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From Deron Eriksson <deroneriks...@gmail.com>
Subject [DRAFT] November monthly report
Date Tue, 01 Nov 2016 23:43:21 GMT
Hello,

Here is a draft of the November monthly report due tomorrow that Felix and
I put together. Feedback is welcome.

Deron

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SystemML

SystemML provides declarative large-scale machine learning (ML) that aims at
flexible specification of ML algorithms and automatic generation of hybrid
runtime plans ranging from single node, in-memory computations, to
distributed
computations running on Apache Hadoop MapReduce and Apache Spark.

SystemML has been incubating since 2015-11-02.

Three most important issues to address in the move towards graduation:

 - Grow SystemML community: increase mailing list activity,
   increase adoption of SystemML for scalable machine learning, encourage
   data scientists to adopt DML and PyDML algorithm scripts, respond to
   user feedback to ensure SystemML meets the requirements of real-world
   situations, write papers, and present talks about SystemML.
 - Continue to produce releases.
 - Increase the diversity of our project's contributors and committers.

Any issues that the Incubator PMC (IPMC) or ASF Board wish/need to be aware
of?

 NONE.

How has the community developed since the last report?
 Our mailing list from August through October had 375 messages on a wide
range
 of topics. We have gained 4 new contributors to the main project since
August
 1st. Our website has been redesigned with the help of several design
engineers
 and we have commits from 3 new contributors to the website project. On
GitHub,
 the project has been starred 417 times and forked 156 times.

 Niketan Pansare gave a talk with the title "Apache SystemML - Declarative
 Machine Learning at Scale" on October 7th in the CS graduate seminar at UC
 Merced. Matthias Boehm gave a talk on "Compressed Linear Algebra for Large-
 Scale Machine Learning" at TU Dresden on August 30th. We presented the
papers
 "Compressed Linear Algebra for Large-Scale Machine Learning" (research
paper +
 poster) and "SystemML: Declarative Machine Learning on Spark" (industry
paper)
 at VLDB'16, gave two 90 minute tutorials at the BOSS'16 workshop,
co-located
 with VLDB'16, and our paper "SPOOF: Sum-Product Optimization and Operator
 Fusion for Large- Scale Machine Learning" has been accepted at CIDR'17.

How has the project developed since the last report?
 The main project has had 213 commits since August 1. The website project
has
 had 51 commits since August 1. Since August 1, 241 issues have been
reported
 on our JIRA site and 137 issues have been resolved or closed. 79 pull
requests
 have been created since August 1, and 72 pull requests have been closed.

Date of last release:

 2016-06-15 (version 0.10.0-incubating)

When were the last committers or PMC members elected?

 2016-05-07 Glenn Weidner
 2016-05-07 Faraz Makari Manshadi

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