So I am on windows 10 and am using multiple GPUs now in order to run the training of some machine learning model and this model is about GAN algorithm you can check the full code over here : Here, ...

I have a server (Ubuntu 16.04) with 4 GPUs. My team shares this, and our current approach is to containerize all of our work with Docker, and to restrict containers to GPUs using something like $ N...

In Mac OS X, every display gets a unique CGDirectDisplayID number assigned to it. You can use CGGetActiveDisplayList() or [NSScreen screens] to access them, among others. Per Apple's docs: A dis...

I have access to six 24GB GPUs. When I try to load some HuggingFace models, for example the following from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pr...

When I launch my main script on the cluster with ddp mode (2 GPU's), Pytorch Lightning duplicates whatever is executed in the main script, e.g. prints or other logic. I need some extended training ...

Let's begin with the premise that I'm newly approaching to TensorFlow and deep learning in general. I have TF 2.0 Keras-style model trained using tf.Model.train(), two available GPUs and I'm looki...

My server has two GPUs, How can I use two GPUs for training at the same time to maximize their computing power? Is my code below correct? Does it allow my model to be properly trained? class MyMode...

I want my model to run on multiple GPU-sharing parameters but with different batches of data. Can I do something like that with model.fit()? Is there any other alternative?

I have multiple GPU devices and want to run a Pytorch on them. I have already tried MULTI-GPU EXAMPLES and DATA PARALLELISM in my code by device = torch.device("cuda:0,1,2") model = torch...

I was to set up DDP (distributed data parallel) on a DGX A100 but it doesn't work. Whenever I try to run it simply hangs. My code is super simple just spawning 4 processes for 4 gpus (for the sake ...

I want to train a model on several GPUs using tensorflow 2.0. In the tensorflow tutorial for distributed training (https://www.tensorflow.org/guide/distributed_training), the tf.data datagenerator ...

I'm working on a business project that is done in Java, and it needs huge computation power to compute business markets. Simple math, but with huge amount of data. We ordered some CUDA GPUs to try...

I'd like to know the possible ways to implement batch normalization layers with synchronizing batch statistics when training with multi-GPU. Caffe Maybe there are some variants of caffe that coul...

I have a server with multiple GPUs and want to make full use of them during model inference inside a java app. By default tensorflow seizes all available GPUs, but uses only the first one. I can ...

Would using multi-GPUs in Vulkan be something like making many command queues then dividing command buffers between them? There are 2 problems: In OpenGL, we use GLEW to get functions. With more...

I have created 3 virtual GPU's (have 1 GPU) and try to speedup vectorization on images. However, using provided below code with manual placement from off docs (here) I got strange results: training...

I have a standard tensorflow Estimator with some model and want to run it on multiple GPUs instead of just one. How can this be done using data parallelism? I searched the Tensorflow Docs but did...

I am trying to run a Subclassed Keras Model on multiple GPUs. The code is running as expected, however, the following "warning" crops up during the execution of the code: "Efficient allreduce is ...

In order to leverage the GPUs on a system, I'd like to be able to draw a block diagram and understand the connections represented by "nvidia-smi topo -m" output. Here is an example output: Can...

I have a 4 GPU machine on which I run Tensorflow (GPU) with Keras. Some of my classification problems take several hours to complete. nvidia-smi returns Volatile GPU-Util which never exceeds 25% ...

I have a CUDA stream which someone handed to me - a cudaStream_t value. The CUDA Runtime API does not seem to indicate how I can obtain the index of the device with which this stream is associated....

I'm having a problem with ffmpeg video encoding using GPU (CUDA). I have 2x nVidia GTX 1050 Ti The problem comes when i try to do multiple parallel encodings. More than 2 processes and ffmpeg die...

When I try the following code sample for using Tensorflow with Ray, Tensorflow fails to detect the GPU's on my machine when invoked by the "remote" worker but it does find the GPU's when invoked "l...

Following the upgrade to Keras 2.0.9, I have been using the multi_gpu_model utility but I can't save my models or best weights using model.save('path') The error I get is TypeError: can’t pi...

I want to use two python source codes, the first one is developed with tensorflow and the other is developed using pythorch. I want to run each of these codes in a thread with a separate GPU. the i...