{ai}[foss/2022a,GCCcore/11.3.0] tsne-cuda v3.0.1, faiss v1.7.2, gflag…

…s v2.2.2, cxxopts v3.1.1 /w CUDA 11.7.0

easybuild/easyconfigs/c/cxxopts/cxxopts-3.1.1-GCCcore-11.3.0.eb

@@ -0,0 +1,30 @@
+##
+# Author:    Robert Mijakovic <[email protected]>
+##
+# update: thembl
+easyblock = 'CMakeMake'
+
+name = 'cxxopts'
+version = '3.1.1'
+
+homepage = 'https://github.com/jarro2783/cxxopts'
+description = """cxxopts is a lightweight C++ command line option parser"""
+
+toolchain = {'name': 'GCCcore', 'version': '11.3.0'}
+
+github_account = 'jarro2783'
+source_urls = [GITHUB_SOURCE]
+sources = ['v%(version)s.tar.gz']
+checksums = ['523175f792eb0ff04f9e653c90746c12655f10cb70f1d5e6d6d9491420298a08']
+
+builddependencies = [
+    ('CMake', '3.24.3'),
+    ('binutils', '2.38'),
+]
+
+sanity_check_paths = {
+    'files': ["include/cxxopts.hpp"],
+    'dirs': ["lib"]
+}
+
+moduleclass = 'devel'

easybuild/easyconfigs/f/faiss/faiss-1.7.2-foss-2022a-CUDA-11.7.0.eb

@@ -0,0 +1,54 @@
+# Thomas Hoffmann, EMBL Heidelberg, [email protected], 2022/11
+easyblock = 'CMakePythonPackage'
+
+name = 'faiss'
+version = '1.7.2'
+versionsuffix = '-CUDA-%(cudaver)s'
+
+homepage = 'https://github.com/facebookresearch/faiss'
+description = """Faiss is a library for efficient similarity search and clustering of dense      
+vectors. It contains algorithms that search in sets of vectors of any size, up  
+to ones that possibly do not fit in RAM. It also contains supporting code for   
+evaluation and parameter tuning. Faiss is written in C++ with complete wrappers 
+for Python/numpy. Some of the most useful algorithms are implemented on the GPU.
+It is developed primarily at Facebook AI Research."""
+
+toolchain = {'name': 'foss', 'version': '2022a'}
+toolchainopts = {'pic': True}
+
+source_urls = [GITHUB_SOURCE]
+sources = ['v%(version)s.tar.gz']
+checksums = ['d49b4afd6a7a5b64f260a236ee9b2efb760edb08c33d5ea5610c2f078a5995ec']
+
+github_account = 'facebookresearch'
+
+builddependencies = [
+    ('CMake', '3.23.1'),
+    ('SWIG', '4.0.2'),
+    ('googletest', '1.11.0'),
+]
+dependencies = [
+    ('CUDA', '11.7.0', '', True),
+    ('SciPy-bundle', '2022.05')
+]
+
+configopts = '-DFETCHCONTENT_FULLY_DISCONNECTED=ON'
+configopts += ' -DFAISS_ENABLE_C_API=ON'
+configopts += ' -DCMAKE_CUDA_ARCHITECTURES="%(cuda_cc_cmake)s"'
+configopts += ' -DBUILD_TESTING=ON'
+configopts = [
+    configopts + ' -DBUILD_SHARED_LIBS=ON',
+    configopts + ' -DBUILD_SHARED_LIBS=OFF'  # order important due to libfaiss_python_callbacks.so static link.
+]
+
+build_cmd_targets = ' faiss swigfaiss'
+# remove tests (all) from target preinstall:
+preinstallopts = 'sed -i "s/^preinstall:.*/preinstall: faiss/g" Makefile &&'
+install_cmd = 'make install && '
+install_cmd += 'cd faiss/python && pip install . --prefix=%(installdir)s --ignore-installed --no-deps'
+sanity_check_paths = {
+    'files': ['lib64/libfaiss.%s' % x for x in ['a', SHLIB_EXT]],
+    'dirs': ["lib", 'include']
+}
+
+moduleclass = 'lib'

easybuild/easyconfigs/g/gflags/gflags-2.2.2-GCCcore-11.3.0.eb

@@ -0,0 +1,35 @@
+easyblock = 'CMakeMake'
+
+name = 'gflags'
+version = '2.2.2'
+
+homepage = 'https://github.com/gflags/gflags'
+description = """
+The gflags package contains a C++ library that implements commandline flags
+processing.  It includes built-in support for standard types such as string
+and the ability to define flags in the source file in which they are used.
+"""
+
+toolchain = {'name': 'GCCcore', 'version': '11.3.0'}
+toolchainopts = {'pic': True}
+
+source_urls = ['https://github.com/gflags/gflags/archive/']
+sources = ['v%(version)s.tar.gz']
+checksums = ['34af2f15cf7367513b352bdcd2493ab14ce43692d2dcd9dfc499492966c64dcf']
+
+builddependencies = [
+    ('binutils', '2.38'),
+    ('CMake', '3.24.3'),
+]
+
+configopts = '-DBUILD_SHARED_LIBS=ON -DBUILD_STATIC_LIBS=ON'
+
+sanity_check_paths = {
+    'files': ['bin/gflags_completions.sh'] +
+             ['lib/%s' % x for x in ['libgflags.%s' % SHLIB_EXT, 'libgflags_nothreads.%s' % SHLIB_EXT,
+                                     'libgflags.a', 'libgflags_nothreads.a']] +
+             ['include/gflags/gflags_completions.h'],
+    'dirs': [],
+}
+
+moduleclass = 'devel'

easybuild/easyconfigs/t/tsne-cuda/tsne-cuda-3.0.1-foss-2022a-CUDA-11.7.0.eb

@@ -0,0 +1,57 @@
+# Thomas Hoffmann, EMBL Heidelberg, [email protected], 2023/11
+easyblock = 'CMakePythonPackage'
+
+name = 'tsne-cuda'
+version = '3.0.1'
+versionsuffix = '-CUDA-11.7.0'
+
+homepage = 'https://github.com/CannyLab/tsne-cuda'
+description = """A optimized CUDA version of FIt-SNE algorithm with associated python modules. We
+find that our implementation of t-SNE can be up to 1200x faster than Sklearn, or
+up to 50x faster than Multicore-TSNE when used with the right GPU. The paper    
+describing our approach, as well as the results below, is available at          
+https://arxiv.org/abs/1807.11824."""
+
+toolchain = {'name': 'foss', 'version': '2022a'}
+
+github_account = 'CannyLab'
+source_urls = [GITHUB_SOURCE]
+sources = ['%(version)s.tar.gz']
+patches = ['%(name)s-%(version)s_cudacc.patch']
+checksums = [
+    {'3.0.1.tar.gz': '0f778247191f483df22dc4dbed792c9a6a9152ee7404329c4d9da3fd9a8774d6'},
+    {'tsne-cuda-3.0.1_cudacc.patch': 'f9a097e871daf2951e4aa8f8a1f50bfe6ecd3f85f54f604dadf22519603aa013'},
+]
+
+builddependencies = [
+    ('CMake', '3.24.3'),
+    ('googletest', '1.11.0'),
+    ('cxxopts', '3.1.1'),
+    ('cppzmq', '4.9.0', '', SYSTEM),
+
+]
+dependencies = [
+    ('Python', '3.10.4'),
+    ('CUDA', '11.7.0', '', SYSTEM),
+    ('gflags', '2.2.2'),
+    ('ZeroMQ', '4.3.4'),
+    ('faiss', '1.7.2', versionsuffix),
+]
+
+configopts = "-DCMAKE_CUDA_ARCHITECTURES='%(cuda_cc_cmake)s' "
+configopts += '-DBUILD_PYTHON=ON '
+configopts += '-DWITH_MKL=OFF '
+configopts += '-DWITH_ZMQ=ON '
+
+use_pip = True
+
+install_cmd = 'python -m pip install python/ --prefix=%(installdir)s '
+
+options = {'modulename': 'tsnecuda'}
+
+sanity_check_paths = {
+    'files': [],
+    'dirs': ['lib/python%(pyshortver)s/site-packages/tsnecuda'],
+}
+
+moduleclass = 'ai'

easybuild/easyconfigs/t/tsne-cuda/tsne-cuda-3.0.1_cudacc.patch

@@ -0,0 +1,114 @@
+# Thomas Hoffmann, EMBL Heidelberg, [email protected]
+# use gencodes according to CUDA_CMAKE_ARCHITECUTES
+#
+diff -ru tsne-cuda-3.0.1/CMakeLists.txt tsne-cuda-3.0.1_cudacc/CMakeLists.txt
+--- tsne-cuda-3.0.1/CMakeLists.txt	2021-12-10 02:27:07.000000000 +0100
++++ tsne-cuda-3.0.1_cudacc/CMakeLists.txt	2023-11-07 18:53:05.060718265 +0100
+@@ -58,54 +58,59 @@
+     set(CMAKE_CUDA_STANDARD_REQUIRED ON)
+ endif()
+
+-if(CUDAToolkit_VERSION_MAJOR EQUAL "10")
+-    set(CUDA_ARCH
+-        -gencode=arch=compute_30,code=sm_30
+-        -gencode=arch=compute_35,code=sm_35
+-        -gencode=arch=compute_37,code=sm_37
+-        -gencode=arch=compute_50,code=sm_50
+-        -gencode=arch=compute_52,code=sm_52
+-        -gencode=arch=compute_60,code=sm_60
+-        -gencode=arch=compute_61,code=sm_61
+-        -gencode=arch=compute_70,code=sm_70
+-        -gencode=arch=compute_75,code=sm_75
+-    )
+-elseif(CUDAToolkit_VERSION_MAJOR EQUAL "11" AND CUDAToolkit_VERSION_MINOR LESS "1")
+-    set(CUDA_ARCH
+-        -gencode=arch=compute_35,code=sm_35
+-        -gencode=arch=compute_37,code=sm_37
+-        -gencode=arch=compute_50,code=sm_50
+-        -gencode=arch=compute_52,code=sm_52
+-        -gencode=arch=compute_60,code=sm_60
+-        -gencode=arch=compute_61,code=sm_61
+-        -gencode=arch=compute_70,code=sm_70
+-        -gencode=arch=compute_75,code=sm_75
+-        -gencode=arch=compute_80,code=sm_80
+-    )
+-elseif(CUDAToolkit_VERSION_MAJOR EQUAL "11")
+-    set(CUDA_ARCH
+-        -gencode=arch=compute_35,code=sm_35
+-        -gencode=arch=compute_37,code=sm_37
+-        -gencode=arch=compute_50,code=sm_50
+-        -gencode=arch=compute_52,code=sm_52
+-        -gencode=arch=compute_60,code=sm_60
+-        -gencode=arch=compute_61,code=sm_61
+-        -gencode=arch=compute_70,code=sm_70
+-        -gencode=arch=compute_75,code=sm_75
+-        -gencode=arch=compute_80,code=sm_80
+-        -gencode=arch=compute_86,code=sm_86
+-    )
+-else()
+-    set(CUDA_ARCH
+-        -gencode=arch=compute_30,code=sm_30
+-        -gencode=arch=compute_35,code=sm_35
+-        -gencode=arch=compute_37,code=sm_37
+-        -gencode=arch=compute_50,code=sm_50
+-        -gencode=arch=compute_52,code=sm_52
+-        -gencode=arch=compute_60,code=sm_60
+-        -gencode=arch=compute_61,code=sm_61
+-        )
+-endif()
++set(CUDA_ARCH "")
++foreach(sm IN ${CUDA_CMAKE_ARCHITECUTES})
++    set(CUDA_ARCH "-gencode=arch=compute_${sm},code=sm_${sm}")
++endforeach()
++
++#if(CUDAToolkit_VERSION_MAJOR EQUAL "10")
++#    set(CUDA_ARCH
++#        -gencode=arch=compute_30,code=sm_30
++#        -gencode=arch=compute_35,code=sm_35
++#        -gencode=arch=compute_37,code=sm_37
++#        -gencode=arch=compute_50,code=sm_50
++#        -gencode=arch=compute_52,code=sm_52
++#        -gencode=arch=compute_60,code=sm_60
++#        -gencode=arch=compute_61,code=sm_61
++#        -gencode=arch=compute_70,code=sm_70
++#        -gencode=arch=compute_75,code=sm_75
++#    )
++#elseif(CUDAToolkit_VERSION_MAJOR EQUAL "11" AND CUDAToolkit_VERSION_MINOR LESS "1")
++#    set(CUDA_ARCH
++#        -gencode=arch=compute_35,code=sm_35
++#        -gencode=arch=compute_37,code=sm_37
++#        -gencode=arch=compute_50,code=sm_50
++#        -gencode=arch=compute_52,code=sm_52
++#        -gencode=arch=compute_60,code=sm_60
++#        -gencode=arch=compute_61,code=sm_61
++#        -gencode=arch=compute_70,code=sm_70
++#        -gencode=arch=compute_75,code=sm_75
++#        -gencode=arch=compute_80,code=sm_80
++#    )
++#elseif(CUDAToolkit_VERSION_MAJOR EQUAL "11")
++#    set(CUDA_ARCH
++#        -gencode=arch=compute_35,code=sm_35
++#        -gencode=arch=compute_37,code=sm_37
++#        -gencode=arch=compute_50,code=sm_50
++#        -gencode=arch=compute_52,code=sm_52
++#        -gencode=arch=compute_60,code=sm_60
++#        -gencode=arch=compute_61,code=sm_61
++#        -gencode=arch=compute_70,code=sm_70
++#        -gencode=arch=compute_75,code=sm_75
++#        -gencode=arch=compute_80,code=sm_80
++#        -gencode=arch=compute_86,code=sm_86
++#    )
++#else()
++#    set(CUDA_ARCH
++#        -gencode=arch=compute_30,code=sm_30
++#        -gencode=arch=compute_35,code=sm_35
++#        -gencode=arch=compute_37,code=sm_37
++#        -gencode=arch=compute_50,code=sm_50
++#        -gencode=arch=compute_52,code=sm_52
++#        -gencode=arch=compute_60,code=sm_60
++#        -gencode=arch=compute_61,code=sm_61
++#        )
++#endif()
+
+
+ set(CUDA_OPTS