Copyright (C) 2012-2020 RIKEN R-CCS

KMR is a high-performance map-reduce library in C/C++, Fortran, and Python. It simplifies data-processing by hiding the low-level details of using MPI (the Message Passing Interface). See "http://riken-rccs.github.io/kmr" for API usage.

KMR provides a set of map-reduce operations in MPI (Message Passing Interface), especially with a hope to be useful in Fortran. It is designed to work in-memory by exploiting the large amount of memory available on supercomputers. Data exchanges in KMR are, thus, performed by message passing instead of remote file operations that are the norm in popular map-reduce systems.

KMR includes functions found in fancy old data-parallel languages such as Connection-Machine Lisp. In the hindsight, the API design for Fortran hindered the usefulness of such fancy functions.

Building KMR requires a C compiler and an MPI library. The Python binding requires Python 3.4 and higher and the mpi4py package. KMR does not need any other uncommon libraries. However, a few routines have a restriction on the choice of MPI library (that is related to the behaviour of spawning processes). Note that recent KMR releases are only lightly tested.

KMR can be installed by just typing "configure", "make", and "make install". To change the installation directory, specify the "--prefix" option to the configure script.

$ ./configure --prefix=PATH_TO_INSTALL
$ make
$ make install

To build KMR documents, type "make htmldoc". It requres packages Doxygen, Python's pdoc, and GNU Troff. The documents are generated in the "./html" directory.

$ make htmldoc

To install KMR documents, type "make install-htmldoc" after installing KMR binaries.

$ make install-htmldoc

Care should be taken in the Cray environment to use KMR with Python3. KMR needs to be built with the same MPI library as mpi4py (the Python-MPI binding). But, the default environment is not the one used to build the mpi4py (for example, at the sites like kudpc.kyoto-u.ac.jp). It needs to switch the compiler and the MPI library appropriately before running the configure script.

$ module switch PrgEnv-cray PrgEnv-gnu
$ ./confugire ......

Care should be taken to use KMR with Python3. It needs CFLAGS=-Nclang and CXXFLAGS=-Nclang in configuring KMR, to match the configuration of mpi4py. Also, setting some environment variables is needed to use mpi4py. See the documents of Fugaku. It is recommended to start Python3 with environment variable XOS_MMM_L_HPAGE_TYPE=none.

The "src" directory contains the source code. The "cmd" directory contains the source code of the commands. The "kmrrun" directory contains the source code for shell command pipelining (or "streaming"). The "python3" directory contains the source code for the Pything binding. The "shell" directory contains the source code of the old shell command pipelining, which was mostly replaced by the "kmrrun" command. The "ex" directory contains a few examples.

The file "gensort-1.2.tar.gz" is a 3rd-party software of the data generator of TeraSort. The file "tpch_2_17_0.zip" is also a 3rd-party software of the data generator of TPC-H. These files are not part of KMR, but they are needed for running some examples.

• CHANGELOG.md
• Examples: ex
• Tools: tool

The files in "src" directory include the materials copyrighted by Akiyama Lab., Tokyo Institute of Technology (titec) (code from the GHOST Project) and the materials copyrighted by The Regents of the University of California (qsort code from NetBSD-5.1.2). The files in "ex" directory include the materials copyrighted by Stanford University (code from Phoenix MapReduce Library), and the materials copyrighted by Sandia Corporation (code from MapReduce-MPI Library). The files in "gensort-1.2.tar.gz" are copyrighted by Chris Nyberg ([email protected]). The files in "tpch_2_17_0.zip" are copyrighted by the Transaction Processing Performance Council (TPC).

KMR is copyrighted by RIKEN R-CCS and distributed under the BSD 2-Clause License. Part of the results is obtained by using Fugaku at RIKEN R-CCS.