[petsc-dev] Fwd: [DL-interest] The missing piece in deep learning?

[Mills, Richard Tran]

Interesting. I expect that Google will be convinced to rewrite Tensorflow entirely in Fortran now.

Seriously, I'm not sure what the motivation for this particular project is. Is it that people are tired of reading in their data using some nice Python tool and would rather be using old school fixed-format data routines in Fortran? =)

--Richard

On 5/16/19 11:16 AM, Smith, Barry F. via petsc-dev wrote:
 Looks like that job is now done.



Begin forwarded message:

From: "Foster, Ian T. via DL-interest" <dl-interest at lists.cels.anl.gov<mailto:dl-interest at lists.cels.anl.gov>>
Subject: [DL-interest] The missing piece in deep learning?
Date: May 16, 2019 at 11:52:29 AM CDT
To: "DL-interest at lists.cels.anl.gov<mailto:DL-interest at lists.cels.anl.gov>" <DL-interest at lists.cels.anl.gov<mailto:DL-interest at lists.cels.anl.gov>>
Reply-To: "Foster, Ian T." <foster at anl.gov<mailto:foster at anl.gov>>

Have you ever lamented the lack of good DNN tools in Fortran? If so, you need lament no longer.

https://arxiv.org/pdf/1902.06714


A parallel Fortran framework for neural networks and deep learning

This paper describes neural-fortran, a parallel Fortran frame- work for neural networks and deep learning. It features a simple interface to construct feed-forward neural networks of arbitrary structure and size, several activation functions, and stochastic gradient descent as the default optimization algorithm. neural-fortran also leverages the Fortran 2018 standard collective subroutines to achieve data-based paral- lelism on shared- or distributed-memory machines.

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