package ( " mkl " )
set_homepage ( " https://software.intel.com/content/www/us/en/develop/tools/oneapi/components/onemkl.html " )
set_description ( " Intel® oneAPI Math Kernel Library " )
if is_plat ( " windows " ) then
if is_arch ( " x64 " ) then
add_urls ( " https://anaconda.org/intel/mkl-static/$(version).tar.bz2 " , { version = function ( version )
local mv = version : split ( " %+ " )
return format ( " %s/download/win-64/mkl-static-%s-intel_%s " , mv [ 1 ] , mv [ 1 ] , mv [ 2 ] )
end } )
add_versions ( " 2021.2.0+296 " , " 54209e5d9c4778381f08b9a90e900c001494db020cda426441cd624cb0f7ebdc " )
add_resources ( " 2021.2.0+296 " , " headers " , " https://anaconda.org/intel/mkl-include/2021.2.0/download/win-64/mkl-include-2021.2.0-intel_296.tar.bz2 " , " ba222ea4ceb9e09976f23a3df39176148b4469b297275f3d05c1ad411b3d54c3 " )
add_versions ( " 2021.3.0+524 " , " 842628a8621f2ca19d7f1809e50420e311edf20b9bea18404dd1c20af798f5e6 " )
add_resources ( " 2021.3.0+524 " , " headers " , " https://anaconda.org/intel/mkl-include/2021.3.0/download/win-64/mkl-include-2021.3.0-intel_524.tar.bz2 " , " 8ca8f77d0c57a434541d62a9c61781aa37225f5e669de01b8cc98488b3f9e82f " )
add_versions ( " 2022.1.0+192 " , " fd9a529c0caa27ee3068e8d845f07e536970b0cbf713118d1f3daa32fb2b9e8c " )
add_resources ( " 2022.1.0+192 " , " headers " , " https://anaconda.org/intel/mkl-include/2022.1.0/download/win-64/mkl-include-2022.1.0-intel_192.tar.bz2 " , " b6452e8c4891fcfab452bc23c6adc9c61ab6635fa494bb2b29725473c1013abc " )
add_versions ( " 2023.2.0+49496 " , " 21a9fe03ba80009934a50b9d75f16757b9e49415e44245ced3b896fd471351ca " )
add_resources ( " 2023.2.0+49496 " , " headers " , " https://anaconda.org/intel/mkl-include/2023.2.0/download/win-64/mkl-include-2023.2.0-intel_49496.tar.bz2 " , " daa93c899e6c7627232fa60e67a2b6079cd29752e8ba1251ae895a57e51defa7 " )
add_versions ( " 2024.1.0+692 " , " 6431647057cd8757a464a3f6ab2099139e059d04446f04443afd2570febe42bf " )
add_resources ( " 2024.1.0+692 " , " headers " , " https://anaconda.org/intel/mkl-include/2024.1.0/download/win-64/mkl-include-2024.1.0-intel_692.tar.bz2 " , " 28229844aa6c19870531452e5805ab876da4a5df896a9e753e6b481da2d389cb " )
add_versions ( " 2024.2.0+661 " , " e760103a484d5132f0af35e58ccad7b576536d38744141e776f3ad1673adc455 " )
add_resources ( " 2024.2.0+661 " , " headers " , " https://anaconda.org/intel/mkl-include/2024.2.0/download/win-64/mkl-include-2024.2.0-intel_661.tar.bz2 " , " 34f5cc20b6d2ab7c82f301b108fa2ac48e1f6c0acd8ad166897fb53184d5c93e " )
elseif is_arch ( " x86 " ) then
add_urls ( " https://anaconda.org/intel/mkl-static/$(version).tar.bz2 " , { version = function ( version )
local mv = version : split ( " %+ " )
return format ( " %s/download/win-32/mkl-static-%s-intel_%s " , mv [ 1 ] , mv [ 1 ] , mv [ 2 ] )
end } )
add_versions ( " 2021.2.0+296 " , " eaf0df027d58c5fd948f86b83dfc4d608855962cbdb04551712c9aeeb7b26eca " )
add_resources ( " 2021.2.0+296 " , " headers " , " https://anaconda.org/intel/mkl-include/2021.2.0/download/win-32/mkl-include-2021.2.0-intel_296.tar.bz2 " , " 8ed173edff75783426de1bbc1d122266047fc84d4cfc5a9b810b1f2792f02c37 " )
add_versions ( " 2021.3.0+524 " , " 799a42ab4422d1532be65e40ed4ac5e81692b796ae3de37a7489389f9e10f112 " )
add_resources ( " 2021.3.0+524 " , " headers " , " https://anaconda.org/intel/mkl-include/2021.3.0/download/win-32/mkl-include-2021.3.0-intel_524.tar.bz2 " , " 9ff8e58dc98da8ec2fe3b15eac2abfef4eb3335d90feeb498f84126371ccea8c " )
add_versions ( " 2022.0.3+171 " , " b34d5e5d0dd779b117666c9fc89d008431f6239ad60fc08a52a6b874fdf24517 " )
add_resources ( " 2022.0.3+171 " , " headers " , " https://anaconda.org/intel/mkl-include/2022.0.3/download/win-32/mkl-include-2022.0.3-intel_171.tar.bz2 " , " f696cd98b2f33b2c21bf7b70f57e894a763dad1831c721a348614cfeb17a4541 " )
add_versions ( " 2023.2.0+49496 " , " 4795b6a00b1b7ae5c608de67ba2c79ad152223d0eaf4aba46db848bbae268718 " )
add_resources ( " 2023.2.0+49496 " , " headers " , " https://anaconda.org/intel/mkl-include/2023.2.0/download/win-32/mkl-include-2023.2.0-intel_49496.tar.bz2 " , " 0ed907ecc2eaae0ed8c280814392b5b80cc19df78838d9688273a12bd72c7bf8 " )
add_versions ( " 2024.1.0+692 " , " 7a8622f23a27fa487f08653645b6dc3f46b10f5b60ea2b90377812571730d0d9 " )
add_resources ( " 2024.1.0+692 " , " headers " , " https://anaconda.org/intel/mkl-include/2024.1.0/download/win-32/mkl-include-2024.1.0-intel_692.tar.bz2 " , " 8994e1c5b5599934e83eb964a136be98dc5a6355f3f5b35cab44cdc0e8b970dd " )
add_versions ( " 2024.2.0+661 " , " 0a126754b76cf41e9fbc10e7cb70d69018059a2a413560938184b7886bced28b " )
add_resources ( " 2024.2.0+661 " , " headers " , " https://anaconda.org/intel/mkl-include/2024.2.0/download/win-32/mkl-include-2024.2.0-intel_661.tar.bz2 " , " 431feac62519a0d65c85e801d7329cb7caa66ced53a0b4d26f15420d06d1717d " )
end
elseif is_plat ( " macosx " ) and is_arch ( " x86_64 " ) then
add_urls ( " https://anaconda.org/intel/mkl-static/$(version).tar.bz2 " , { version = function ( version )
local mv = version : split ( " %+ " )
return format ( " %s/download/osx-64/mkl-static-%s-intel_%s " , mv [ 1 ] , mv [ 1 ] , mv [ 2 ] )
end } )
add_versions ( " 2021.2.0+269 " , " b7af248f01799873333cbd388b5efa19601cf6815dc38713509974783f4b1ccd " )
add_resources ( " 2021.2.0+269 " , " headers " , " https://anaconda.org/intel/mkl-include/2021.2.0/download/osx-64/mkl-include-2021.2.0-intel_269.tar.bz2 " , " 5215d62cadeb3f8021230163dc35ad38259e3688aa0f39d7da69ebe54ab45624 " )
add_versions ( " 2021.3.0+517 " , " 85a636642ee4f76fba50d16c45099cd22082eb1f8b835a4a0b455ec4796ebf8f " )
add_resources ( " 2021.3.0+517 " , " headers " , " https://anaconda.org/intel/mkl-include/2021.3.0/download/osx-64/mkl-include-2021.3.0-intel_517.tar.bz2 " , " db9896e667b31908b398d515108433d8df95e6429ebfb9d493a463f25886019c " )
add_versions ( " 2022.1.0+208 " , " 06e5dcd7b8f11f9736d4e4d7d5a9972333ee8822cf2263ecccf4cb0e3cc95530 " )
add_resources ( " 2022.1.0+208 " , " headers " , " https://anaconda.org/intel/mkl-include/2022.1.0/download/osx-64/mkl-include-2022.1.0-intel_208.tar.bz2 " , " 569ea516148726b2698f17982aba2d9ec1bfb321f0180be938eddbc696addbc5 " )
add_versions ( " 2023.2.0+49499 " , " 2e2f6bd275e439f82f081e28e774dec663718b199a696da635934536a51faa73 " )
add_resources ( " 2023.2.0+49499 " , " headers " , " https://anaconda.org/intel/mkl-include/2023.2.0/download/osx-64/mkl-include-2023.2.0-intel_49499.tar.bz2 " , " c3940a33498df821821c28dc292f7d7a739b11892856fd9fbbc3de5cf0990b00 " )
elseif is_plat ( " linux " ) then
if is_arch ( " x86_64 " ) then
add_urls ( " https://anaconda.org/intel/mkl-static/$(version).tar.bz2 " , { version = function ( version )
local mv = version : split ( " %+ " )
return format ( " %s/download/linux-64/mkl-static-%s-intel_%s " , mv [ 1 ] , mv [ 1 ] , mv [ 2 ] )
end } )
add_versions ( " 2021.2.0+296 " , " 2bcaefefd593e4fb521e1fc88715f672ae5b9d1706babf10e3a10ef43ea0f983 " )
add_resources ( " 2021.2.0+296 " , " headers " , " https://anaconda.org/intel/mkl-include/2021.2.0/download/linux-64/mkl-include-2021.2.0-intel_296.tar.bz2 " , " 13721fead8a3eddee15b914fd3ae9cf2095966af79bbc2f086462eda9fff4d62 " )
add_versions ( " 2021.3.0+520 " , " c1e21988bbf05b455077a512cb719ef59ec6e06a6807cfefb892945ec19de5d0 " )
add_resources ( " 2021.3.0+520 " , " headers " , " https://anaconda.org/intel/mkl-include/2021.3.0/download/linux-64/mkl-include-2021.3.0-intel_520.tar.bz2 " , " b0df7fb4c2071fdec87b567913715a2e47dca05e8c3ac4e5bcf072d7804085af " )
add_versions ( " 2022.1.0+223 " , " 9dfb2940447cc8cf7ca3e647e2b62be714e89cbca162998cbf4e05deb69b6bd2 " )
add_resources ( " 2022.1.0+223 " , " headers " , " https://anaconda.org/intel/mkl-include/2022.1.0/download/linux-64/mkl-include-2022.1.0-intel_223.tar.bz2 " , " 704e658a9b25a200f8035f3d0a8f2e094736496a2169f87609f1cfed2e2eb0a9 " )
add_versions ( " 2023.2.0+49495 " , " 5c91829865f36f7f5845f5b38e509bb05bee1a38ccfd2caa0eabc0c28aaa4082 " )
add_resources ( " 2023.2.0+49495 " , " headers " , " https://anaconda.org/intel/mkl-include/2023.2.0/download/linux-64/mkl-include-2023.2.0-intel_49495.tar.bz2 " , " 0dfb6ca3c17d99641f20877579c78155cf95aa0b22363bcc91b1d57df4646318 " )
add_versions ( " 2024.1.0+691 " , " be8833b094253d51abe49de418f7db2260f4c8f32514969a4a2eabaadc5d55c2 " )
add_resources ( " 2024.1.0+691 " , " headers " , " https://anaconda.org/intel/mkl-include/2024.1.0/download/linux-64/mkl-include-2024.1.0-intel_691.tar.bz2 " , " e36b2e74f5c28ff91565abe47a09dc246c9cf725e0d05b5fb08813b4073ea68b " )
add_versions ( " 2024.2.0+663 " , " 7ee44680030cf187c430a34051ccf37a2c697ad82b62fb0508dfe7a94d7e27f7 " )
add_resources ( " 2024.2.0+663 " , " headers " , " https://anaconda.org/intel/mkl-include/2024.2.0/download/linux-64/mkl-include-2024.2.0-intel_663.tar.bz2 " , " 2e29ca36f199bafed778230b054256593c2d572aeb050389fd87355ba0466d13 " )
elseif is_arch ( " i386 " ) then
add_urls ( " https://anaconda.org/intel/mkl-static/$(version).tar.bz2 " , { version = function ( version )
local mv = version : split ( " %+ " )
return format ( " %s/download/linux-32/mkl-static-%s-intel_%s " , mv [ 1 ] , mv [ 1 ] , mv [ 2 ] )
end } )
add_versions ( " 2021.2.0+296 " , " 34a1bc80a4a39ca5a55d29e9fcc803380fbc4d029ae496e60a918e8d12db68c2 " )
add_resources ( " 2021.2.0+296 " , " headers " , " https://anaconda.org/intel/mkl-include/2021.2.0/download/linux-32/mkl-include-2021.2.0-intel_296.tar.bz2 " , " 7fcbc945377b486b40d29b170d0b6c39bbc5b430ac7284dae2046bbf610f643d " )
add_versions ( " 2021.3.0+520 " , " 4df801f5806d1934c5f3887e8f2153fb0c929be9545627cf99ce9e72c907653b " )
add_resources ( " 2021.3.0+520 " , " headers " , " https://anaconda.org/intel/mkl-include/2021.3.0/download/linux-32/mkl-include-2021.3.0-intel_520.tar.bz2 " , " dce1f2a08499f34ed4883b807546754c1547a9cc2424b7b75b9233641cf044c1 " )
add_versions ( " 2022.0.2+136 " , " 157c09248cb5e5cbcb28ef8db53d529ab2f049e9269b2a2bc90601c0c420080e " )
add_resources ( " 2022.0.2+136 " , " headers " , " https://anaconda.org/intel/mkl-include/2022.0.2/download/linux-32/mkl-include-2022.0.2-intel_136.tar.bz2 " , " 16882aeddbd33a2dc9210e61c59db6ad0d7d9efdd40ad1544b369b0830683371 " )
add_versions ( " 2023.2.0+49495 " , " 9cdcb26ebbbe1510611f01f75780c0e69522d5df73395370a73c81413beaa56a " )
add_resources ( " 2023.2.0+49495 " , " headers " , " https://anaconda.org/intel/mkl-include/2023.2.0/download/linux-32/mkl-include-2023.2.0-intel_49495.tar.bz2 " , " b4433c6839bb7f48951b2dcf409dec7306aee3649c539ee0513d8bfb1a1ea283 " )
add_versions ( " 2024.1.0+691 " , " 8bd52f73844edc59fe925fa9edef66a7158e502df7c06ddc532d1b370df4fb7d " )
add_resources ( " 2024.1.0+691 " , " headers " , " https://anaconda.org/intel/mkl-include/2024.1.0/download/linux-32/mkl-include-2024.1.0-intel_691.tar.bz2 " , " 88529f8bea2498e88b2cf8dc7aa3735f46f348cf5047006dfc6455f8e2bbdd30 " )
add_versions ( " 2024.2.0+663 " , " 505eea9981643dac10f342eca80603982365f6b598e6435e07c9d5385622f578 " )
add_resources ( " 2024.2.0+663 " , " headers " , " https://anaconda.org/intel/mkl-include/2024.2.0/download/linux-32/mkl-include-2024.2.0-intel_663.tar.bz2 " , " d97e655707590ba38d1240a4f9be3f60df2bc82f3ab5f7b16cf2735d4d9ba401 " )
end
end
add_configs ( " threading " , { description = " Choose threading modal for mkl. " , default = " tbb " , type = " string " , values = { " tbb " , " openmp " , " gomp " , " seq " } } )
add_configs ( " interface " , { description = " Choose index integer size for the interface. " , default = 32 , values = { 32 , 64 } } )
on_fetch ( " fetch " )
if is_plat ( " linux " ) then
add_syslinks ( " pthread " , " dl " )
end
on_load ( function ( package )
-- Refer to [oneAPI Math Kernel Library Link Line Advisor](https://www.intel.com/content/www/us/en/developer/tools/oneapi/onemkl-link-line-advisor.html)
-- to get the link option for MKL library.
local suffix = ( package : config ( " interface " ) == 32 and " lp64 " or " ilp64 " )
if package : config ( " interface " ) == 64 then
package : add ( " defines " , " MKL_ILP64 " )
end
package : add ( " links " , package : is_arch ( " x64 " , " x86_64 " ) and " mkl_blas95_ " .. suffix or " mkl_blas95 " )
package : add ( " links " , package : is_arch ( " x64 " , " x86_64 " ) and " mkl_lapack95_ " .. suffix or " mkl_lapack95 " )
if package : has_tool ( " cc " , " gcc " , " gxx " ) then
local flags = { " -Wl,--start-group " }
table.insert ( flags , package : is_arch ( " x64 " , " x86_64 " ) and " -lmkl_intel_ " .. suffix or " -lmkl_intel " )
local threading = package : config ( " threading " )
if threading == " tbb " then
table.insert ( flags , " -lmkl_tbb_thread " )
package : add ( " deps " , " tbb " )
elseif threading == " seq " then
table.insert ( flags , " -lmkl_sequential " )
elseif threading == " openmp " then
table.insert ( flags , " -lmkl_intel_thread " )
table.insert ( flags , " -lomp " )
elseif threading == " gomp " then
table.insert ( flags , " -lmkl_gnu_thread " )
table.insert ( flags , " -lgomp " )
end
table.insert ( flags , " -lmkl_core " )
table.insert ( flags , " -Wl,--end-group " )
package : add ( " ldflags " , table.concat ( flags , " " ) )
else
package : add ( " links " , package : is_arch ( " x64 " , " x86_64 " ) and " mkl_intel_ " .. suffix or " mkl_intel_c " )
local threading = package : config ( " threading " )
if threading == " tbb " then
package : add ( " links " , " mkl_tbb_thread " )
package : add ( " deps " , " tbb " )
elseif threading == " seq " then
package : add ( " links " , " mkl_sequential " )
elseif threading == " openmp " then
package : add ( " links " , " mkl_intel_thread " , " omp " )
elseif threading == " gomp " then
package : add ( " links " , " mkl_gnu_thread " , " gomp " )
end
package : add ( " links " , " mkl_core " )
end
end )
on_install ( " windows|!arm64 " , " macosx|!arm64 " , " linux|x86_64 " , " linux|i386 " , function ( package )
local headerdir = package : resourcedir ( " headers " )
if package : is_plat ( " windows " ) then
os.trymv ( path.join ( " Library " , " lib " ) , package : installdir ( ) )
os.trymv ( path.join ( headerdir , " Library " , " include " ) , package : installdir ( ) )
else
os.trymv ( path.join ( " lib " ) , package : installdir ( ) )
os.trymv ( path.join ( headerdir , " include " ) , package : installdir ( ) )
end
end )
on_test ( function ( package )
assert ( package : check_csnippets ( { test = [ [
void test ( ) {
double A [ 6 ] = { 1.0 , 2.0 , 1.0 , - 3.0 , 4.0 , - 1.0 } ;
double B [ 6 ] = { 1.0 , 2.0 , 1.0 , - 3.0 , 4.0 , - 1.0 } ;
double C [ 9 ] = { .5 , .5 , .5 , .5 , .5 , .5 , .5 , .5 , .5 } ;
cblas_dgemm ( CblasColMajor , CblasNoTrans , CblasTrans , 3 , 3 , 2 , 1 , A , 3 , B , 3 , 2 , C , 3 ) ;
}
] ] } , { includes = " mkl_cblas.h " } ) )
end )