THE WRENCH FRAMEWORK
Accurate, scalable, and reproducible simulations
WRENCH builds on the open-source SimGrid simulation framework for simulation accuracy (via its validated simulation models), scalability (low ratio of simulation time to simulated time, ability to run large simulations on a single computer with low compute, memory, and energy footprints), and expressivity (ability to simulate arbitrary platform, application, and execution scenarios). WRENCH provides high-level simulation abstractions on top of SimGrid to make it possible to implement simulators of complex scenarios with minimal development effort.
SIMULATION BUILDING BLOCKS
Prototype implementations of cyberinfrastructure (CI) components and underlying algorithms
SIMULATION ACCURACY
Captures the behavior of a real-world system with as little bias as possible via validated simulation models
SCALABILITY
Ability to run large simulations quickly on a single computer with low compute, memory, and energy footprints
REPRODUCIBLE RESULTS
Reproduction or repetition of published results by a party working independently using the same/different simulation models
EDUCATION
eduWRENCH provides a set of simulation-driven, self-contained, modules for teaching parallel and distributed computing. These modules span a range of proficiency levels, from college freshmen to graduate students, and for assessing the pedagogic effectiveness of simulation-drive pedagogy
In a nutshell, WRENCH makes it possible to:
- Develop in-simulation implementations of runtime systems that execute application workloads on distributed hardware platforms managed by various software services commonly known as Cyberinfrastructure (CI) services; and
- Quickly, scalably, and accurately simulate, on a single computer, arbitrary application and platform scenarios for these runtime system implementation.
RESEARCH PUBLICATIONS
Research Papers, Journal Articles, and Technical Reports
When citing WRENCH, please use the following paper. You should also actually read that paper, as it provides a recent and general overview on the framework.
H. Casanova, R. Ferreira da Silva, R. Tanaka, S. Pandey, G. Jethwani, W. Koch, S. Albrecht, J. Oeth, and F. Suter, "Developing Accurate and Scalable Simulators of Production Workflow Management Systems with WRENCH", Future Generation Computer Systems, vol. 112, p. 162-175, 2020.
@article{wrench,
title = {Developing Accurate and Scalable Simulators of Production Workflow Management Systems with WRENCH},
author = {Casanova, Henri and Ferreira da Silva, Rafael and Tanaka, Ryan and Pandey, Suraj and Jethwani, Gautam and Koch, William and Albrecht, Spencer and Oeth, James and Suter, Fr\'{e}d\'{e}ric},
journal = {Future Generation Computer Systems},
volume = {112},
number = {},
pages = {162--175},
year = {2020},
doi = {10.1016/j.future.2020.05.030}
}
On the Feasibility of Simulation-driven Portfolio Scheduling for Cyberinfrastructure Runtime Systems, H. Casanova, Y. C. Wong, L. Pottier, R. Ferreira da Silva, Workshop on Job Scheduling Strategies for Parallel Processing (JSSPP), 2022, doi:
Peachy Parallel Assignments (EduPar 2022), H. M. Bücker, H. Casanova, R. Ferreira da Silva, A. Lasserre, D. Luyen, R. Namyst, J. Schoder, P-A. Wacrenier, D. P. Bunde, 12th NSF/TCPP Workshop on Parallel and Distributed Computing Education (EduPar), 2022, doi:
Teaching Parallel and Distributed Computing Concepts in Simulation with WRENCH, H. Casanova, R. Tanaka, W. Koch, R. Ferreira da Silva, Journal of Parallel and Distributed Computing, 2021, doi: 10.1016/j.jpdc.2021.05.009
GLUME: A Strategy for Reducing Workflow Execution Times on Batch-Scheduled Platforms, E. Hataishi, P.-F. Dutot, R. Ferreira da Silva, H. Casanova, Workshop on Job Scheduling Strategies for Parallel Processing (JSSPP), 2021, doi: 10.1007/978-3-030-88224-2_11
Evaluating energy-aware scheduling algorithms for I/O-intensive scientific workflows, T. Coleman, H. Casanova, T. Gwartney, R. Ferreira da Silva, International Conference on Computational Science (ICCS), 2021, doi: 10.1007/978-3-030-77961-0_16
Peachy Parallel Assignments (EduHPC 2021), H. Casanova, R. Ferreira Da Silva, A. Gonzalez-Escribano, H. Li, Y. Torres, D. P. Bunde, 2021 IEEE/ACM Ninth Workshop on Education for High Performance Computing (EduHPC), doi: 10.1109/EduHPC54835.2021.00012
Emerging Frameworks for Advancing Scientific Workflows Research, Development, and Education, H. Casanova, E. Deelman, S. Gesing, M. Hildreth, S. Hudson, W. Koch, J. Larson, M.A. McDowell, N. Meyers, J.L. Navarro, G. Papadimitriou, R. Tanaka, I. Taylor, D. Thain, S.M. Wild, R. Filgueira, R. Ferreira da Silva, 2021 IEEE Workshop on Workflows in Support of Large-Scale Science (WORKS), doi: 10.1109/WORKS54523.2021
Peachy Parallel Assignments (EduHPC 2020), H. Casanova, R. Ferreira da Silva, A. Gonzalez-Escribano, W. Koch, Y. Torres, D. P. Bunde, 2020 IEEE/ACM Workshop on Education for High-Performance Computing (EduHPC), doi: 10.1109/EduHPC51895.2020.00012
WorkflowHub: Community Framework for Enabling Scientific Workflow Research and Development, R. Ferreira da Silva, L. Pottier, T. Coleman, E. Deelman, H. Casanova, 15th Workshop on Workflows in Support of Large-Scale Science (WORKS’20), 2020, doi: 10.1109/WORKS51914.2020.00012
Modeling the Performance of Scientific Workflow Executions on HPC Platforms with Burst Buffers, L. Pottier, R. Ferreira da Silva, H. Casanova, E. Deelman, IEEE Cluster, 2020, doi: 10.1109/CLUSTER49012.2020.00019
Developing Accurate and Scalable Simulators of Production Workflow Management Systems with WRENCH, H. Casanova, R. Ferreira da Silva, R. Tanaka, S. Pandey, G. Jethwani, W. Koch, S. Albrecht, J. Oeth, F. Suter, Future Generation Computer Systems, 2020, vol. 112, p. 162-175, doi: 10.1016/j.future.2020.05.030
Characterizing, Modeling, and Accurately Simulating Power and Energy Consumption of I/O-intensive Scientific Workflows, R. Ferreira da Silva, H. Casanova, A. Orgerie, R. Tanaka, E. Deelman, F. Suter, Journal of Computational Science, 2020, doi: 10.1016/j.jocs.2020.101157
Teaching Parallel and Distributed Computing Concepts in Simulation with WRENCH, R. Tanaka, R. Ferreira da Silva, H. Casanova, Workshop on Education for High-Performance Computing (EduHPC), 2019, doi: 10.1109/EduHPC49559.2019.00006
Bridging Concepts and Practice in eScience via Simulation-driven Engineering, R. Ferreira da Silva, H. Casanova, R. Tanaka, F. Suter, Workshop on Bridging from Concepts to Data and Computation for eScience (BC2DC’19), 15th International Conference on eScience (eScience), 2019, p. 609-614, doi: 10.1109/eScience.2019.00084
Accurately Simulating Energy Consumption of I/O-intensive Scientific Workflows, R. Ferreira da Silva, A-C. Orgerie, H. Casanova, R. Tanaka, E. Deelman, F. Suter, 2019 International Conference on Computational Science (ICCS), 2019, p. 138-152, doi: 10.1007/978-3-030-22734-0_11
WRENCH: A Framework for Simulating Workflow Management Systems, Casanova, H., Pandey, S. , Oeth, J., Tanaka, R., Suter, F., and Ferreira da Silva, R., 13th Workshop on Workflows in Support of Large-Scale Science (WORKS’18), 2018, p. 74–85, doi: 10.1109/WORKS.2018.00013
THEY USE WRENCH
Research Outcomes Enabled by WRENCH
WRENCH has enabled research in 37 research articles. These articles include research outcomes produced by our own team as well as other researchers from the workflows community.
J. McDonald, M. Horzela, F. Suter, H. Casanova, Automated Calibration of Parallel and Distributed Computing Simulators: A Case Study, 2024
J. McDonald, J. Dobbs, Y. C. Wong, R. Ferreira da Silva, H. Casanova, An exploration of online-simulation-driven portfolio scheduling in workflow management systems, 2024
J. McDonald, J. Dobbs, Y.C. Wong, R. Ferreira da Silva, H. Casanova, An exploration of online-simulation-driven portfolio scheduling in workflow management systems, 2024
Y. C. Wong, F. Suter, K. Mehta, H. Casanova, J. McDonald, Automated Calibration of a Simulator of MPI Application Executions, 2024
J. Monniot, F. Tessier, H. Casanova, G. Antoniu, Simulation of Large-Scale HPC Storage Systems: Challenges and Methodologies, 2024
P. Barredo, J. Puente, Precise makespan optimization via hybrid genetic algorithm for scientific workflow scheduling problem, 2023
M. Horzela, H. Casanova, M. Giffels, A. Gottmann, R. Hofsaess, G. Quast, S. Rossi Tisbeni, A. Streit, F. Suter, Modelling Distributed Heterogeneous Computing Infrastructures for HEP Applications, 2023
T. N'Takpé, J. E. Gnimassoun, S. Oumtanaga, F. Suter, Data-aware and simulation-driven planning of scientific workflows on IaaS clouds, 2022
T. Coleman, H. Casanova, L. Pottier, M. Kaushik, E. Deelman, R. Ferreira da Silva, WfCommons: A Framework for Enabling Scientific Workflow Research and Development, 2022
H. M. Bücker, H. Casanova, R. Ferreira da Silva, A. Lasserre, D. Luyen, R. Namyst, J. Schoder, P-A. Wacrenier, D. P. Bunde, Peachy Parallel Assignments (EduPar 2022), 2022
H. Casanova, Y. C. Wong, L. Pottier, R. Ferreira da Silva, On the Feasibility of Simulation-driven Portfolio Scheduling for Cyberinfrastructure Runtime Systems, 2022
T.M.A. Do, L. Pottier, R. Ferreira da Silva, F. Suter, S. Caino-Lores, M. Taufer, E. Deelman, Co-scheduling Ensembles of In Situ Workflows, 2022
A. Losser, J. Witzke, F. Schintke, B. Scheuermann, BottleMod: Modeling Data Flows and Tasks for Fast Bottleneck Analysis, 2022
P. Barredo, J. Puente, Robust Makespan Optimization Via Genetic Algorithms On the Scientific Workflow Scheduling Problem, 2022
T. Coleman, H. Casanova, T. Gwartney, R. Ferreira da Silva, Evaluating energy-aware scheduling algorithms for I/O-intensive scientific workflows, 2021
E. Hataishi, P-F. Dutot, R. Ferreira da Silva, H. Casanova, GLUME: A Strategy for Reducing Workflow Execution Times on Batch-Scheduled Platforms, 2021
H. Casanova, R. Tanaka, Koch, William, R. Ferreira da Silva, Teaching Parallel and Distributed Computing Concepts in Simulation with WRENCH, 2021
T. Coleman, H. Casanova, R. Ferreira da Silva, WfChef: Automated Generation of Accurate Scientific Workflow Generators, 2021
H-D. Do, V. Hayot-Sasson, R. Ferreira da Silva, C. Steele, H. Casanova, T. Glatard, Modeling the Linux page cache for accurate simulation of data-intensive applications, 2021
Y. Wang, K. T. Cheng, Traffic-Adaptive Power Reconfiguration for Energy-Efficient and Energy-Proportional Optical Interconnects, 2021
H. Casanova, E. Deelman, S. Gesing, M. Hildreth, S. Hudson, W. Koch, J. Larson, M.A. McDowell, N. Meyers, J-L. Navarro, G. Papadimitriou, R. Tanaka, I. Taylor, D. Thain, S.M. Wild, R. Filgueira, R. Ferreira da Silva, Emerging Frameworks for Advancing Scientific Workflows Research, Development, and Education, 2021
R. Ferreira da Silva, H. Casanova, A-C. Orgerie, R. Tanaka, E. Deelman, F. Suter, Characterizing, Modeling, and Accurately Simulating Power and Energy Consumption of I/O-intensive Scientific Workflows, 2020
J. E. Gnimassoun, T. N'Takpe, G. H. F. Diedie, S. Oumtanaga, A Workflow Scheduling Algorithm for Reducing Data Transfers in Cloud IaaS, 2020
E. Hataishi, Efficient Execution of Scientific Workflows on Batch-Scheduled Clusters, 2020
L. Pottier, R. Ferreira da Silva, H. Casanova, E. Deelman, Modeling the Performance of Scientific Workflow Executions on HPC Platforms with Burst Buffers, 2020
R. Ferreira da Silva, L. Pottier, T. Coleman, E. Deelman, H. Casanova, WorkflowHub: Community Framework for Enabling Scientific Workflow Research and Development, 2020
H. Casanova, R. Ferreira da Silva, A. Gonzalez-Escribano, W. Koch, Y. Torres, D. P. Bunde, Peachy Parallel Assignments (EduHPC 2020), 2020
R. Ferreira da Silva, R. Filgueira, E. Deelman, E. Pairo-Castineira, I. M. Overton, M. Atkinson, Using Simple PID-inspired Controllers for Online Resilient Resource Management of Distributed Scientific Workflows, 2019
R. Ferreira da Silva, R. Mayani, Y. Shi, A. R. Kemanian, M. Rynge, E. Deelman, Empowering Agroecosystem Modeling with HTC Scientific Workflows: The Cycles Model Use Case, 2019
R. Ferreira da Silva, A-C. Orgerie, H. Casanova, R. Tanaka, E. Deelman, F. Suter, Accurately Simulating Energy Consumption of I/O-intensive Scientific Workflows, 2019
R. Ferreira da Silva, H. Casanova, R. Tanaka, F. Suter, Bridging Concepts and Practice in eScience via Simulation-driven Engineering, 2019
R. Tanaka, R. Ferreira da Silva, H. Casanova, Teaching Parallel and Distributed Computing Concepts in Simulation with WRENCH, 2019
H. Casanova, A. Legrand, M. Quinson, F. Suter, SMPI Courseware: Teaching Distributed-Memory Computing with MPI in Simulation, 2018
WHO ARE WE?
ABOUT
WRENCH is open-source software distributed under the LGPLV3 license
WRENCH is mainly developed by a collaborative team from the University of Hawai'i at Mãnoa (UHM), the Oak Ridge National Laboratory (ORNL), and the University of Southern California (USC).
PREVIOUS CONTRIBUTORS
DEV'S CORNER
Best practices and collaborative insights for developing and enhancing the WRENCH simulation framework
WRENCH's source code is available on GitHub. Our preferred channel to report a bug or request a feature is via WRENCH's Github Issues Track.
You can also reach the WRENCH team via our support email at support@wrench-project.org.
JOIN US ON SLACK
Connect with the WRENCH community on Slack to collaborate with peers, share your experiences, and get real-time support and updates on the WRENCH simulation framework
The WfCommons project offers a collection of workflow traces and tools for generating synthetic yet realistic workflow instances, seamlessly compatible with simulators developed using the WRENCH framework
Latest Unstable Version
If you want to use the latest unstable version, that will contain brand-new features and can achieve up-to-date performances (but may also contain bugs as the stabilization work is still underway), you may consider retrieving the latest unstable version.
git clone https://github.com/wrench-project/wrench.git