{bio}[foss/2021a] OpenFold v1.0.0, colossalai v0.1.8, einops v0.4.1, OpenMM 7.5.1 (incl. AlphaFold patch) w/ Python 3.9.5 + CUDA 11.3.1

easybuild/easyconfigs/c/colossalai/colossalai-0.1.8-foss-2021a-CUDA-11.3.1.eb

@@ -0,0 +1,55 @@
+easyblock = 'PythonBundle'
+
+name = 'colossalai'
+version = '0.1.8'
+versionsuffix = '-CUDA-%(cudaver)s'
+
+homepage = 'https://colossalai.org/'
+description = """Colossal-AI: A Unified Deep Learning System for Big Model Era"""
+
+toolchain = {'name': 'foss', 'version': '2021a'}
+
+dependencies = [
+ ('Python', '3.9.5'),
+ ('CUDA', '11.3.1', '', True),
+ ('SciPy-bundle', '2021.05'),
+ ('PyTorch-Lightning', '1.5.9', versionsuffix),
+ ('torchvision', '0.11.1', versionsuffix),
+]
+
+exts_list = [
+ ('cfgv', '3.3.1', {
+ 'checksums': ['f5a830efb9ce7a445376bb66ec94c638a9787422f96264c98edc6bdeed8ab736'],
+ }),
+ ('identify', '2.5.1', {
+ 'checksums': ['3d11b16f3fe19f52039fb7e39c9c884b21cb1b586988114fbe42671f03de3e82'],
+ }),
+ ('nodeenv', '1.6.0', {
+ 'checksums': ['3ef13ff90291ba2a4a7a4ff9a979b63ffdd00a464dbe04acf0ea6471517a4c2b'],
+ }),
+ ('pre_commit', '2.19.0', {
+ 'checksums': ['4233a1e38621c87d9dda9808c6606d7e7ba0e087cd56d3fe03202a01d2919615'],
+ }),
+ ('commonmark', '0.9.1', {
+ 'checksums': ['452f9dc859be7f06631ddcb328b6919c67984aca654e5fefb3914d54691aed60'],
+ }),
+ ('rich', '12.4.4', {
+ 'checksums': ['4c586de507202505346f3e32d1363eb9ed6932f0c2f63184dea88983ff4971e2'],
+ }),
+ ('invoke', '1.7.1', {
+ 'checksums': ['7b6deaf585eee0a848205d0b8c0014b9bf6f287a8eb798818a642dff1df14b19'],
+ }),
+ ('fabric', '2.7.1', {
+ 'checksums': ['76f8fef59cf2061dbd849bbce4fe49bdd820884385004b0ca59136ac3db129e4'],
+ }),
+ (name, version, {
+ 'checksums': ['3a2cdd4dc2d8b4832fa132a0bd1102f86c38f6865d7f119018404069d35984b2'],
+ }),
+]
+
+download_dep_fail = True
+use_pip = True
+
+sanity_pip_check = True
+
+moduleclass = 'ai'

easybuild/easyconfigs/e/einops/einops-0.4.1-GCCcore-10.3.0.eb

@@ -0,0 +1,29 @@
+easyblock = 'PythonPackage'
+
+name = 'einops'
+version = '0.4.1'
+
+homepage = 'https://einops.rocks/'
+description = """
+Flexible and powerful tensor operations for readable and reliable code.
+Supports numpy, pytorch, tensorflow, jax, and others."""
+
+toolchain = {'name': 'GCCcore', 'version': '10.3.0'}
+
+sources = [SOURCE_TAR_GZ]
+checksums = ['65ede824fa54ce99ba969c61152f9948eb8cad08d5f0ca97c95e3804bafcce48']
+
+builddependencies = [
+ ('binutils', '2.36.1'),
+]
+
+dependencies = [
+ ('Python', '3.9.5'),
+]
+
+download_dep_fail = True
+use_pip = True
+
+sanity_pip_check = True
+
+moduleclass = 'math'

easybuild/easyconfigs/o/OpenFold/OpenFold-1.0.0-foss-2021a-CUDA-11.3.1.eb

@@ -0,0 +1,91 @@
+easyblock = 'PythonBundle'
+
+name = 'OpenFold'
+version = '1.0.0'
+versionsuffix = '-CUDA-%(cudaver)s'
+
+homepage = 'https://github.com/aqlaboratory/openfold'
+description = "A faithful PyTorch reproduction of DeepMind's AlphaFold 2"
+
+toolchain = {'name': 'foss', 'version': '2021a'}
+
+builddependencies = [
+ ('CMake', '3.20.1'), # required to build ninja
+]
+
+dependencies = [
+ ('Python', '3.9.5'),
+ ('CUDA', '11.3.1', '', True),
+ ('SciPy-bundle', '2021.05'),
+ ('PyYAML', '5.4.1'),
+ ('Biopython', '1.79'),
+ ('HH-suite', '3.3.0'),
+ ('HMMER', '3.3.2'),
+ ('Kalign', '3.3.1'),
+ ('UCX-CUDA', '1.10.0', versionsuffix),
+ ('cuDNN', '8.2.1.32', versionsuffix, True),
+ ('NCCL', '2.10.3', versionsuffix),
+ ('dm-tree', '0.1.6'),
+ ('einops', '0.4.1'),
+ ('colossalai', '0.1.8', versionsuffix),
+ ('scikit-build', '0.11.1'),
+ ('OpenMM', '7.5.1', '_AlphaFold'), # patched OpenMM
+]
+
+use_pip = True
+
+exts_list = [
+ ('PDBFixer', '1.7', {
+ 'source_urls': ['https://github.com/openmm/pdbfixer/archive/refs/tags/'],
+ 'sources': [{'download_filename': 'v%(version)s.tar.gz', 'filename': '%(name)s-%(version)s.tar.gz'}],
+ 'checksums': ['a0bef3c52a7bbe69a6aea5333f51f3e7d158339be5829aed19b0344bd66d4eea'],
+ }),
+ ('ninja', '1.10.2.3', {
+ 'checksums': ['e1b86ad50d4e681a7dbdff05fc23bb52cb773edb90bc428efba33fa027738408'],
+ }),
+ ('hjson', '3.0.2', {
+ 'checksums': ['2838fd7200e5839ea4516ece953f3a19892c41089f0d933ba3f68e596aacfcd5'],
+ }),
+ ('py-cpuinfo', '8.0.0', {
+ 'modulename': 'cpuinfo',
+ 'checksums': ['5f269be0e08e33fd959de96b34cd4aeeeacac014dd8305f70eb28d06de2345c5'],
+ }),
+ ('triton', version, {
+ 'source_tmpl': '%(name)s-%(version)s-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl',
+ 'checksums': ['37b8d0eb36ed7631a6f9d01bd3183f900ae7dbd9e5e40112468a3568505671dc'],
+ }),
+ ('deepspeed', '0.5.9', {
+ 'checksums': ['7c43d151b51d346a430034e77764097c4af7637217c08503291c48c37ae7d090'],
+ }),
+ ('contextlib2', '21.6.0', {
+ 'checksums': ['ab1e2bfe1d01d968e1b7e8d9023bc51ef3509bba217bb730cee3827e1ee82869'],
+ }),
+ ('ml_collections', '0.1.0', {
+ 'preinstallopts': "touch requirements.txt && touch requirements-test.txt && ",
+ 'checksums': ['59a17fcd1c140153009788517f304caaddd7a94f06690f9f0ed09987beebcf3c'],
+ }),
+ ('dllogger', version, {
+ 'source_urls': ['https://github.com/NVIDIA/dllogger/archive/refs/tags/'],
+ 'sources': [{'download_filename': 'v%(version)s.tar.gz', 'filename': '%(name)s-%(version)s.tar.gz'}],
+ 'checksums': ['43e5e3c3acf891dfe6151f7d869f3ad2424772fe57fd8dcb0a45bad06de93bf7'],
+ }),
+ (name, version, {
+ 'source_urls': ['https://github.com/aqlaboratory/openfold/archive/refs/tags/'],
+ 'sources': ['v%(version)s.tar.gz'],
+ 'checksums': ['543cb0d36a6118a60de4b4ec2f4a49ebcc965523e5b31e9ad03425de367384a7'],
+ }),
+]
+
+sanity_check_paths = {
+ 'files': ['bin/pdbfixer'],
+ 'dirs': ['lib/python%(pyshortver)s/site-packages'],
+}
+
+sanity_check_commands = [
+ "pdbfixer --help",
+ "python -c 'import openfold'",
+]
+
+sanity_pip_check = True
+
+moduleclass = 'bio'

easybuild/easyconfigs/o/OpenMM/OpenMM-7.5.1-foss-2021a_AlphaFold.eb

@@ -0,0 +1,55 @@
+easyblock = 'CMakeMake'
+
+name = 'OpenMM'
+version = '7.5.1'
+versionsuffix = '_AlphaFold'
+
+homepage = 'https://openmm.org'
+description = "OpenMM is a toolkit for molecular simulation."
+
+toolchain = {'name': 'foss', 'version': '2021a'}
+toolchainopts = {'opt': True}
+
+source_urls = ['https://github.com/openmm/openmm/archive/']
+sources = ['%(version)s.tar.gz']
+patches = [('OpenMM-%(version)s_AlphaFold.patch', 'wrappers/python')]
+checksums = [
+ 'c88d6946468a2bde2619acb834f57b859b5e114a93093cf562165612e10f4ff7',
+ '1b109dfff3af5c6aa70690bca14618612953c68840a7e64f679db7ca33c1aff6',
+]
+
+builddependencies = [
+ ('CMake', '3.20.1'),
+ ('Doxygen', '1.9.1'),
+]
+
+separate_build_dir = True
+
+dependencies = [
+ ('Python', '3.9.5'),
+ ('SciPy-bundle', '2021.05'),
+ ('SWIG', '4.0.2'),
+]
+
+runtest = """test -e ARGS="-E \'(Integrator)|(Thermostat)|(Barostat)|(Rpmd)|(Amoeba)|(HippoNonbondedForce)\'" """
+
+preinstallopts = ' export OPENMM_INCLUDE_PATH=%(installdir)s/include && '
+preinstallopts += ' export OPENMM_LIB_PATH=%(installdir)s/lib && '
+
+# required to install the python API
+installopts = ' && cd python && python setup.py build && python setup.py install --prefix=%(installdir)s'
+
+sanity_check_paths = {
+ 'files': ['lib/libOpenMM.%s' % SHLIB_EXT, 'lib/python%(pyshortver)s/site-packages/simtk/openmm/openmm.py'],
+ 'dirs': []
+}
+
+sanity_check_commands = ["python -m simtk.testInstallation"]
+
+modextrapaths = {
+ 'PYTHONPATH': 'lib/python%(pyshortver)s/site-packages',
+ 'OPENMM_INCLUDE_PATH': 'include',
+ 'OPENMM_LIB_PATH': 'lib',
+}
+
+moduleclass = 'bio'

easybuild/easyconfigs/o/OpenMM/OpenMM-7.5.1_AlphaFold.patch

@@ -0,0 +1,45 @@
+custom patch for OpenMM to use in conjunction with AlphaFold
+see https://github.com/deepmind/alphafold/blob/main/docker/openmm.patch
+
+Index: simtk/openmm/app/topology.py
+===================================================================
+--- simtk.orig/openmm/app/topology.py
++++ simtk/openmm/app/topology.py
+@@ -356,19 +356,35 @@
+ def isCyx(res):
+ names = [atom.name for atom in res._atoms]
+ return 'SG' in names and 'HG' not in names
++ # This function is used to prevent multiple di-sulfide bonds from being
++ # assigned to a given atom. This is a DeepMind modification.
++ def isDisulfideBonded(atom):
++ for b in self._bonds:
++ if (atom in b and b[0].name == 'SG' and
++ b[1].name == 'SG'):
++ return True
++
++ return False
+
+ cyx = [res for res in self.residues() if res.name == 'CYS' and isCyx(res)]
+ atomNames = [[atom.name for atom in res._atoms] for res in cyx]
+ for i in range(len(cyx)):
+ sg1 = cyx[i]._atoms[atomNames[i].index('SG')]
+ pos1 = positions[sg1.index]
++ candidate_distance, candidate_atom = 0.3*nanometers, None
+ for j in range(i):
+ sg2 = cyx[j]._atoms[atomNames[j].index('SG')]
+ pos2 = positions[sg2.index]
+ delta = [x-y for (x,y) in zip(pos1, pos2)]
+ distance = sqrt(delta[0]*delta[0] + delta[1]*delta[1] + delta[2]*delta[2])
+- if distance < 0.3*nanometers:
+- self.addBond(sg1, sg2)
++ if distance < candidate_distance and not isDisulfideBonded(sg2):
++ candidate_distance = distance
++ candidate_atom = sg2
++ # Assign bond to closest pair.
++ if candidate_atom:
++ self.addBond(sg1, candidate_atom)
++
++
+
+ class Chain(object):
+ """A Chain object represents a chain within a Topology."""