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Revisions №62002

branch: master 「№62002」
Commited by: Rocco Moretti
GitHub commit link: 「28b344ef7da98efe」 「№6353」
Difference from previous tested commit:  code diff
Commit date: 2023-04-25 12:12:13
linux.clang linux.gcc linux.srlz mac.clang
debug
release
unit
linux.clang.cxx11thread.serialization.python37.PyRosetta.unit mac.clang.python38.PyRosetta.unit mpi mpi.serialization build.header build.levels build.ninja_debug beautification code_quality.cppcheck code_quality.merge_size serialization code_quality.submodule_regression integration.mpi integration.release_debug integration.tensorflow integration.thread integration performance profile release.PyRosetta.MinSizeRel release.PyRosetta.Release scientific.ligand_scoring_ranking scientific.mp_f19_sequence_recovery linux.clang.score linux.gcc.score mac.clang.score linux.scripts.pyrosetta scripts.rosetta.parse scripts.rosetta.validate scripts.rosetta.verify util.apps windows.build.debug windows.build.release

Merge pull request #6353 from RosettaCommons/roccomoretti/speed_VDDistanceMatrix Speed up NBR distance calculation. It looks like the slow bit of loading types from the Chemical Components Dictionary is the find_nbr_dist() calc. The slow bit looks to be data structure access in the Floyd-Warshall. Right now we're using a map of maps. If we can use compact data storage (and integer indexes), we can speed this up greatly. The find_nbr_dist() function gets ~50 times faster, though given the total time we spend in it, the overall speedup due to this fix is probably ~1% at most (depending on how many CCD components you have.)

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Test: linux.gcc.mpi.serialization.integration.mpi

Failed sub-tests (click for more details):
replica_docking
Test: mac.clang.python39.integration

Failed sub-tests (click for more details):
per_residue_solvent_exposure
Test: mac.clang.python311.release.PyRosetta.MinSizeRel

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Test: mac.clang.python311.release.PyRosetta.Release

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Test: ubuntu-20.04.clang.python36.scientific.mp_f19_sequence_recovery

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