Projects 11723-25 (GPU, Core21, Linux only) to ADVANCED
Posted: Sun Sep 09, 2018 11:49 pm
Projects 11723-25 now in ADVANCED!
Stats:
11723:
# atoms: 6578
credit: 8448
k-factor: 0.75
timeout: 7d
deadline: 10d
precision: mixed
11724:
# atoms: 7974
credit: 10363
k-factor: 0.75
timeout: 7d
deadline: 10d
precision: mixed
11725:
# atoms: 7976
credit: 10656
k-factor: 0.75
timeout: 7d
deadline: 10d
precision: mixed
Due to inconsistent GPU usage on Windows with these small no. of atoms projects, they are Linux only.
Projects 11723-25 are performing calculations in the context of the SAMPL6 SAMPLing challenge to test the accuracy and the efficiency of state-of-the-art algorithms for the prediction of the binding free energy between a ligand and a receptor. These methods are of general interest as they have the potential to guide and speed up the development of novel inhibitors that are effective against an arbitrary therapeutic target. This data will establish a reference that will be fundamental to benchmark, analyze, and push forward the performance of current methodologies that are being developed to solve this general problem. Thanks folks!
Stats:
11723:
# atoms: 6578
credit: 8448
k-factor: 0.75
timeout: 7d
deadline: 10d
precision: mixed
11724:
# atoms: 7974
credit: 10363
k-factor: 0.75
timeout: 7d
deadline: 10d
precision: mixed
11725:
# atoms: 7976
credit: 10656
k-factor: 0.75
timeout: 7d
deadline: 10d
precision: mixed
Due to inconsistent GPU usage on Windows with these small no. of atoms projects, they are Linux only.
Projects 11723-25 are performing calculations in the context of the SAMPL6 SAMPLing challenge to test the accuracy and the efficiency of state-of-the-art algorithms for the prediction of the binding free energy between a ligand and a receptor. These methods are of general interest as they have the potential to guide and speed up the development of novel inhibitors that are effective against an arbitrary therapeutic target. This data will establish a reference that will be fundamental to benchmark, analyze, and push forward the performance of current methodologies that are being developed to solve this general problem. Thanks folks!