About • Prerequisites • Dependencies • Installation • Publications • Copyright and License
The project's harnessed knowledge of molecular structures' transformations at runtime can be used to steer simulations to more promising areas of the simulation space, identify the data that should be written to congested parallel file systems, and index generated data for retrieval and post-simulation analysis. Supported by this knowledge, molecular dynamics workflows such as replica exchange simulations, Markov state models, and the string method with swarms of trajectories can be executed from the outside (i.e., without reengineering the molecular dynamics code)
In order to use this package, your system should have the following installed:
- C++11
- cmake
- boost
- python3
(Optional) To use the built-in analysis library, it is required to install:
- mdtraj
- freud
The framework is also built on top the following third-party libraries:
- Dataspaces
- Decaf (optional)
We also use Catch2 as a test framework.
Here is the extensive installation instructions. Please make sure the all the prerequisites are satisfied before proceeding the following steps. Make sure you are using ssh with GitHub and you have gcc compiler in your system.
- Clone the source code from this repository
git clone --recursive [email protected]:Analytics4MD/A4MD.git a4md
- Build A4MD package
cd a4md
. setup_deps.sh
The execution of previous script should create a folder called a4md-test in your home directory. This folder includes the binaries and examples to test A4MD.
With all the installation process we created a sample workflow, which consists of two consumers and two producers. To test this follow next steps
cd ~/a4md-test/examples/sample_workflow/
sh local.dspaces.prod_con.sh
There are many things that can be customized in this script, e.g. the number of consumers, producers, and their execution scripts.
Number of ingesters - NWRITERS
Ratio - NREADERS_PER_WRITER
Number of consumers - NREADERS=$((NWRITERS*$NREADERS_PER_WRITER ))
Number of producer processes - NP_WRITER
Number of consumer processes - NP_READER
Lock type - LOCK
Number of DataSpaces servers - NSERVERS
Number of steps - NSTEPS
Window of frames to read - WINDOW
Number of atoms - NATOMS
Delay time - DELAY
To build additional data transport layer based on Decaf, specify Decaf installation directory in the install_a4md.sh file as follows :
-Ddtl_decaf=on -DDECAF_PREFIX=${DECAF_ROOT}
Marquez, Jack, Michel A. Cuendet, Silvina Caino-Lores, Trilce Estrada, Ewa Deelman, Harel Weinstein, and Michela Taufer. Increasing the Efficiency of Ensemble Molecular Dynamics Simulations with Termination of Unproductive Trajectories Identified at Runtime. The Journal of Physical Chemistry A (2025).
Harshita Sahni, Hector Carrillo-Cabada, Ekaterina Kots, Silvina Caino-Lores, Jack Marquez, Ewa Deelman, Michel Cuendet Harel Weinstein, Michela Taufer, and Trilce Estrada. Online Boosted Gaussian Learners for in-situ Detection and Characterization of Protein Folding States in Molecular Dynamics Simulations. In Proceedings of the 19th IEEE International Conference on e-Science (eScience) (2023).
Silvina Caino-Lores, Michel A. Cuendet, Jack Marquez* Trilce Estrada, Ewa Deelman, Harel Weinstein, and Michela Taufer. Runtime Steering of Molecular Dynamics Simulations Through In Situ Analysis and Annotation of Collective Variables. In Proceedings of Platform for Advanced Scientific Computing (PASC) Conference (2023).
Tu Mai Anh Do, Lo ̈ıc Pottier, Rafael Ferreira da Silva, Silvina Ca ́ıno-Lores, Michela Taufer, and Ewa Deelman. Performance Assessment of Ensembles of In Situ Workflows under Re- source Constraints. Journal of Concurrency and Computation: Practice and Experience (CCPE). (2023).
Silvina Caino-Lores, Michel Cuendet, Trilce Estrada, Ewa Deelman, Harel Weinstein, and Taufer, Michela. High-Throughput In-Situ Workflows for Ensemble Molecular Dynamics. In Proceedings of the 18th IEEE International Conference on e-Science (eScience) (2022).
Hector Carrillo-Cabada, Jeremy Benson, Asghar Razavi, Brianna Mulligan, Michel A. Cuendet, Harel Weinstein, Michela Taufer, and Trilce Estrada. A Graphic Encoding Method for Quantitative Classification of Protein Structure and Representation of Conformational Changes IEEE/ACM Transactions on Computational Biology and Bioinformatics (IEEE/ACM TCBC). (2020). [link]
Tu Mai Anh Do, Loic Pottier, Stephen Thomas, Rafael Ferreira da Silva, Michel A. Cuendet, Harel Weinstein, Trilce Estrada, Michela Taufer, and Ewa Deelman. A Novel Metric to Evaluate In Situ Workflows In Proceedings of the International Conference on Computational Science (ICCS), pp. 1 – 14. (2020). [link]
Michela Taufer, Trilce Estrada, and Travis Johnston. A Survey of Algorithms for Transforming Molecular Dynamics Data into Metadata for In Situ Analytics based on Machine Learning Methods Issue of Philosophical Transactions A., 378(2166):1-11. (2020). [link]
Copyright (c) 2022, Global Computing Lab
A4MD is distributed under terms of the Apache License, Version 2.0 with LLVM Exceptions.
See LICENSE for more details.
XSEDE -- This research was supported by the National Science Foundation (NSF) under grant numbers 1741057, 1841758, 2138811 and 2223704; the Oak Ridge Leadership Computing Facility under allocation CSC427; the Extreme Science and Engineering Discovery Environment (XSEDE) under allocation TG-CIS200053; and IBM through a Shared University Research Award.