Artificial Intelligence Stack Exchange
Artificial Intelligence Stack Exchange

Questions tagged [gpu]

Graphics processing units or GPUs are specialized hardware for the manipulation of images and calculation of local image properties.

The mathematical basis of neural networks and image manipulation are similar, parallel tasks involving matrices, leading GPUs to become increasingly used for machine learning tasks. As of 2016, GPUs are popular for AI work, and they continue to evolve in a direction to facilitate deep learning, both for training[24] and inference in devices such as self-driving cars. GPU developers are developing additional connective capability for the kind of dataflow workloads AI benefits from. As GPUs have been increasingly applied to AI acceleration, GPU manufacturers have incorporated neural network specific hardware to further accelerate these tasks. Tensor cores are intended to speed up the training of neural networks. Wikipedia Reference

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Is a GPU always faster than a CPU for training neural networks?

Currently, I am working on a few projects that use feedforward neural networks for regression and classification of simple tabular data. I have noticed that training a neural network using TensorFlow-GPU is often slower than training the same…
GKozinski
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Can LSTM neural networks be sped up by a GPU?

I am training LSTM neural networks with Keras on a small mobile GPU. The speed on the GPU is slower than on the CPU. I found some articles that say that it is hard to train LSTMs (and, in general, RNNs) on GPUs because the training cannot be…
Dieshe
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Effect of batch size and number of GPUs on model accuracy

I have a data set that was split using a fixed random seed and I am going to use 80% of the data for training and the rest for validation. Here are my GPU and batch size configurations use 64 batch size with one GTX 1080Ti use 128 batch size with…
bit_scientist
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How does a transformer leverage the GPU to be trained faster than RNNs?

How does a transformer leverage the GPU to be trained faster than RNNs? I understand the parameter space of the transformer might be significantly larger than that of the RNN. But why does the transformer structure can leverage multiple GPUs, and…
YoYO Man
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Good model and training algorithm to store texture data for fast gpu inference

Now, the following may sound silly, but I want to do it for my better understanding of performance and implementation of GPU inference for a set of deep learning problems. What I want to do is to replace a surface texture for a 3d model by a NN that…
matthias_buehlmann
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Training network with 4 GPUs performance is not exactly 4 times over one GPU why?

Training neural network with 4 GPUs using pyTorch, performance is not even 2 times (btw 1 & 2 times) compare to using one GPU. From Nvidia-smi we see GPU usage is for few milliseconds and next 5-10 seconds looks like data is off-loaded and loaded…
Troy
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How can I reduce the GPU memory usage with large images?

I am trying to train a CNN-LSTM model. The size of my images is 640x640. I have a GTX 1080 ti 11GB. I am using Keras with the TensorFlow backend. Here is the model. img_input_1 = Input(shape=(1, n_width, n_height, n_channels)) conv_1 =…
Thiedent
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How does one deal with images that are too large to fit in the GPU memory for doing ML image analysis?

How does one deal with images that are too large to fit in the GPU memory for doing ML image analysis? I am interested in detecting small structures on images which are themselves many GB in size. Beyond simple downsampling and maybe doing…
Luca
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How to train neural networks with multiprocessing?

I am trying to figure out how multiprocessing works in neural networks. In the example I've seen, the database is split into $x$ parts (depending on how many workers you have) and each worker is responsible to train the network using a different…
Yedidya kfir
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How do GPUs faciliate the training of a Deep Learning Architecture?

I would love to know in detail, how exactly GPUs help, in technical terms, in training the deep learning models. To my understanding, GPUs help in performing independent tasks simultaneously to improve the speed. For example, in calculation of the…
Anubhav Sachan
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In addition to matrix algebra, can GPU's also handle the various Kernel functions for Neural Networks?

I've read a number of articles on how GPUs can speed up matrix algebra calculations, but I'm wondering how calculations are performed when one uses various kernel functions in a neural network. If I use Sigmoid functions in my neural network, does…
Greg Thatcher
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Inference process and flow, and role of GPU, CPU, and RAM

This is a noob question. I load a HuggingFace transformer model into GPU and create a HuggingFace pipeline using that model. Then I run inference on the model using the pipeline. I would be glad to read in some depth about the actual process flow of…
ahron
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How are gaming GPUs different from GPUs for ML?

I have a seemingly innocent question. I was looking to buy a computer for deep learning development using large language models. When I searched online on consumer e-commerce websites, I could not find any computer with NVIDIA P100, V100 for sale.…
morpheus
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For an LLM model, how can I estimate its memory requirements based on storage usage?

It is easy to see the amount of disk space consumed by an LLM model (downloaded from huggingface, for instance). Just go in the relevant directory and check the file sizes. How can I estimate the amount of GPU RAM required to run the model? For…
ahron
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Why training the same model on the same data can be slower on better card?

Can someone explain why training CNN model (in my case DenseNet201) on the same data, and the same data processing pipeline can be slower on better GPU (RTX3090) than worse one (RTX3060), with the same other parameters (exactly same PC just with new…
GKozinski
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