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From Andrew Musselman <...@apache.org>
Subject [ANNOUNCE] Apache Mahout 0.14.0 Release
Date Thu, 07 Mar 2019 02:25:17 GMT
The Apache Mahout PMC is pleased to announce the release of Mahout 0.14.0.
Mahout's goal is to create an environment for quickly creating
machine-learning applications that scale and run on the highest-performance
parallel computation engines available. Mahout comprises an interactive
environment and library that support generalized scalable linear algebra
and include many modern machine-learning algorithms. This release ships
some major changes from 0.13.0, most in support of simplicity and tidiness.

To get started with Apache Mahout 0.14.0, download the release artifacts
and signatures from http://www.apache.org/dist/mahout/0.14.0.

Many thanks to the contributors and committers who were part of this
release.


RELEASE HIGHLIGHTS

The theme of the 0.14.0 release is a major refactor for simplicity of usage
and maintenance. Non-core items have been moved to the new “community”
module, and a new “experimental” area has been created for cutting-edge
work that may require user tuning for specific hardware configurations.


STATS

A total of 15 separate JIRA issues are addressed in this release [1].


GETTING STARTED

Download the release artifacts and signatures at
https://mahout.apache.org/general/downloads.html. The examples directory
contains several working examples of the core functionality available in
Mahout. These can be run via scripts in the examples/bin directory. Most
examples do not need a Hadoop cluster in order to run.


FUTURE PLANS

0.14.1

As the project moves towards a 0.14.1 release, we are working on the
following:

* Further Native Integration for increased speedups

* JCuda backing for In-core Matrices and CUDA solvers

* Enumeration across multiple GPUs per JVM instance on a given instance

* GPU/OpenMP Acceleration for linear solvers

* Further integration with other libraries such as MLLib and SparkML

* Incorporate more statistical operations

* Runtime probing and optimization of available hardware for caching of
correct/most optimal solver


CONTRIBUTING

If you are interested in contributing, please see our How to Contribute [2]
page or contact us via email at dev@mahout.apache.org.


CREDITS

As with every release, we wish to thank all of the users and contributors
to Mahout. Please see the JIRA Release Notes [1] for individual credits.
Big thanks to Trevor Grant for a large effort on the refactoring and
cleanup in this release.


KNOWN ISSUES:

* The classify-wikipedia.sh example has an outdated link to the data files.
A workaround is to change the download section of the script to:  `curl
https://dumps.wikimedia.org/enwiki/latest/enwiki-latest-pages-articles10.xml-p002336425p003046511.bz2
-o ${WORK_DIR}/wikixml/enwiki-latest-pages-articles.xml.bz2`

* Currently GPU acceleration for supported operations is limited to a
single JVM instance

* Occasional segfault with certain GPU models and computations

* On older GPUs some tests fail when building ViennaCL due to card
limitations

* Currently automatic probing of a system’s hardware happens at each
supported operation, adding some overhead

* Currently the example in the main README errors out due to a packaging
error; we will be fixing this in the next point release



[1]
https://issues.apache.org/jira/issues/?jql=project%20%3D%20MAHOUT%20AND%20issuetype%20in%20(standardIssueTypes()%2C%20subTaskIssueTypes())%20AND%20status%20%3D%20Resolved%20AND%20fixVersion%20in%20(0.14.0)
<https://issues.apache.org/jira/issues/?jql=project%20%3D%20MAHOUT%20AND%20issuetype%20in%20(standardIssueTypes()%2C%20subTaskIssueTypes())%20AND%20status%20%3D%20Resolved%20AND%20fixVersion%20in%20(0.13.0%2C%200.13.1%2C%201.0.0)>

[2] https://mahout.apache.org/developers/how-to-contribute

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