!!! Welcome to KMR

This is KMR, a high-performance map-reduce library.
KMR-1.0 is available on the K computer since 2013-04-26.
KMR works on ordinary clusters as well.

__Latest release is KMR-1.1 (2013-09-20).__.

KMR is a set of high-performance map-reduce operations in the MPI (Message Passing Interface) environment.
It makes programming for data-processing much easier by hiding low-level details of message passing.
Its main targets are large-scale supercomputers with thousands of compute nodes, such as K and Fujitsu FX10.
On these platforms, KMR provides utilities other than the map-reduce operations which address issues such as accessing very large file-systems.

KMR is designed to work on-memory and exploits large amount of memory available on supercomputers, whereas most map-reduce implementations are designed to work with external (disk-based) operations.
So, data exchanges in KMR occur as message passing instead of remote file operations.
The KMR routines work in bulk-synchronous and the most part of the code is sequential, but the code inside the mapper and reducer are multi-threaded.

!!Project Site

* Project Overview and other Activities of the Team at RIKEN:
** [http://mt.aics.riken.jp]

!!Documents

* Overview and API Document:
** [http://mt.aics.riken.jp/kmr/docs/kmr-1.1/html/index.html]
** It is a Doxgen generated document, included in the installation.
//* Overview and API Document (Newer, corrected, for the next release):
//** [https://mt.aics.riken.jp/kmr/docs/next/html/index.html]
//** Documentation in the distribution is late, and it is placed here for late breaking.

!!Downloading

* Source Code Download:
** [Download]
** KMR source is available with LGPL-2.1.

!!Issue Reporting

* KMR Issue Tracker:
** [http://mt.aics.riken.jp/jtrac/]
** Please make a new user by the login-page to report a new issue.

!!Publications

* [cluster2013.pdf]: __K MapReduce: A Scalable Tool for Data-Processing and Search/Ensemble Applications on Large-Scale Supercomputers__.  Motohiko Matsuda, Naoya Maruyama, and Shinichiro Takizawa. IEEE Cluster Computing (CLUSTER) 2013. (C) Copyright IEEE.  [IEEE Explore|http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6702663].\\
 It describes an overview and optimisations used in KMR.

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!!DISCLAIMER

KMR comes with ABSOLUTELY NO WARRANTY.
This wiki also comes with ABSOLUTELY NO WARRANTY.
Contents are liable to change.

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!!Acknowledgment

KMR is a product of RIKEN AICS.
Part of the results is obtained by using the K computer at RIKEN AICS.

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