gpu

问题 I know that sometimes browsers will GPU accelerate a CSS transform. But when does that happen, and is there a way to force GPU acceleration for a smooth animation? this article 回答1: Most modern browsers support GPU acceleration, but they only use it when they think a DOM element will benefit from it. The strongest indication is that a 3D transformation is being applied. So use the 3D-equivalent transform. For example, instead of transform: translateX(50px) , use transform: translate3d(50px, 0

问题 I am trying to offload code the GPU using OpenMP 4+ directives. I am using ubuntu 16.04 with GCC 7.2 and for general cases it is working fine. My problem comes when I am trying to offload a code that has a call to the sqrtf function that is defined in "math.h". The troubeling code is this: #pragma omp target teams distribute \ map(to:posx[:n],posy[:n],posz[:n]) \ map(from:frcx[:n],frcy[:n],frcz[:n]) for (int i = 0; i < n; i++) { frcx[i] = 0.0f; frcy[i] = 0.0f; frcz[i] = 0.0f; for (int j = 0;

问题 I am using C++, GTX1070 I am allocating a cuda array as described: //variables: Vdepth = 200, Vheight = 100, Vwidth = 100, device = 0 VolumeId = 0 cudaExtent volumeSize = make_cudaExtent(Vdepth, Vheight, Vwidth); cudaArray *d_volumeArray = NULL; cudaChannelFormatDesc channelDesc = cudaCreateChannelDesc<texture_type>(); VERIFY_CALL( cudaMalloc3DArray(&d_volumeArray, &channelDesc, volumeSize) ); cu_VolArray[device][VolumeId] = d_volumeArray; Then I try to free it like this: VERIFY_CALL

问题 I created a DataGenerator with Sequence class. import tensorflow.keras as keras from skimage.io import imread from skimage.transform import resize import numpy as np import math from tensorflow.keras.utils import Sequence Here, `x_set` is list of path to the images and `y_set` are the associated classes. class DataGenerator(Sequence): def __init__(self, x_set, y_set, batch_size): self.x, self.y = x_set, y_set self.batch_size = batch_size def __len__(self): return math.ceil(len(self.x) / self

问题 I created a DataGenerator with Sequence class. import tensorflow.keras as keras from skimage.io import imread from skimage.transform import resize import numpy as np import math from tensorflow.keras.utils import Sequence Here, `x_set` is list of path to the images and `y_set` are the associated classes. class DataGenerator(Sequence): def __init__(self, x_set, y_set, batch_size): self.x, self.y = x_set, y_set self.batch_size = batch_size def __len__(self): return math.ceil(len(self.x) / self

问题 When I'm trying to run Yolo detection examples, I got that error: 2020-02-02 21:39:00.821721: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_101.dll WARNING:tensorflow:From C:\Users\Dominux\AppData\Local\Programs\Python\Python37\lib\site-packages\tensorflow_core\python\ops\resource_variable_ops.py:1635: calling BaseResourceVariable.__init__ (from tensorflow.python.ops.resource_variable_ops) with constraint is deprecated and will be

问题 I am building a program that use ffmpeg to stream webcam content over internet. I would like to know if it is possible to use the GPU for the streaming part on the raspberry pi model 3. If yes, how could I implement this on ffmpeg? 回答1: You'll need some additional configure options: --enable-mmal – Enable Broadcom Multi-Media Abstraction Layer (Raspberry Pi) via MMAL. For hardware decoding of H.264, VC-1, MPEG-2, MPEG-4. As a dependency you'll need the linux-raspberrypi-headers (Arch Linux)

问题 what I did is follow the instruction on the official github site !git clone https://github.com/NVIDIA/apex !cd apex !pip install -v --no-cache-dir ./ it gives me the error: ERROR: Directory './' is not installable. Neither 'setup.py' nor 'pyproject.toml' found. Exception information: Traceback (most recent call last): File "/usr/local/lib/python3.6/dist-packages/pip/_internal/cli/base_command.py", line 178, in main status = self.run(options, args) File "/usr/local/lib/python3.6/dist-packages

问题 Is there a standard way of getting GPU percent usage in Cocoa/Objective-C on OS X (10.6 and 10.7)? 回答1: Enjoy it, GPU and RAM usage , doesn't work on the discreet GPU btw because it does not expose the performances monitoring dictionary. My MBP has an NVIDIA gpu, should work on ATI too but I'm not sure 100% #include <CoreFoundation/CoreFoundation.h> #include <Cocoa/Cocoa.h> #include <IOKit/IOKitLib.h> int main(int argc, const char * argv[]) { while (1) { // Get dictionary of all the PCI

问题 I am trying to train the following CNN as follows, but I keep getting the same error regarding .cuda() and I am not sure how to fix it. Here is a chunk of my code so far. import matplotlib.pyplot as plt import numpy as np import torch from torch import nn from torch import optim import torch.nn.functional as F import torchvision from torchvision import datasets, transforms, models from torch.utils.data.sampler import SubsetRandomSampler data_dir = "/home/ubuntu/ML2/ExamII/train2/" valid_size