Date: Sun, 16 Dec 2018 09:06:14 +0000 (UTC) From: Yuri Victorovich <yuri@FreeBSD.org> To: ports-committers@freebsd.org, svn-ports-all@freebsd.org, svn-ports-head@freebsd.org Subject: svn commit: r487566 - in head/math: . hipmcl hipmcl/files Message-ID: <201812160906.wBG96Erj038271@repo.freebsd.org>
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Author: yuri Date: Sun Dec 16 09:06:13 2018 New Revision: 487566 URL: https://svnweb.freebsd.org/changeset/ports/487566 Log: New port: math/hipmcl: High-performance parallel algorithm for large-scale network clustering Added: head/math/hipmcl/ head/math/hipmcl/Makefile (contents, props changed) head/math/hipmcl/distinfo (contents, props changed) head/math/hipmcl/files/ head/math/hipmcl/files/patch-CMakeLists.txt (contents, props changed) head/math/hipmcl/pkg-descr (contents, props changed) Modified: head/math/Makefile Modified: head/math/Makefile ============================================================================== --- head/math/Makefile Sun Dec 16 09:01:08 2018 (r487565) +++ head/math/Makefile Sun Dec 16 09:06:13 2018 (r487566) @@ -264,6 +264,7 @@ SUBDIR += grpn SUBDIR += gsl SUBDIR += hexcalc + SUBDIR += hipmcl SUBDIR += hs-Agda SUBDIR += hs-Agda-stdlib SUBDIR += hs-NumInstances Added: head/math/hipmcl/Makefile ============================================================================== --- /dev/null 00:00:00 1970 (empty, because file is newly added) +++ head/math/hipmcl/Makefile Sun Dec 16 09:06:13 2018 (r487566) @@ -0,0 +1,38 @@ +# $FreeBSD$ + +PORTNAME= HipMCL +DISTVERSION= g20180814 +CATEGORIES= math +MASTER_SITES= https://bitbucket.org/${BB_ACCOUNT}/${BB_PROJECT}/get/${BB_COMMIT}.tar.gz?dummy=/ + +MAINTAINER= yuri@FreeBSD.org +COMMENT= High-performance parallel algorithm for large-scale network clustering + +LICENSE= BSD3CLAUSE +LICENSE_FILE= ${WRKSRC}/license.txt + +LIB_DEPENDS= libCombBLAS.so:math/combblas \ + libmpi.so:net/mpich \ + libomp.so:devel/openmp +RUN_DEPENDS= ${LOCALBASE}/lib/gcc${GCC_DEFAULT}/libgcc_s.so.1:lang/gcc${GCC_DEFAULT} # because of the link flags induced by mpich + +USES= cmake:outsource compiler:c++14-lang dos2unix localbase:ldflags +DOS2UNIX_FILES= CMakeLists.txt + +CMAKE_ON= BUILD_SHARED_LIBS + +BB_ACCOUNT= azadcse +BB_PROJECT= ${PORTNAME:tl} +BB_COMMIT= e20476acc473 + +WRKSRC= ${WRKDIR}/${BB_ACCOUNT}-${BB_PROJECT}-${BB_COMMIT} + +PLIST_FILES= bin/${PORTNAME:tl} + +post-extract: + @${RM} -r ${WRKSRC}/src/CombBLAS + +do-install: + ${INSTALL_PROGRAM} ${BUILD_WRKSRC}/bin/hipmcl ${STAGEDIR}${PREFIX}/bin + +.include <bsd.port.mk> Added: head/math/hipmcl/distinfo ============================================================================== --- /dev/null 00:00:00 1970 (empty, because file is newly added) +++ head/math/hipmcl/distinfo Sun Dec 16 09:06:13 2018 (r487566) @@ -0,0 +1,3 @@ +TIMESTAMP = 1544950762 +SHA256 (HipMCL-g20180814.tar.gz) = 324fbe12f3547cd1e3da38d01ea2d6882061821a7cf6a7904e1402759c01e94c +SIZE (HipMCL-g20180814.tar.gz) = 43337935 Added: head/math/hipmcl/files/patch-CMakeLists.txt ============================================================================== --- /dev/null 00:00:00 1970 (empty, because file is newly added) +++ head/math/hipmcl/files/patch-CMakeLists.txt Sun Dec 16 09:06:13 2018 (r487566) @@ -0,0 +1,15 @@ +--- CMakeLists.txt.orig 2018-08-14 19:42:54 UTC ++++ CMakeLists.txt +@@ -30,10 +30,10 @@ else (NOT C14) + endif (NOT C14) + + +-ADD_SUBDIRECTORY( src/CombBLAS ) ++#ADD_SUBDIRECTORY( src/CombBLAS ) + set(CMAKE_RUNTIME_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR}/bin) + add_executable(hipmcl src/HipMCL.cpp) +-target_link_libraries(hipmcl CombBLASlib ) ++target_link_libraries(hipmcl CombBLAS ) + + + Added: head/math/hipmcl/pkg-descr ============================================================================== --- /dev/null 00:00:00 1970 (empty, because file is newly added) +++ head/math/hipmcl/pkg-descr Sun Dec 16 09:06:13 2018 (r487566) @@ -0,0 +1,16 @@ +HipMCL is a high-performance parallel algorithm for large-scale network +clustering. HipMCL parallelizes popular Markov Cluster (MCL) algorithm that has +been shown to be one of the most successful and widely used algorithms for +network clustering. It is based on random walks and was initially designed to +detect families in protein-protein interaction networks. Despite MCL's +efficiency and multi-threading support, scalability remains a bottleneck as it +fails to process networks of several hundred million nodes and billion edges in +an affordable running time. HipMCL overcomes all of these challenges by +developing massively-parallel algorithms for all components of MCL. HipMCL can +be 1000 times faster than the original MCL without any information loss. It can +easily cluster a network of ~75 million nodes with ~68 billion edges in ~2.4 +hours using ~2000 nodes of Cori supercomputer at NERSC. HipMCL is developed in +C++ language and uses standard OpenMP and MPI libraries for shared- and +distributed-memory parallelization. + +WWW: https://bitbucket.org/azadcse/hipmcl/wiki/Home
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