VEVekz·May 9, 2017
Here is another WebGL example that does GPU accelerated handwritten digit recognition. https://github.com/Erkaman/regl-cnn
In How to Create a Neural Network in JavaScript [video]Erkaman
regl-cnn
JavaScript2016–2017
Erkaman / regl-cnn
regl-cnn
Digit recognition with Convolutional Neural Networks in WebGL
2Distinct people
3Mentions
0Explicit recommenders
512GitHub stars
What to know before exploring
What it is
Digit recognition with Convolutional Neural Networks in WebGL
GitHub
Where it is used
No documented product use has been verified yet.
What people are saying
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Also in these discussions
- regl-project/regl · linked in 2 of the same discussions
Mentioned in the same Hacker News threads. That is not proof they are substitutes.
This week on Hacker News
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Mentions over time
HN mentions by month3 dated mentions
Observed mentions: 2016-08-17 06:13:59 UTC to 2017-05-09 17:02:19 UTC.
Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.
View mention counts and date ranges
| Period | Start (UTC) | End (exclusive, UTC) | Mentions | Submissions | Comments |
|---|---|---|---|---|---|
| Aug 2016 | 2016-08-01 00:00:00 UTC | 2016-09-01 00:00:00 UTC | 2 | 0 | 2 |
| Sep 2016 | 2016-09-01 00:00:00 UTC | 2016-10-01 00:00:00 UTC | 0 | 0 | 0 |
| Oct 2016 | 2016-10-01 00:00:00 UTC | 2016-11-01 00:00:00 UTC | 0 | 0 | 0 |
| Nov 2016 | 2016-11-01 00:00:00 UTC | 2016-12-01 00:00:00 UTC | 0 | 0 | 0 |
| Dec 2016 | 2016-12-01 00:00:00 UTC | 2017-01-01 00:00:00 UTC | 0 | 0 | 0 |
| Jan 2017 | 2017-01-01 00:00:00 UTC | 2017-02-01 00:00:00 UTC | 0 | 0 | 0 |
| Feb 2017 | 2017-02-01 00:00:00 UTC | 2017-03-01 00:00:00 UTC | 0 | 0 | 0 |
| Mar 2017 | 2017-03-01 00:00:00 UTC | 2017-04-01 00:00:00 UTC | 0 | 0 | 0 |
| Apr 2017 | 2017-04-01 00:00:00 UTC | 2017-05-01 00:00:00 UTC | 0 | 0 | 0 |
| May 2017 | 2017-05-01 00:00:00 UTC | 2017-06-01 00:00:00 UTC | 1 | 0 | 1 |
What Hacker News says
3 sourcesThe demo uses WebGL, and if you can't get the demo to work, you can
here(https://github.com/Erkaman/regl-cnn) find a recorded gif that shows what it is supposed to look like.
This demo does handwritten digit recognition by evaluating a
Convolutional Neural Network on the GPU with WebGL. The network was
trained in TensorFlow by this script here(https://github.com/Erkaman/regl-cnn/blob/gh-pages/scripts/cr...), and the network was then
reimplemented on the GPU by hand with WebGL. The main purpose of the
demo was to demonstate how our WebGL framework
regl(https://github.com/mikolalysenko/regl) can be used to greatly
simplify GPGPU programming in WebGL. The secondary purpose was to test
whether evaluating Deep Learning networks in WebGL is doable. To our
knowledge(but we may be wrong!), our implementation is the first
implementation ever to a
Read the rest
ttempt GPU accelerating neural networks with
WebGL And we hope that this implementation will provide a foundation
for people who, like us, wish to experiment with Deep Learning and
WebGL The GPU implementation can be found here(https://github.com/Erkaman/regl-cnn/blob/gh-pages/src/gpu.js)
Note that this network will probably be slower than the corresponding
network implemented on the CPU. This is because of the overhead
associated with transferring data to and from the GPU. But in the
future we will attempt implementing more complex networks in the browser,
such as Neural Style(https://arxiv.org/pdf/1508.06576v2.pdf), and then we think that we will see a
significant speedup compared to the CPU.
Lastly, if anyone has any questions, I will be glad to answer them
here.
The demo uses WebGL, and if you can't get the demo to work, you can
here(https://github.com/Erkaman/regl-cnn) find a recorded gif that shows what it is supposed to look like.
This demo does handwritten digit recognition by evaluating a
Convolutional Neural Network on the GPU with WebGL. The network was
trained in TensorFlow by this script here(https://github.com/Erkaman/regl-cnn/blob/gh-pages/scripts/cr...), and the network was then
reimplemented on the GPU by hand with WebGL. The main purpose of the
demo was to demonstate how our WebGL framework
regl(https://github.com/mikolalysenko/regl) can be used to greatly
simplify GPGPU programming in WebGL. The secondary purpose was to test
whether evaluating Deep Learning networks in WebGL is doable. To our
knowledge(but we may be wrong!), our implementation is the first
implementation ever to a
Read the rest
ttempt GPU accelerating neural networks with
WebGL And we hope that this implementation will provide a foundation
for people who, like us, wish to experiment with Deep Learning and
WebGL The GPU implementation can be found here(https://github.com/Erkaman/regl-cnn/blob/gh-pages/src/gpu.js)
Note that this network will probably be slower than the corresponding
network implemented on the CPU. This is because of the overhead
associated with transferring data to and from the GPU. But in the
future we will attempt implementing more complex networks in the browser,
such as Neural Style(https://arxiv.org/pdf/1508.06576v2.pdf), and then we think that we will see a
significant speedup compared to the CPU.
Lastly, if anyone has any questions, I will be glad to answer them
here.