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1. WRENCH: A Framework for Simulating Workflow Management Systems

   https://doi.org/10.1109/WORKS.2018.00013  

   Casanova, Henri; Pandey, Suraj; Oeth, James; Tanaka, Ryan; Suter, Frederic; Ferreira da Silva, Rafael (October 2018, 13th Workshop on Workflows in Support of Large-Scale Science (WORKS'18))

   Scientific workflows are used routinely in numerous scientific domains, and Workflow Management Systems (WMSs) have been developed to orchestrate and optimize workflow executions on distributed platforms. WMSs are complex software systems that interact with complex software infrastructures. Most WMS research and development activities rely on empirical experiments conducted with full-fledged software stacks on actual hardware platforms. Such experiments, however, are limited to hardware and software infrastructures at hand and can be labor- and/or time-intensive. As a result, relying solely on real-world experiments impedes WMS research and development. An alternative is to conduct experiments in simulation. In this work we present WRENCH, a WMS simulation framework, whose objectives are (i) accurate and scalable simulations; and (ii) easy simulation software development. WRENCH achieves its first objective by building on the SimGrid framework. While SimGrid is recognized for the accuracy and scalability of its simulation models, it only provides low-level simulation abstractions and thus large software development efforts are required when implementing simulators of complex systems. WRENCH thus achieves its second objective by providing high-level and directly re-usable simulation abstractions on top of SimGrid. After describing and giving rationales for WRENCH’s software architecture and APIs, we present a case study in which we apply WRENCH to simulate the Pegasus production WMS. We report on ease of implementation, simulation accuracy, and simulation scalability so as to determine to which extent WRENCH achieves its two above objectives. We also draw both qualitative and quantitative comparisons with a previously proposed workflow simulator. 

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2. Bridging Concepts and Practice in eScience via Simulation-driven Engineering

   Ferreira da Silva, Rafael; Casanova, Henri; Tanaka, Ryan; Suter, Frédéric (January 2019, Workshop on Bridging from Concepts to Data and Computation for eScience (BC2DC’19), 15th International Conference on eScience (eScience))

   The CyberInfrastructure (CI) has been the object of intensive research and development in the last decade, resulting in a rich set of abstractions and interoperable software implementations that are used in production today for supporting ongoing and breakthrough scientific discoveries. A key challenge is the development of tools and application execution frameworks that are robust in current and emerging CI configurations, and that can anticipate the needs of upcoming CI applications. This paper presents WRENCH, a framework that enables simulation-driven engineering for evaluating and developing CI application execution frameworks. WRENCH provides a set of high-level simulation abstractions that serve as building blocks for developing custom simulators. These abstractions rely on the scalable and accurate simulation models that are provided by the SimGrid simulation framework. Consequently, WRENCH makes it possible to build, with minimum software development effort, simulators that that can accurately and scalably simulate a wide spectrum of large and complex CI scenarios. These simulators can then be used to evaluate and/or compare alternate platform, system, and algorithm designs, so as to drive the development of CI solutions for current and emerging applications. 

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3. Modeling Distributed Computing Infrastructures for HEP Applications

   https://doi.org/10.1051/epjconf/202429504032  

   Horzela, Maximilian; Casanova, Henri; Giffels, Manuel; Gottmann, Artur; Hofsaess, Robin; Quast, Günter; Rossi_Tisbeni, Simone; Streit, Achim; Suter, Frédéric (January 2024, EPJ Web of Conferences)

   De_Vita, R; Espinal, X; Laycock, P; Shadura, O (Ed.)

   Predicting the performance of various infrastructure design options in complex federated infrastructures with computing sites distributed over a wide area network that support a plethora of users and workflows, such as the Worldwide LHC Computing Grid (WLCG), is not trivial. Due to the complexity and size of these infrastructures, it is not feasible to deploy experimental test-beds at large scales merely for the purpose of comparing and evaluating alternate designs. An alternative is to study the behaviours of these systems using simulation. This approach has been used successfully in the past to identify efficient and practical infrastructure designs for High Energy Physics (HEP). A prominent example is the Monarc simulation framework, which was used to study the initial structure of the WLCG. New simulation capabilities are needed to simulate large-scale heterogeneous computing systems with complex networks, data access and caching patterns. A modern tool to simulate HEP workloads that execute on distributed computing infrastructures based on the SimGrid and WRENCH simulation frameworks is outlined. Studies of its accuracy and scalability are presented using HEP as a case-study. Hypothetical adjustments to prevailing computing architectures in HEP are studied providing insights into the dynamics of a part of the WLCG and candidates for improvements. 

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4. A Roadmap to Robust Science for High-throughput Applications: The Developers’ Perspective

   https://doi.org/10.1109/Cluster48925.2021.00068  

   Taufer, M.; Deelman, E.; Silva, R. Ferreira; Estrada, T.; Hall, M.; Livny, M. (September 2021, IEEE International Conference on Cluster Computing, CLUSTER 2021)

   IEEE Computer Society (Ed.)

   Scientists using the high-throughput computing (HTC) paradigm for scientific discovery rely on complex software systems and heterogeneous architectures that must deliver robust science (i.e., ensuring performance scalability in space and time; trust in technology, people, and infrastructures; and reproducible or confirmable research). Developers must overcome a variety of obstacles to pursue workflow interoperability, identify tools and libraries for robust science, port codes across different architectures, and establish trust in non-deterministic results. This poster presents recommendations to build a roadmap to overcome these challenges and enable robust science for HTC applications and workflows. The findings were collected from an international community of software developers during a Virtual World Cafe in May 2021. 

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5. Accelerating Scientific Workflows on HPC Platforms with In Situ Processing

   https://doi.org/10.1109/CCGrid54584.2022.00009  

   Do, Tu Mai; Pottier, Loic; Yildiz, Orcun; Vahi, Karan; Krawczuk, Patrycja; Peterka, Tom; Deelman, Ewa (May 2022, 2022 22nd IEEE International Symposium on Cluster, Cloud and Internet Computing (CCGrid))

   Scientific workflows drive most modern large-scale science breakthroughs by allowing scientists to define their computations as a set of jobs executed in a given order based on their data dependencies. Workflow management systems (WMSs) have become key to automating scientific workflows-executing computational jobs and orchestrating data transfers between those jobs running on complex high-performance computing (HPC) platforms. Traditionally, WMSs use files to communicate between jobs: a job writes out files that are read by other jobs. However, HPC machines face a growing gap between their storage and compute capabilities. To address that concern, the scientific community has adopted a new approach called in situ, which bypasses costly parallel filesystem I/O operations with faster in-memory or in-network communications. When using in situ approaches, communication and computations can be interleaved. In this work, we leverage the Decaf in situ dataflow framework to accelerate task-based scientific workflows managed by the Pegasus WMS, by replacing file communications with faster MPI messaging. We propose a new execution engine that uses Decaf to manage communications within a sub-workflow (i.e., set of jobs) to optimize inter-job communications. We consider two workflows in this study: (i) a synthetic workflow that benchmarks and compares file- and MPI-based communication; and (ii) a realistic bioinformatics workflow that computes mu-tational overlaps in the human genome. Experiments show that in situ communication can improve the bioinformatics workflow execution time by 22% to 30% compared with file communication. Our results motivate further opportunities and challenges for bridging traditional WMSs with in situ frameworks. 

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