Re: [GSoC 2019] Possible Mentorship for a project on implementing uBLAS tensor product and decomposition algorithms

Cem Bassoy via ublas <[email protected]> Tue, 26 Mar 2019 08:43:33 +0100
Newsgroups gmane.comp.lib.boost.ublas
Message-ID <CADrR+FsY1a+bmJ5kiAJQAYrUbq5v8pV0Xdae=COzSp7Qk+t_Fw@mail.gmail.com>
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Hello Thomas,

thanks for considering Boost/uBLAS.

The current tensor implementation does not provide any alternative tensor
representation such as the tucker, cp or the tensor-train format. We want
to definitely support such representations and according operations.
However, this year the focus is more on the dense structures. On the long
run it would be good for Boost/uBlas to support the above mentioned types
and operations.


Your matrix expressions do not include expression templates. Are you going
to add this feature?
If you have resources and time left, please write your proposal (google
documents) and share the link of your proposal directly with me.

Best,
Cem




Am Di., 26. M=C3=A4rz 2019 um 04:38 Uhr schrieb Thomas Yang via ublas <
[email protected]>:

> Hello,
>
> My name is Thomas Yang, a 4th year BS/MS student studying Computer Scienc=
e
> and Electrical Engineering at Northwestern University. I have used boost =
in
> the past for a summer internship, and I would love to learn more about th=
e
> possibility of completing a GSoC project with the organization, and about
> contributing to boost numeric libraries in general.
>
> I noticed that currently in the tensor library, there is only support for
> tensor arithmetic involving standard tensor n-mode multiplication. Other
> products which are highly useful in working with large tensors are missin=
g,
> including the various products mentioned in the project page (e.g.
> Kronecker product) have not yet been implemented. Furthermore, there is n=
o
> representation for a tensor decomposition for default dense tensors. I wa=
s
> hoping to pursue a project where I would implement these in the
> algorithms.hpp header alongside the other products, as well as possibly
> creating a new tensor decomposition class. This would enable high-order
> tensors to be represented as products of lesser order tensors, thus
> enabling users to work with large datasets with uBLAS tensors.
>
> Here is my programming competency test:
> https://github.com/thomasyang1207/BoostProgrammingAssessment. In my
> repository, I have also included other open source contributions, as well
> as personal projects of my own.
>
> I understand that this email is quite late, and that mentorship
> opportunities are quite low at this point, but I would love any feedback =
on
> my proposal, and if possible, some guidance on possibly doing a GSoC
> project next year. If mentorship is possible this year, I can quickly
> complete a proposal within this week.
>
> Thank you very much,
>
> Thomas Yang
> _______________________________________________
> ublas mailing list
> [email protected]
> https://lists.boost.org/mailman/listinfo.cgi/ublas
> Sent to: [email protected]
>

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<div dir=3D"ltr"><div>Hello Thomas,</div><div><br></div><div>thanks for con=
sidering Boost/uBLAS. <br></div><div><br></div><div>The current tensor impl=
ementation does not provide any alternative tensor representation such as t=
he tucker, cp or the tensor-train format. We want to definitely support suc=
h representations and according operations. However, this year the focus is=
 more on the dense structures. On the long run it would be good for Boost/u=
Blas to support the above mentioned types and operations.</div><div><br></d=
iv><div><br></div><div>Your matrix expressions do not include expression te=
mplates. Are you going to add this feature?</div><div>If you have resources=
 and time left, please write your proposal (google documents) and share the=
 link of your proposal directly with me.</div><div><br></div><div>Best,</di=
v><div>Cem<br></div><div><br></div><div><br></div><div><br></div></div><br>=
<div class=3D"gmail_quote"><div dir=3D"ltr" class=3D"gmail_attr">Am Di., 26=
. M=C3=A4rz 2019 um 04:38=C2=A0Uhr schrieb Thomas Yang via ublas &lt;<a hre=
f=3D"mailto:[email protected]" target=3D"_blank">[email protected]<=
/a>&gt;:<br></div><blockquote class=3D"gmail_quote" style=3D"margin:0px 0px=
 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex"><div di=
r=3D"ltr">Hello,=C2=A0<div><br></div><div>My name is Thomas Yang, a 4th yea=
r BS/MS student studying Computer Science and Electrical Engineering at Nor=
thwestern University. I have used boost in the past for a summer internship=
, and I would love to learn more about the possibility of completing a GSoC=
 project with the organization, and about contributing to boost numeric lib=
raries in general.=C2=A0</div><div><br></div><div>I noticed that currently =
in the tensor library, there is only support for tensor arithmetic involvin=
g standard tensor n-mode multiplication. Other products which are highly us=
eful in working with large tensors are missing, including the various produ=
cts mentioned in the project page (e.g. Kronecker product) have not yet bee=
n implemented. Furthermore, there is no representation for a tensor decompo=
sition for default dense tensors. I was hoping to pursue a project where I =
would implement these in the algorithms.hpp header alongside the other prod=
ucts, as well as possibly creating a new tensor decomposition class. This w=
ould enable high-order tensors to be represented as products of lesser orde=
r tensors, thus enabling users to work with large datasets with uBLAS tenso=
rs.</div><div><br></div><div>Here is my programming competency test:=C2=A0<=
a href=3D"https://github.com/thomasyang1207/BoostProgrammingAssessment" tar=
get=3D"_blank">https://github.com/thomasyang1207/BoostProgrammingAssessment=
</a>. In my repository, I have also included other open source contribution=
s, as well as personal projects of my own.=C2=A0</div><div><br></div><div>I=
 understand that this email is quite late, and that mentorship opportunitie=
s are quite low at this point, but I would love any feedback on my proposal=
, and if possible, some guidance on possibly doing a GSoC project next year=
. If mentorship is possible this year, I can quickly complete a proposal wi=
thin this week.=C2=A0</div><div><br></div><div>Thank you very much,=C2=A0</=
div><div><br></div><div>Thomas Yang</div></div>
_______________________________________________<br>
ublas mailing list<br>
<a href=3D"mailto:[email protected]" target=3D"_blank">[email protected]=
t.org</a><br>
<a href=3D"https://lists.boost.org/mailman/listinfo.cgi/ublas" rel=3D"noref=
errer" target=3D"_blank">https://lists.boost.org/mailman/listinfo.cgi/ublas=
</a><br>
Sent to: <a href=3D"mailto:[email protected]" target=3D"_blank">cem.bass=
[email protected]</a><br>
</blockquote></div>

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