gpu

问题 I am a newbie in CUDA programming and in the process of re-writing a C code into a parallelized CUDA new code. Is there a way to write output data files directly from the device without bothering copying arrays from device to host? I assume if cuPrintf exists, there must be away to write a cuFprintf? Sorry, if the answer has already been given in a previous topic, I can't seem to find it... Thanks! 回答1: The short answer is, no there is not. cuPrintf and the built-in printf support in Fermi

问题 I am using CUDA/Thrust/CUDPP. As I understand, in Stream compaction, certain items in an array are marked as invalid and then "removed". Now what does "removal" really mean here? Suppose the original array A and has length 6. If 2 elements are invalid (by whatever condition we may provide) then Does the system create a new array of size 4 in GPU-memory to store the valid elements to get the final result? OR does it physically remove the invalid elements from memory and shrink the original

问题 I am trying to run the vector step addition function on CUDA C++ code, but for large float arrays of size 5,000,000 too, it runs slower than my CPU version. Below is the relevant CUDA and cpu code that I am talking about: #define THREADS_PER_BLOCK 1024 typedef float real; __global__ void vectorStepAddKernel2(real*x, real*y, real*z, real alpha, real beta, int size, int xstep, int ystep, int zstep) { int i = blockDim.x * blockIdx.x + threadIdx.x; if (i < size) { x[i*xstep] = alpha* y[i*ystep] +

问题 I am trying to run the vector step addition function on CUDA C++ code, but for large float arrays of size 5,000,000 too, it runs slower than my CPU version. Below is the relevant CUDA and cpu code that I am talking about: #define THREADS_PER_BLOCK 1024 typedef float real; __global__ void vectorStepAddKernel2(real*x, real*y, real*z, real alpha, real beta, int size, int xstep, int ystep, int zstep) { int i = blockDim.x * blockIdx.x + threadIdx.x; if (i < size) { x[i*xstep] = alpha* y[i*ystep] +

问题 I am now programming on Android and I wonder whether we can use GPGPU for Android now? I once heard that Renderscript can potentially execute on GPGPU in the future. But I wonder whether it is possible for us to programming on GPGPU now? And if it is possible for me to program on the Android GPGPU, where can I find some tutorials or sample programs? Thank you for your help and suggestions. Up till now I know that the OpenGL ES library was now accelerated use GPU, but I want to use the GPU for

问题 I am currently learning vulkan, right now I am just taking apart each command and inspecting the structures to try to understand what they mean. Right now I am analyzing QueueFamilies, for which I have the following code: vector<vk::QueueFamilyProperties> queue_families = device.getQueueFamilyProperties(); for(auto &q_family : queue_families) { cout << "Queue number: " + to_string(q_family.queueCount) << endl; cout << "Queue flags: " + to_string(q_family.queueFlags) << endl; } This produces

问题 I'm updating my question with some new benchmarking results (I also reformulated the question to be more specific and I updated the code)... I implemented a kernel for matrix-vector multiplication in CUDA C following the CUDA C Programming Guide using shared memory. Let me first present some benchmarking results which I did on a Jetson TK1 (GPU: Tegra K1, compute capability 3.2) and a comparison with cuBLAS: Here I guess cuBLAS does some magic since it seems that its execution is not affected

问题 This is the sample MNIST code I am running: from tensorflow.examples.tutorials.mnist import input_data mnist = input_data.read_data_sets('MNIST_data', one_hot=True) import tensorflow as tf sess = tf.InteractiveSession() x = tf.placeholder(tf.float32, shape=[None, 784]) y_ = tf.placeholder(tf.float32, shape=[None, 10]) W = tf.Variable(tf.zeros([784,10])) b = tf.Variable(tf.zeros([10])) y = tf.nn.softmax(tf.matmul(x,W) + b) def weight_variable(shape): initial = tf.truncated_normal(shape, stddev

问题 I'm trying to use the new feature of the android avd features "GPU emulation - yes" It's needed to use GLES2.0 on the emulator. However, when I turn that on, the screen of the emulator goes blank. Here is the output when I call it from command line. 回答1: For those having the same problem and having a nvidia card with optimus... Just install ironhide! sudo apt-add-repository ppa:mj-casalogic/ironhide sudo apt-get update sudo apt-get upgrade sudo apt-get install ironhide Then follow the

问题 In cuBLAS, cublasIsamin() gives the argmin for a single-precision array. Here's the full function declaration: cublasStatus_t cublasIsamin(cublasHandle_t handle, int n, const float *x, int incx, int *result) The cuBLAS programmer guide provides this information about the cublasIsamin() parameters: If I use host (CPU) memory for result , then cublasIsamin works properly. Here's an example: void argmin_experiment_hostOutput(){ float h_A[4] = {1, 2, 3, 4}; int N = 4; float* d_A = 0; CHECK_CUDART