AWE - Accelerated Weighted Ensemble

Accelerated Weighted Ensemble or AWE package provides a Python library for adaptive sampling of molecular dynamics. The framework decomposes the resampling computations and the molecular dynamics simulations into tasks that are dispatched to Work Queue for distribution and execution across allocated resources.

To use AWE, you write a Work Queue program using calls to the adpative sampler module. Then, run the work_queue_worker program on as many machines as you can access. You can start them manually, run them on the cloud, or submit them to systems like Condor or SGE. AWE will organize the machines into a workforce that, under the right conditions, can speed up protein folding by a hundred fold.

The output of AWE has been validated on the included Alanine Dipeptide protein and the WW domain dataset listed below.

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Sample Data

Publications

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Badi Abdul-Wahid, Haoyun Feng, Dinesh Rajan, Ronan Costaouec, Eric Darve, Douglas Thain, and Jesus A. Izaguirre, AWE-WQ: Fast-Forwarding Molecular Dynamics using the Accelerated Weighted Ensemble, Journal of Chemical Information and Modeling, 54(10), pages 3033-3043, September, 2014. DOI: 10.1021/ci500321g

Michael Albrecht, Dinesh Rajan, Douglas Thain, Making Work Queue Cluster-Friendly for Data Intensive Scientific Applications, IEEE International Conference on Cluster Computing, September, 2013. DOI: 10.1109/CLUSTER.2013.6702628

Badi Abdul-Wahid, Li Yu, Dinesh Rajan, Haoyun Feng, Eric Darve, Douglas Thain, Jesus A. Izaguirre, Folding Proteins at 500 ns/hour with Work Queue, 8th IEEE International Conference on eScience (eScience 2012), October, 2012. DOI: 10.1109/eScience.2012.6404429

Peter Bui, Dinesh Rajan, Badi Abdul-Wahid, Jesus Izaguirre, Douglas Thain, Work Queue + Python: A Framework For Scalable Scientific Ensemble Applications, Workshop on Python for High Performance and Scientific Computing (PyHPC) at the ACM/IEEE International Conference for High Performance Computing, Networking, Storage, and Analysis (Supercomputing) , November, 2011.