Hi,
As described in "Convolution Demo" section of
http://cs231n.github.io/convolutionalnetworks, convolution layer construct
output maps by convoluting trainable kernel filter. Animation will be very
helpful. The initial weights of kernel filter are random like MLP. And, this
convolution computation between a feature map and a kernel can be simplified
to a vector/matrix multiplication. The batch of multiple images is matmat
multiplication. This is normal way in other projects like Torch.
Instead we doing like that, we'll do elementwise multiplication within each
neuron object. User define the neuron function then, framework process the
neurons in parallel. To understand this flow, Pregel system will be helpful.
I roughly guess our system can be useful when if a server receive image to
recognize. Because, GPUoriented systems are optimized to process batch
operations.

Best Regards, Edward J. Yoon
Original Message
From: Zachary Jaffee [mailto:zij@case.edu]
Sent: Tuesday, January 19, 2016 1:34 PM
To: Unknown
Subject: Re: Implement convolutional neuron function
So I've tried out a few things, but I can't seem to see what you mean when
you say not to use a dot product. If you have any insights as to what this
function would look like, I'd be interested in seeing what you are thinking
of.
On Wed, Dec 16, 2015 at 6:29 PM, Edward J. Yoon <edward.yoon@samsung.com>
wrote:
> Thanks.
>
> You can discuss this issue with me and shubham.
>
> I personally we need to approach neuroncentric instead of dot product of
> matrix or tensor, so that we can parallelize computations at neuron level.
> In
> here, the tricky issue is handling the topology of neurons within
> rectangular
> grid (graph structure). But, you can ignore this at the moment.
>
> If you have any questions/opinions, let's discuss together.
>
> 
> Best Regards, Edward J. Yoon
>
> Original Message
> From: Zachary Jaffee [mailto:zij@case.edu]
> Sent: Thursday, December 17, 2015 12:59 AM
> To: Unknown
> Subject: Re: Implement convolutional neuron function
>
> I'll take care of this.
>
> On Wed, Dec 16, 2015 at 2:26 AM, Edward J. Yoon <edward.yoon@samsung.com>
> wrote:
>
> > Hi forks,
> >
> > Does anyone volunteer for HORN10?
> >
> > To implement convolutional neuron function, you can refer my standard
> > neuron
> > function code here:
> >
> >
> https://github.com/edwardyoon/incubatorhorn/blob/HORN7/src/test/java/org/a
> > pache/horn/trainer/TestNeuron.java
> >
> > And basic equation
> >
> >
> https://jianfengwang.files.wordpress.com/2015/07/forwardandbackwardpropagati
> > onofconvolutionallayer.pdf and animation version can be found at
> > http://cs231n.github.io/convolutionalnetworks/ for forward and backward
> > of
> > convolutional neuron.
> >
> > Thanks!
> >
> > 
> > Best Regards, Edward J. Yoon
> >
> >
> >
> >
>
>
> 
> Zach Jaffee
> B.S. Computer Science
> Case Western Reserve University Class of 2017
> Operations Director  WRUW FM 91.1 Cleveland
> Secretary  Recruitment Chair  Phi Kappa Theta Fraternity
> (917) 8810646
> zjaffee.com
> github.com/ZJaffee
>
>
>

Zach Jaffee
B.S. Computer Science
Case Western Reserve University Class of 2017
Operations Director  WRUW FM 91.1 Cleveland
Secretary  Recruitment Chair  Phi Kappa Theta Fraternity
(917) 8810646
zjaffee.com
github.com/ZJaffee
