objects in the case of Mandelbrot - to the CUDA arrays containing the simulation data and render them directly from the GPU. This...
Undefined reference to symbol XOpenDisplay refers to linker error, meaning there is a function call of XOpenDisplay in the object file but the linker is unable to determine which shared object (library) provides the function. The problem can be fixed by figuring out which library contains function XOpenDisplay and installing...
graphics,driver,nvidia,xserver,kubuntu
Fixed ! As the re-installation of the nvidia current driver version did not work I thought to install one other version. This link shows how to install NVIDIA driver on ubuntu : BinaryDriverHowto/Nvidia So I did exactly the same procedure as above but I replaced nvidia-current with nvidia-319. You can...
c,memory-management,cuda,nvidia,cosine
I was able to reproduce problematic behavior on a supported config (CUDA 6.5, CentOS 6.2, K40). When I switched from CUDA 6.5 to CUDA 7 RC, the problem went away. The problem also did not appear to be reproducible on an older config (CUDA 5.5, CentOS 6.2, M2070) I suggest...
The stock Linux kernel 3.10.40 does not have a firewire1394 driver. So, I added a firewire1394 driver. The "Grinch" kernel adds 1394 support. The Grinch kernel is available from: https://devtalk.nvidia.com/default/topic/823132/embedded-systems/-customkernel-the-grinch-21-3-4-for-jetson-tk1-developed/ I followed the instructions and finally I have the firewire1394 driver installed and loaded. To install CUDA and OpenCV4Tegra, one...
I believe I have found the reason for this behaviour. After further investigations (using Linux trace events and looking at the nvmap driver code) I found that the source of the overhead comes from the fact that data allocated with cudaHostAlloc() are marked "uncacheable" using the NVMAP_HANDLE_UNCACHEABLE flag. A call...
c,visual-studio-2013,opencl,gpu,nvidia
You have not clearly indicated that you are using Windows as OS but I assume it since you have the VS2013 tag in your question. The Nvidia card does not crash. On Windows you have Timeout Detection & Recovery (TDR) in the WDDM driver which restarts GPU drivers if they...
c,linux,cuda,parallel-processing,nvidia
Got it! Turns out it was a problem with the IOMMU kernel option enabled. My motherboard, GIGABYTE 990-FXAUD3 seems to have had an error with IOMMU between the GPU and the CPU. Detection: Whenever you launch Unified Memory accessing code in the console (without X), there should be an error...
cudaMemcpyAsync(m_haParticleID + m_OutputParticleStart,m_daOutputParticleID+ m_OutputParticleStart,size, cudaMemcpyDeviceToHost, m_CudaStream); cudaMemcpyAsync is a cuda runtime API call which is used to transfer data usually between the GPU and the host. This api call has the Async suffix because it must be called with a cuda stream designation, and returns control immediately to the host...
CompuBench may be useful where not only the benchmark results can be found but also a clGetDeviceInfo like info, for example: AMD Radeon™ R9 Series
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)...
You have to install the drivers for your integrated onboard gpu. This can be done by booting up while using iGPU from bios settings, and your pc shall be able to load the drivers it needs on its own. For my Ivy bridge, the bios settings are these: Go...
The application engines all deal with graphics problems, the principal use case of a GPU. But the point of CUDA is to task the GPU to do things other than graphics problems. The accelerated libraries involve things like linear algebra, calculation of Fourier Transforms, parallelization of general (non-graphic) computing problems,...
This is normal, when the driver packaged in the CUDA installer is "older" than your GPU. You should retain your current GPU driver, and go ahead with the CUDA toolkit installation, but de-select the option to install the GPU driver. Your existing driver should work fine. ...
linux,ubuntu-14.04,nvidia,firewire
Current running kernel Linux tegra-ubuntu 3.10.40-grinch-21.3.4 does not have v4l2loopback support. I used module assistant to compile v4l2loopback module. sudo aptitude install v4l2loopback-source module-assistant sudo module-assistant auto-install v4l2loopback-source Don't forget to mention the current running kernel headers. Then build and make v4l2loopback from here...
You don't need the ampersand on the symbol name. A symbol is not the same as a pointer or a variable. Instead of this: cudaStatus = cudaMemcpyToSymbol((void*)&var1,p1,sizeof(double),0,cudaMemcpyHostToDevice); Do this: cudaStatus = cudaMemcpyToSymbol(var1,&var1ToCopy,sizeof(double)); I've also simplified the above call based on the fact that some of the parameters have defaults as...
cuda,parallel-processing,nvidia
I'd suggest not implementing it yourself but using the random algorithms provided by Thrust: uint32_t seed = 1234; thrust::default_random_engine rng(seed); thrust::uniform_real_distribution<float> dist(0.0f, 1.0f); float random_value_1 = dist(rng); float random_value_2 = dist(rng); You can use this both in host and device code. Have a look at the Thrust examples....
Different from AMD sprofile, ./ is needed before the application name on Linux
Nvidia shield SoC is based on Tegra 4. Tegra K1 is the first Tegra processor you can write CUDA programs for. So you can expect it's not possible to have CUDA programs working on (current) Nvidia shield.
This is the answer given by njuffa in the comments: ...The content of GPU memory doesn't change between invocations of the application. In case of a program failure, we would want to avoid picking up good data from a previous run, which may lead (erroneously) to a belief that the...
linux,opencl,gpgpu,nvidia,pyopencl
NVIDIA have a whitepaper for the NVIDIA GeForce GTX 750 Ti, which is worth a read. An OpenCL compute unit translates to a streaming multiprocessor in NVIDIA GPU terms. Each Maxwell SMM in your GPU contains 128 processing elements ("CUDA cores") - and 128*5 = 640. The SIMD width of...
After hours of debugging, I found out that I forgot to set the Camera-parameters right, it had nothing to go to with the OpenGL stuff. My U-coordinate, the horizontal axis of view plane was messed up, but the V,W and eye coordinates were right. After I added these lines in...
You will have to install the flycapture sdk for ARM if you want to do it manually (by code). The flycap UI software i dont believe works on ARM, let alone ubuntu 14.04, just ubuntu 12.04 x86. If you have access, what I usually do is plug it into my...
java,opengl,lwjgl,nvidia,gldrawarrays
I found it: glEnableClientState(GL_VERTEX_ARRAY); glEnableClientState(GL_NORMAL_ARRAY); glEnableClientState(GL_TEXTURE_COORD_ARRAY); ... glDisableClientState(GL_VERTEX_ARRAY); glDisableClientState(GL_NORMAL_ARRAY); glDisableClientState(GL_TEXTURE_COORD_ARRAY); All client states have to be deactivated after every call on NVIDIA components....
No. nvprof v7.5 and earlier does not support collection of performance counters in a way that is useful for investigating the performance of concurrent kernels. I recommend you submit a feature request through the NVIDIA developer program. This is on the teams task list. Customer feedback helps move features up...
To compile a C/C++ OpenCL program on Windows using Cygwin or MinGW you need to: Make sure the OpenCL headers are on the include path. You can download them here. Link against a static OpenCL library (libopencl.a), which you already have. To run the program, it needs to find the...
CUDA threadblocks are limited to 1024 threads (or 512 threads, for cc 1.x gpus). The size of the threadblock is indicated in the second kernel configuration parameter in the kernel launch: even<<<3,SIZE>>>(d_A,SIZE); ^^^^ So when you enter a SIZE value greater than 1024, this kernel will not launch. You're getting...
The function you want to use is an extension function, and you will need to dynamically load it to a function pointer. I would suggest using any one the available extension loader libraries (glew, gl3w, glad...) to help simplifying this process. Alternatively, consider a higher level library like SDL which...
This is the standard CUDA idiom for determining the minimum number of blocks in each dimension (the "grid") that completely cover the desired input. This could be expressed as ceil(nx/block.x), that is, figure out how many blocks are needed to cover the desired size, then round up. But full floating...
The PTX file format is intended to describe a virtual machine and instruction set architecture: PTX defines a virtual machine and ISA for general purpose parallel thread execution. PTX programs are translated at install time to the target hardware instruction set. The PTX-to-GPU translator and driver enable NVIDIA GPUs to...
Combining information from the PTX manual and a simple inline-PTX wrapper, the following functions should give you what you need: static __device__ __inline__ uint32_t __mysmid(){ uint32_t smid; asm volatile("mov.u32 %0, %%smid;" : "=r"(smid)); return smid;} the above function will tell you which multiprocessor the (thread) code is executing on. static...
There is the NVIDIA test drive program that you could sign up for and try a high end tesla. http://www.nvidia.com/object/gpu-test-drive.html If you are familiar with linux: You can log into another persons computer with ssh (login and password is provided with test drive program) Copy of your code with scp...
It seems that you've made at least 1 error in transcribing the code from the GPU Gems 3 chapter into your kernel. This line is incorrect: temp[bi] += g_idata[ai]; it should be: temp[bi] += temp[ai]; When I make that one change to the code you have now posted, it seems...
cuda,gpgpu,nvidia,gpu-programming,multi-gpu
No. The GPU atomics are only atomic across the GPU performing the operation. They do not work on host memory or nonlocal device memory. I'm sure it is a roadmap item for NVIDIA to address these limitations on future platforms, esp. with NVLink....
First things first: The open source graphics drivers, all of them, use Mesa for the front side OpenGL interface and state tracking. Let's break this down: Theoretically a OpenGL implementation can directly talk to the hardware. This is what the NVidia and AMD proprietary drivers actually do. But in the...
Your edited code contains a number of absolutely elementary errors which have nothing to do with textures or their usage with streams: In the kernel, you have a broken printf statement which treats a floating point value as an integer In the host code, the host memory you use to...
It turns out my algorithm itself had to be re-worked, since there is no way to avoid the performance hit from non-coalesced operations with the above method. Instead, I was able to merge values on each block and use much less global memory. As a side note, I did some...
cuda,gpgpu,nvidia,gpu-programming,kepler
Yes, the warp schedulers in Kepler can schedule two instructions per clock, as long as: the instructions are independent the instructions come from the same warp there are sufficient execution resources in the SM for both instructions If that fits your definition of superscalar, then it is superscalar. With respect...
For now, it would be best to uninstall both of these packages (intel-opencl-sdk and intel-opencl-runtime) and install beignet from the AUR. https://aur.archlinux.org/packages/beignet/ The package provides the same functionality and allows you to use the Intel GPU cores also. I can confirm that it coexists well with other OpenCL platforms such...
What about constructing QImage directly? uchar* data = (uchar *)m_outputBuffer->map(); QImage img(data, m_width, m_height, QImage::Format_ARGB32); // or maybe Format_RGBA8888 would work for you.. you have to check docs m_outputBuffer->unmap(); img.save("optixSampleSix.png","PNG"); ...
That's correct. The CUDA 5.5 installer does not contain a compatible driver for your GPU. If you really want to use CUDA 5.5, then continue on past this screen. Deselect the option in a subsequent screen to install the GPU driver, but install the toolkit (and samples, if you wish)....
ubuntu,cuda,ubuntu-14.04,nvidia
304.xx is a driver that will support CUDA 5 and previous (does not support newer CUDA versions.) If you want to reinstall ubuntu to create a clean setup, the linux getting started guide has all the instructions needed to set up CUDA 7 if that is your intent. I believe...
kernelkernel<<<grid, 1>>> This is a significant issue; threads on nVidia GPUs work in warps of 32 threads. However, you've only assigned a single thread to each block, which means 31 of those threads will sit idle while a single thread does work. And usually, for kernels where you have the...
This is a bug in your code. The fileContents pointer your are giving to the driver is totally invalid, hence the driver crashes when dereferencing this pointer. You don't have a native string data type in C, you just work with arrays of char. And C won't do any kind...
opengl,architecture,cuda,gpgpu,nvidia
Most rendering tasks would be way harder to implement using CUDA. Shaders are fully integrated with rendering APIs, such as OpenGL, to automate and provide all the most common and efficient tools for rendering geometry. Things like texture sampling and polygon rasterisation are built-in all shading languages. If you where...
opencv,cuda,gpgpu,nvidia,opencv3.0
CascadeClassifier_GPU uses mixed GPU/CPU implementation and performs extra synchronizations internally, that's why it doesn't support asynchronous mode with gpu::Stream parameter. In order to launch it asynchronously with your code, you need to use separate CPU thread for it.
Look at the makefile that comes with that cdpSimpleQuicksort project. It shows some additional switches that are needed to compile it, due to CUDA dynamic parallelism (which is essentially the second set of errors you are seeing.) Go back and study that makefile, and see if you can figure out...
You have to use nvidiaLegacy304 instead of nvidia in the system.xserver.videoDrivers = [ "nvidia..." ]; declaration (use hardware.opengl.videoDrivers for the unstable channel).
For anyone interested, Nsight captures all commands issued to the OpenGL server. Not just those issued through your application. If you have any FPS or recording software enabled, these tend to use deprecated methods drawing to the framebuffer. In my case it was Riva Tuner which displays the FPS on...
I figured out by myself, I forgot to add libraries of sutils of OptiX. Here is what I added to my LIBS: LIBS += -lcuda -lcudart -loptix -loptixu -lsutil -L/usr/local/cuda-6.5/lib64 -L/home/Remb/NVIDIA-OptiX-SDK-3.7.0-linux64/lib64 ...
There are quite a few issues in the provided code. The device memory allocation using cudaMallocPitch is totally broken. You are trying to allocate device memory to a 2D array which is already allocated on the host. Trying to do so will result in memory corruption and undefined behavior. A...
Your command to read the data back from the device is only reading 8 bytes, which is two floats: err = queue.enqueueReadBuffer( src_d, CL_TRUE, 0, 8, // <- This is the number of bytes, not the number of elements! // This is float * src_h = new float[8]; src_h); To...
These questions aren't well-suited on SO, but I'm posting a few resources you might start with anyway The "Learning CUDA" section of the NVIDIA website is the best spot on resources and tutorials to get you up to speed: https://developer.nvidia.com/how-to-cuda-c-cpp CUDA by Example(beginner) and Programming Massively Parallel Processors (intermediate) are...