Subject: [ublas] [GSoC 2019] Possible Mentorship for a project on implementing uBLAS tensor product and decomposition algorithms
From: Thomas Yang (ThomasYang_at_[hidden])
Date: 2019-03-26 03:37:26
My name is Thomas Yang, a 4th year BS/MS student studying Computer Science
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 the
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 missing,
including the various products mentioned in the project page (e.g.
Kronecker product) have not yet been implemented. Furthermore, there is no
representation for a tensor decomposition for default dense tensors. I was
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,