gpu

问题 I am trying install Cuda on WSL 2. I am following instructions such as this. After executing every step, I try to check if gpu is available in the Linux environment by executing docker run --gpus all nvcr.io/nvidia/k8s/cuda-sample:nbody nbody -gpu -benchmark (as suggested by the aforementioned instructions). But I get the following error: docker: Error response from daemon: could not select device driver "" with capabilities: [[gpu]]. ERRO[0000] error waiting for container: context canceled .

问题 I am using PyTorch. I am going to use the already trained model on multiple GPUs with CPU. how to do this task? I tried on Anaconda 3 and pytorch with cpu only i dont have gpu model = models.get_pose_net(config, is_train=False) gpus = [int(i) for i in config.GPUS.split(',')] model = torch.nn.DataParallel(model, device_ids=gpus).cuda() print('Created model...') print(model) checkpoint = torch.load(config.MODEL.RESUME) model.load_state_dict(checkpoint) model.eval() print('Loaded pretrained

问题 I am using PyTorch. I am going to use the already trained model on multiple GPUs with CPU. how to do this task? I tried on Anaconda 3 and pytorch with cpu only i dont have gpu model = models.get_pose_net(config, is_train=False) gpus = [int(i) for i in config.GPUS.split(',')] model = torch.nn.DataParallel(model, device_ids=gpus).cuda() print('Created model...') print(model) checkpoint = torch.load(config.MODEL.RESUME) model.load_state_dict(checkpoint) model.eval() print('Loaded pretrained

问题 The NVIDIA-SMI is throwing this error: NVIDIA-SMI has failed because it couldn't communicate with the NVIDIA driver. Make sure that the latest NVIDIA driver is installed and running I purged NVIDIA and installed it again following steps mentioned here. My device specs are as follows: Server with a Tesla M40 Running on Ubuntu 16.04 Kernel version Linux 4.4.0-116-generic x86_64 Driver: nvidia-384 Can someone please help in solving the error? 回答1: Try Download the driver from here sudo apt-get

问题 I am confused by __shfl_down and __shfl_down_sync , they give different results. __global__ void shufledown1(double* a, double *b,double *c, int N) { double temp = 2.0; __syncthreads(); for (int offset = 32/2; offset > 0; offset /= 2){ temp+=__shfl_down(temp, offset,32); } printf("%d %f %d \n",threadIdx.x ,temp,blockDim.x * gridDim.x); } __global__ void shufledown2(double* a, double *b,double *c, int N) { double temp = 2.0; __syncthreads(); for (int offset = 32/2; offset > 0; offset /= 2){

问题 i am facing issue with my inception model during the performance testing with Apache JMeter. Error: OOM when allocating tensor with shape[800,1280,3] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc [[Node: Cast = CastDstT=DT_FLOAT, SrcT=DT_UINT8, _device="/job:localhost/replica:0/task:0/device:GPU:0"]] Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.

问题 I am learning GPU Computing with R (http://www.r-tutor.com/gpu-computing). I am trying to install packages 'RPUD' or 'gputools' but failed. The RPUD version I found works only for CUDA toolkit 8.0/7.5. But I could only download CUDA 9.1. The 'gputools' could not be installed either.Any ideas/suggestions will be highly appreciated. 来源： https://stackoverflow.com/questions/48528490/r-gpu-computing-rpud-installation-failed

问题 I am learning GPU Computing with R (http://www.r-tutor.com/gpu-computing). I am trying to install packages 'RPUD' or 'gputools' but failed. The RPUD version I found works only for CUDA toolkit 8.0/7.5. But I could only download CUDA 9.1. The 'gputools' could not be installed either.Any ideas/suggestions will be highly appreciated. 来源： https://stackoverflow.com/questions/48528490/r-gpu-computing-rpud-installation-failed

问题 I am learning GPU Computing with R (http://www.r-tutor.com/gpu-computing). I am trying to install packages 'RPUD' or 'gputools' but failed. The RPUD version I found works only for CUDA toolkit 8.0/7.5. But I could only download CUDA 9.1. The 'gputools' could not be installed either.Any ideas/suggestions will be highly appreciated. 来源： https://stackoverflow.com/questions/48528490/r-gpu-computing-rpud-installation-failed

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