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From Jeremy Anderson <jer...@objectadjective.com>
Subject Re: [Discuss] Google Summer of Code (GSoc) 2017
Date Sat, 07 Jan 2017 04:12:35 GMT
+1

I'd love to extend this to design as well. I'll dig into this and come back.

- Jeremy

...........................

Jeremy Anderson

Github: https://github.com/objectadjective
Twitter: https://twitter.com/ObjectAdjective
LinkedIn: http://www.linkedin.com/in/objectadjective

On 6 January 2017 at 12:12, Mike Dusenberry <dusenberrymw@gmail.com> wrote:

> +1  We should definitely submit a few good project proposals, and
> particularly those that aim to improve the ability of the user to work on a
> wide range of ML problems in a simple and easy manner on top of Spark.
> This could include: building out a full ML demo to solve a real,
> large-scale problem that would benefit from a distributed approach; overall
> performance improvements that address a full class, or wider area, of ML
> algorithms, rather than a single, specific script; infrastructure for
> [performance] testing, and identification of wide areas of improvement
> (your example proposal fits here, and is quite nice!); helping with
> building out fully-featured, clean, well-tested DSLs in Python & Scala
> (we've started, but it would be good to continue stressing them -- we could
> even aim to replace DML with the DSLs); etc.  I like the example proposal
> that you've given since it would be beneficial to the entire project,
> rather than a single, isolated area.
>
> - Mike
>
>
> --
>
> Michael W. Dusenberry
> GitHub: github.com/dusenberrymw
> LinkedIn: linkedin.com/in/mikedusenberry
>
> On Fri, Jan 6, 2017 at 11:57 AM, Madison Myers <madisonjmyers@gmail.com>
> wrote:
>
> > +1 I think it's a great idea, Felix
> >
> > On Fri, Jan 6, 2017 at 11:54 AM, <fschueler@posteo.de> wrote:
> >
> > > Hi all,
> > >
> > > as it just came up on the ML, I want to bring this up again for general
> > > discussion. I think we should try to get at least one or two students
> for
> > > this year's GSOC. If you have never heard of GSOC, look here:
> > > http://write.flossmanuals.net/gsoc-mentoring/what-is-gsoc/ and here:
> > > https://developers.google.com/open-source/gsoc/
> > >
> > > Applications for organizations open on January 19th and it is a great
> way
> > > of introducing new people to the SystemML development and get more
> > > contributors.
> > > To apply, we need to propose projects for a 4-month period in which a
> > > student works on them full time (May - August). Each proposed project
> > needs
> > > one community member to mentor it - in the end Google decides how many
> > > students each project gets, depending of the quality of the proposed
> > ideas.
> > > To successfully apply we need (1) good ideas for projects and (2)
> people
> > > willing to mentor those ideas.
> > > For an initial brainstorming I suggest that we first figure out if we
> > want
> > > to participate (which mainly means we need to find people willing to
> > mentor
> > > projects) and then start collecting ideas. Ideas can be anything from
> > > infrastructure, to core development or implementation of new
> algorithms.
> > >
> > > Here is a quick example of how a project proposal could look like:
> > >
> > >
> > > Title: Performance Benchmarks and Experiments
> > >
> > > Description: To make decisions about new features and the evaluation of
> > > old assumptions we need up-to-date performance statistics on multiple
> > > levels of the systems and on different architectures (local,
> distributed,
> > > GPU). The systematic evaluation of performance can be measured with
> > > performance tests and micro-benchmarks. In this way, changes to the
> > project
> > > or alternative implementations (i.g. for low-level linear algebra
> > backends)
> > > can be systematically evaluated and compared. (Semi-) Automated
> > benchmarks
> > > can help make these decisions and challenge assumptions that were made
> > > during earlier development. In the course of this project, the student
> > > should build a benchmark infrastructure and conduct experiments, that
> > > compare different choices in critical parts (sparsity thresholds, BLAS
> > > backends, optimization decisions, etc.).
> > >
> > > Expected Outcome: A benchmark suite than can be used to detect
> > regressions
> > > or improvements in critical components of the system.
> > >
> > > Skills required: Java/Scala, some knowledge of benchmarking; preferred:
> > > knowledge about high-performance-computing and/or distributed systems.
> > >
> > > Possible Mentors: Matthias, Niketan, Nakul, Felix
> > >
> > >
> > > Let's decide on if we want to apply as an organization!
> > >
> > > - Felix
> > >
> >
> >
> >
> > --
> > *Madison J. Myers*
> > *--------------------------*
> > *Spark Technology Center, IBM Watson*
> > *UC Berkeley, Master of Information & Data Science '17*
> >
> > *King's College London, MA Political Science '14*
> > *New York University, BA Political Science '12*
> >
> >    -
> >       LinkedIn <http://linkedin.com/in/madisonjmyers>
> >
>

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