A Terminology for Scientific Workflow Systems
The term scientific workflow has evolved over the last two decades to encompass a broad range of compositions of interdependent compute tasks and data movements. It has also become an umbrella...
Reproducing GW150914: the first observation of gravitational waves from a binary black hole merger
In 2016, LIGO and Virgo announced the first observation of gravitational waves from a binary black hole merger, known as GW150914. To establish the confidence of this detection, large-scale...
Evaluating the Efficacy of LLM-Based Reasoning for Multiobjective HPC Job Scheduling
High-Performance Computing (HPC) job scheduling involves balancing conflicting objectives such as minimizing makespan, reducing wait times, optimizing resource use, and ensuring fairness....
Large Language Models for Anomaly Detection in Computational Workflows: from Supervised Fine-Tuning to In-Context Learning
Anomaly detection in computational workflows is critical for ensuring system reliability and security. However, traditional rule-based methods struggle to detect novel anomalies. This paper...
WfCommons: A Framework for Enabling Scientific Workflow Research and Development
Scientific workflows are a cornerstone of modern scientific computing. They are used to describe complex computational applications that require efficient and robust management of large volumes of...
Reproducibility of the First Image of a Black Hole in the Galaxy M87 from the Event Horizon Telescope (EHT) Collaboration
This paper presents an interdisciplinary effort aiming to develop and share sustainable knowledge necessary to analyze, understand, and use published scientific results to advance reproducibility...
Workflows Community Summit: Bringing the Scientific Workflows Community Together
Scientific workflows have been used almost universally across scientific domains, and have underpinned some of the most significant discoveries of the past several decades. Many of these workflows...
Self-supervised Learning for Anomaly Detection in Computational Workflows
Anomaly detection is the task of identifying abnormal behavior of a system. Anomaly detection in computational workflows is of special interest because of its wide implications in various domains...
WorkflowHub: Community Framework for Enabling Scientific Workflow Research and Development -- Technical Report
Scientific workflows are a cornerstone of modern scientific computing. They are used to describe complex computational applications that require efficient and robust management of large volumes of...
Mining Scientific Workflows for Anomalous Data Transfers
Modern scientific workflows are data-driven and are often executed on distributed, heterogeneous, high-performance computing infrastructures. Anomalies and failures in the workflow execution cause...
Serverless Containers -- rising viable approach to Scientific Workflows
Increasing popularity of the serverless computing approach has led to the emergence of new cloud infrastructures working in Container-as-a-Service (CaaS) model like AWS Fargate, Google Cloud Run,...
Co-scheduling Ensembles of In Situ Workflows
Molecular dynamics (MD) simulations are widely used to study large-scale molecular systems. HPC systems are ideal platforms to run these studies, however, reaching the necessary simulation...
The Workflow Trace Archive: Open-Access Data from Public and Private Computing Infrastructures -- Technical Report
Realistic, relevant, and reproducible experiments often need input traces collected from real-world environments. We focus in this work on traces of workflows---common in datacenters, clouds, and...
Data Integrity Error Localization in Networked Systems with Missing Data
Most recent network failure diagnosis systems focused on data center networks where complex measurement systems can be deployed to derive routing information and ensure network coverage in order...
Custom Execution Environments with Containers in Pegasus-enabled Scientific Workflows
Science reproducibility is a cornerstone feature in scientific workflows. In most cases, this has been implemented as a way to exactly reproduce the computational steps taken to reach the final...
Blueprint: Cyberinfrastructure Center of Excellence
In 2018, NSF funded an effort to pilot a Cyberinfrastructure Center of Excellence (CI CoE or Center) that would serve the cyberinfrastructure (CI) needs of the NSF Major Facilities (MFs) and large...
Applicability study of the PRIMAD model to LIGO gravitational wave search workflows
The PRIMAD model with its six components (i.e., Platform, Research Objective, Implementation, Methods, Actors, and Data), provides an abstract taxonomy to represent computational experiments and...
Performance-Feedback Autoscaling with Budget Constraints for Cloud-based Workloads of Workflows
The growing popularity of workflows in the cloud domain promoted the development of sophisticated autoscaling policies that allow automatic allocation and deallocation of resources. However, many...