Questions tagged [gpu]

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

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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 ...
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External GPU for Mac

I'd like to buy an eGPU for my MaxBook Pro to use for simple deep learning tasks. My setup is: ...
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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 ...
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Cluster 2 AWS instances for deep learning model training

I am working on a CNN model for image classification. Currently a single AWS instance (p2xlarge) used for model training. I would like to have one more AWS instance and distribute the load across ...
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How can traditional edge detection algorithms be implemented on a GPU?

How can edge detection algorithms, which are not based on deep learning, such as the canny edge detector, be implemented on a GPU? For example, how are non-edge pixels removed from an image once it ...
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Why would my neural network run faster on my laptop than on my university's supercomputer?

I am trying to get my neural network running on my university's supercomputer in order to decrease its runtime (not for training, for testing - feedforward runs only). However, the Matlab function I ...
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What are the properties of a model that is well suited for for high performance real-time inference

What are general best practices or considerations in designing a model that is optimized for real-time inference?
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35 views

Any good resources for learning programming GPU level operations?

I want to be able to improve my lower level device specific programming abilities to assist in future endeavors. Examples would be learning to write custom tensorflow operations in C++ optimized to ...
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What Deep Learning Applications Might Require Super-Computers or “SuperPODs”

With the release of NVIDIA's DGX SuperPOD of A100 GPUs, supercomputers will/are becoming more and more common-place. What potential deep learning tasks/applications might become more accessible with ...
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GPU-training on Google Cloud Platform slower than CPU-training

I recently trained Kaggles "Advanced Housing Prices"-Competition using Catboost. For training i used a compute-instance on Google Cloud Platform (GCP) (CPU: Xeon Quad-Core, RAM: 15GB, GPU: ...