Pinning data to GPU in Tensorflow and PyTorch

Posted on mar. 02 octobre 2018 in Tutorial by Laura Domine
Tagged with memory, tensorflow, pytorch

Sometimes you might want to keep ('pin') some data on GPU. We demonstrate how to do it in Tensorflow and PyTorch.


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Writing your own CUDA kernel (Part 1)

Posted on mar. 02 octobre 2018 in Tutorial by Laura Domine
Tagged with cuda, tensorflow, pytorch

First part of a tutorial serie to write your own CUDA kernel and use it in Tensorflow or PyTorch.


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Writing your own CUDA kernel (Part 2)

Posted on mar. 02 octobre 2018 in Tutorial by Laura Domine
Tagged with cuda, tensorflow, pytorch

Second part of a tutorial serie to write your own CUDA kernel and use it in Tensorflow or PyTorch.


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Profiling Tensorflow

Posted on mar. 25 septembre 2018 in Tutorial by Corey Adams
Tagged with Tensorflow, profiling, memory, comparisons

A walkthrough of many of the current techniques for profiling time and memory usage for tensorflow.


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Singularity container

Posted on lun. 24 septembre 2018 in container by Kazuhiro Terao
Tagged with singularity, container, software

Long due blog post about our singularity container use!


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News @ 2018-09-07

Posted on ven. 07 septembre 2018 in news by Kazuhiro Terao
Tagged with news, paper

News from the last week's meeting publications and talk/job opportunities!


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News @ 2018-08-31 ... paper rush!

Posted on ven. 31 août 2018 in news by Kazuhiro Terao
Tagged with news, paper

News from last 2 weeks, new meeting time, publications and talk/job opportunities!


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Analyzing Network Output - Part 1, Training and Saving

Posted on jeu. 12 avril 2018 in Tutorial by Corey Adams
Tagged with MNIST, training, saving, minibatching, batch norm

I train a very simple and basic mnist classification network with a lot of overkill: I use minibatching, batch normalization, and save the network weights to disk. This tutorial can be done on a CPU. In Part 2, I restore the model, run on the validation set, and analyze the results.


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Analyzing Network Output - Part 2, Restoring and Analyzing

Posted on jeu. 12 avril 2018 in Tutorial by Corey Adams
Tagged with MNIST, retoring, analysis, minibatching, batch norm

See Part 1 first! There, I trained an mnist classifier. Here, I restore the trained network, run the network on the validation script, and do some analysis on the output. This is meant as a template for new users to see "how do I actually use a trained network?" Lots of this information exists elsewhere too, I've just tried to consolidate the basics.


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ThreadProcessor: speed

Posted on mar. 06 mars 2018 in larcv by Kazuhiro Terao
Tagged with larcv, thread processor

Here's a report for a naive data rate profiling of ThreadProcessor, larcv's threaded data reader we often use for network training. Measured on my macbook pro early 2013 model (old!) but reproduced similar numbers on dell xps15 (9560).


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