Presentations

Khyathi Vagolu presents a machine learning approach to improving HTCondor job lease timeouts by replacing a fixed timeout with a dynamically optimized value. The talk explores how Bayesian optimization can reduce unnecessary job failures and wasted computing resources while adapting to changing conditions in distributed computing environments.

Ken Judd explores how HTCondor enables large-scale climate and economic policy modeling by making complex simulations practical to run. The talk highlights how high throughput computing supports dynamic programming, climate risk analysis, and economic models used to evaluate policies such as carbon pricing.

Tom Smith shares practical improvements Brookhaven National Laboratory has made to streamline HTCondor operations, from simplifying system configuration and automation to improving monitoring and resource management. The talk highlights tools and techniques that increase efficiency, reduce operational overhead, and help optimize large-scale computing infrastructure.

Jingyan Shi presents the latest developments in INK, an interactive analysis platform that simplifies access to computing resources for high energy physics researchers. The talk highlights new workflow tools, real-time job monitoring, one-click deployment, and early efforts to integrate AI agents with HTCondor to streamline scientific computing.

Ilija Vukotic presents how AI agents and the Model Context Protocol (MCP) can help HTCondor administrators monitor systems, troubleshoot issues, and automate routine operations. The talk explores a secure, human-in-the-loop approach to integrating AI assistants into large-scale research computing infrastructure.

Ian Ross discusses the challenges AI coding agents introduce to shared HTCondor access points and explores practical strategies for using them safely. The talk examines approaches such as resource limits, guided agent behavior, trusted AI tools, and user education to help balance innovation with responsible research computing.

Matyas Selmeci presents PlacementD, a new authorization system that enables users to securely submit and manage HTCondor jobs remotely without requiring shell access to an access point. The talk covers placement tokens, remote job management, project-based authorization, and improvements to secure research computing workflows.

Benjamin FitzGerald demonstrates an HTCondor and DAGMan workflow that automatically manages dynamic input files and item-level retries for large-scale precipitation analysis. By automating file handling and recovery from missing data, the approach reduces manual intervention, improves workflow reliability, and accelerates hydrologic modeling for flood risk research.

CHTC Summer Fellows Daniella Wright and Snikitha Siddavatam present their projects on enhancing CHTC documentation and measuring throughput using a standardized workflow.

Todd Miller introduces new HTCondor capabilities that reduce redundant file transfers by reusing common files and container images across related jobs. The talk explains how these improvements lower bandwidth usage, improve efficiency, and accelerate workflows for data-intensive computing.

Kashika Mahajan presents a toolkit that gives HTCondor users an easy way to understand the health of their workloads through dashboards, runtime visualizations, resource utilization reports, and job hold analysis. The tools aggregate per-job information into actionable insights, helping researchers identify bottlenecks, optimize resource requests, and troubleshoot failed jobs more efficiently.

Marco Mambelli provides an overview of recent advances in GlideinWMS, a pilot-based workload management system that provisions distributed HTCondor resources across clusters, clouds, and HPC systems. The presentation highlights new credential management, on-demand CVMFS provisioning, expanded HPC integrations, and ongoing efforts to improve scalability and support emerging research infrastructure APIs.

Lily Grace Sheram discusses how OSPool and the Open Science Data Federation support the Trinity Observatory's search for very-high-energy neutrinos. The talk explores large-scale data analysis, simulations, and high throughput computing techniques used to process and study rare astrophysical events.

Todd Tannenbaum highlights the latest developments in the HTCondor Software Suite, previewing features coming in HTCondor v26 and showcasing improvements to monitoring, job management, metrics, data transfer, and resource provisioning. The talk covers new tools for analyzing distributed workloads, enhanced support for HPC and cloud environments, more efficient handling of shared input data, and upcoming capabilities designed to improve scalability and user experience across high throughput computing

Peter Pizzimenti presents OrangeGrid Cloud Workers, a system that expands HTCondor pools into cloud resources without changing researchers' existing workflows. The talk explores cloud bursting, storage integration, and strategies for adding on-demand computing capacity while maintaining a familiar user experience.

Mark Krenz presents the work of the OSG Security Team to help protect the research computing community from emerging cybersecurity threats. The talk covers vulnerability monitoring, threat intelligence, security coordination, and strategies for reducing risk as AI changes the cybersecurity landscape.

Cole Bollig explores how Open OnDemand can provide a browser-based interface for HTCondor, making high throughput computing more accessible through interactive applications and web-based workflows. The presentation also examines current integration challenges and highlights real-world deployments that combine Open OnDemand with HTCondor for research computing.

Greg Thain leads an interactive session where audience members try to distinguish between answers written by Todd Tannenbaum and by AI to common high throughput computing questions. The talk explores best practices for HTCondor, Pelican, and research computing while highlighting both the strengths and limitations of AI-generated technical advice.

Yuanyuan Zhang discusses how OSPool supports simulation-based inference for galaxy cluster cosmology by generating large training datasets for machine learning models. The talk explores how high throughput computing can accelerate cosmological research while bringing computing resources closer to large astronomical data collections.

Ben Tovar and Douglas Thain introduce Vine Reduce, a TaskVine framework designed to efficiently execute massive task graphs by generating work hierarchically instead of constructing the entire graph upfront. The approach dramatically reduces workflow setup time while enabling scalable, data-intensive computing for applications ranging from high-energy physics to large-scale scientific analysis.

Pierrette Dagg of Merit Network shares a statewide perspective on research computing from the vantage point of a regional research and education network (REN), and how such networks connect campuses to shared cyberinfrastructure.

Brian Bockelman explores how large language models and AI agents can make high throughput computing more accessible. The talk examines how AI-assisted tools, REST APIs, and the Model Context Protocol (MCP) can simplify HTCondor workflows while discussing the opportunities and limitations of using AI in scientific computing.

Justin Hiemstra presents new backend capabilities for the Pelican Origin, expanding support for a wider range of storage systems and improving how researchers access and share data. The talk covers backend architecture, protocol translation, caching, and ongoing work to make distributed data access more flexible and efficient.

Stephen Deems discusses community-operated cyberinfrastructure resources and how they broaden access to computing for campus researchers.

Nick Minor presents a case study on deploying Nextflow on CHTC and how AI-assisted software engineering helped overcome compatibility challenges between Nextflow and high throughput computing environments. The talk explores the benefits, limitations, and broader implications of using AI to develop research software for biology.

Marco Mascheroni discusses how the CMS Submission Infrastructure has evolved to support large-scale computing for the CMS experiment at CERN. The talk highlights improvements in resource utilization, workflow management, and HTCondor-based infrastructure as CMS prepares for the High-Luminosity Large Hadron Collider.

Steven Timm discusses the distributed computing and data management challenges facing the DUNE experiment as it prepares for next-generation neutrino research. The talk explores large-scale data movement, heterogeneous CPU and GPU workflows, and the infrastructure needed to support AI-enabled scientific computing.

Seung-Jin Sul presents JAWS, a workflow execution service that simplifies running large-scale scientific workflows across multiple computing facilities. The talk explores how JAWS uses HTCondor to automate data movement, resource management, and workflow execution for genomic research.

Tomás Cabrera discusses the workflow behind following up gravitational-wave events, from receiving alerts to identifying potential astronomical counterparts. The talk highlights the computing tools, data pipelines, and lessons learned from the GW-Multi-Messenger Astronomy DS observing campaign.

Fabio Andrijauskas discusses how the Open Science Data Federation (OSDF) integrates with the National Research Platform to support distributed data access and computing. The talk highlights Pelican deployment, data transfer, monitoring, and infrastructure for managing data across geographically distributed research resources.

Ewa Deelman explores how AI can simplify the creation of Pegasus workflows by transforming sketches, papers, existing workflows, and code into production-ready scientific workflows. The talk discusses AI-assisted workflow development, validation, and the challenges of building trustworthy AI tools for research computing.

Colin Slater presents the systems used to process every image captured by Rubin Observatory. The presentation focuses on scalable workflows, HTCondor, and the data management challenges of large-scale astronomical surveys.

Alessandra Corsi discusses the role of radio observations in following up gravitational-wave events and the opportunities they provide for multi-messenger astronomy. The talk explores the computing and data management challenges of processing growing radio datasets and highlights emerging frameworks for large-scale gravitational-wave follow-up

Gregory Daues discusses how the Rubin Observatory is using HTCondor to scale data release production for the Legacy Survey of Space and Time (LSST). The talk explores workflow management, automation, and strategies for processing millions of tasks across large distributed computing environments.

Brian Aydemir presents new features for sharing data in the Pelican Platform, including authentication, user management, and group-based access control. The talk explores how Pelican enables researchers to securely share and manage data while giving data owners greater control over permissions and collaboration.

David Schultz presents the IceCube CredMon, a custom authentication tool that automates secure credential management for HTCondor and Pelican workflows. The talk explores how the system enables reliable, automated access to scientific data while supporting large-scale distributed computing for the IceCube Neutrino Observatory.

Ian Ross presents a case study on training machine learning models across heterogeneous computing resources using OSPool and the National AI Research Resource (NAIRR). The talk explores how distributed high throughput computing can support large-scale AI training while improving access to GPU resources for scientific research.

Mark Lacy discusses how the VLA Sky Survey supports multi-messenger astronomy by providing radio observations that complement gravitational-wave, neutrino, and other astronomical events. The talk examines the computing and workflow challenges of processing large radio datasets and explains why high throughput computing is well suited to the survey.

Preston Smith of Purdue University examines how campuses can plan computing capacity as AI demand and market forces reshape campus buying power. The talk shares research on capacity planning and explores how a campus plan fits into the larger picture of state, regional, and national resource sharing.

Jason Simms shares a small-campus perspective on the research computing landscape. He discusses how non R1 campuses are utilizing HTC tools like the OSPool, and the challenges and benefits of smaller institutions utilizing HTC

Ewa Deelman from the USC Information Sciences Institute leads an interactive presentation on how the HTC community views opportunities and challenges for AI-enabled cyberinfrastructure. She discusses the CI Compass Fellowship Program (CICF), and how AI is moving into facility operations and science pipelines.

Shreya Anand discusses the computing challenges behind wide-field target-of-opportunity searches for gravitational-wave counterparts using ZTF and the Rubin Observatory. The talk covers observation scheduling, image processing, and transient filtering for real-time follow-up.

Nathan Walker discusses the computational challenges of simulating gamma-ray bursts across multiple scales. The talk explores strategies for efficiently using CPUs, GPUs, and other hardware to improve astrophysical simulations.

CHTC facilitator Danny Morales explains how his team solved AlphaFold3's core HTC challenge: routing jobs to nodes where the 750 GB reference database is already staged, rather than transferring it per job. By treating data as a schedulable resource via HTCondor ClassAds and caching alignments for reuse, they cut preprocessing by ~89% and enabled protein-protein interaction screenings at a scale previously impossible on distributed systems.

Ronda Swanson introduces the 2026 OSG David Swanson Memorial Awardee, Saloni Bhogale.

Saloni Bhogale, the 2026 David Swanson Award recipient, presents her research on legal institutions in the developing world at Throughput Computing Week 2026. Using high-throughput computing resources at UW-Madison's CHTC, she analyzed 80 million Indian judicial records to study barriers to court access, work that would have taken 15 years on a laptop. Her findings show that adding council members to village governments increases case filings by 51%, revealing a direct link between local democracy and access to justice.

Michael Coughlin (University of Minnesota - Twin Cities) surveys the present and future of gravitational-wave astronomy, from the first detections through the dawn of multi-messenger discoveries like GW170817. He details how machine learning and low-latency inference pipelines, including Aframe, DeepClean, and AMPLFI, are transforming gravitational-wave detection and parameter estimation, while brokers like BOOM tackle the flood of alerts from surveys such as ZTF and the upcoming Rubin Observatory. The talk closes with a look at near-term prospects for the field, from next-generation detectors to citizen-science efforts like GravitySpy and Kilonova Catcher.

Ved Shah explores the development of ORACLE, a hierarchical machine learning classifier for real-time astronomical event classification. The presentation highlights multimodal modeling, performance on LSST and ZTF data, and lessons from real-time deployment.

CHTC/PATh Facilitation Lead Christina Koch reflects on 13 years of research computing facilitation and how the rise of agentic AI has amplified longstanding challenges, from researchers overloading login nodes to AI-generated code producing unpredictable results. Koch notes these aren't new problems, but AI has accelerated and scaled them, pushing facilitators to strengthen researcher education, documentation, and system guardrails. She emphasizes human-centered facilitation is more essential than ever as computing environments grow more complex.

This talk explores the computing infrastructure behind real-time multi-messenger astronomy, from processing millions of telescope alerts to rapidly identifying and following up on gravitational-wave events. It also highlights how machine learning is helping classify astronomical events across multiple data sources.

The GOTO Observatory is advancing real-time astronomy by rapidly detecting and following up on gravitational wave events.Kendall Ackley shares how the GOTO Observatory combines autonomous telescopes and real-time data processing to detect and study gravitational wave counterparts

Miron Livny opens HTC26 by introducing the conference theme, Transition, Trust, and Throughput (TT&T), and reflecting on major developments across the research computing community. The talk highlights leadership transitions within the OSG Consortium, the evolution of PATh into FabAID, the growing role of the multi-messenger astronomy community at HTC26, and the importance of trusted software and strong partnerships in advancing scientific computing.

Conor Bendett shares about his work using HTC for comparative genonimcs for large public datasets. He further discusses CHTC and HTCondor and his experience: noting that there are lots of pipelining small tools; not always the easiest to manage; troubleshooting memory/disk space can be time consuming (unpredictableoutputs) and the great support from CHTC facilitators.

Aydan Bailey discussed getting started with CHTC for his research, his use of CHTC guides and Offie hours and the challenges setting up Docker image for running custom software. Bailey also dsicussed the advanges of the ResearchDrive integration, that provides a secure, shareable storage and much faster transfers between the storage location and CHTC servers.

We present the initial design and proposed implementation for a series of long-baseline, distributed inference experiments leveraging ARA --- a platform for advanced wireless research that spans approximately 500 square kilometers near Iowa State University, including campus, the City of Ames, local research and producer farms, and neighboring rural communities in central Iowa. These experiments aim to demonstrate, characterize, and evaluate the use of distributed inference for computer vision tasks in rural and remote regions where high-capacity, low-latency wireless broadband access and backhaul networks enable edge computing devices and sensors in the field to offload compute-intensive workloads to cloud and high-performance computing systems embedded throughout the edge-to-cloud continuum. We highlight the role of HTCondor as the common scheduler and workload manager used to distribute the inference workload across ARA and beyond. We also discuss some of the unique challenges in deploying HTCondor on ARA.

Bujji Selagamsetty discusses his CHTC GPU workflow. He also noted improvements to CHTC Flow, including HTChirp to poll job ad information and self-scheduling job length and device specific tuning. In his current work he asks what are the regions od 3D audio space where a. speech is more perceptible and b. noise is more distracting. Can we map this space at a fine enough granularity to create more personalized, spatial audio experiences? Selagamsetty summarizes his CHTC experience working on this project.

Ian Ross discussed the ML PATh supplement to profile the effects of training on inference on distributed, hetergeneous capacity, Ross talks about the HTCondor's Annex integration with NAIRR sites and use of some new DAG features that could simplify some things.

Amber Lim discusses how to run GPU jobs in CHTC and the OSPool, the researcher-to-AI-workflow-proficiency pipeline, and what you should consider during development.

John Peters focuses on Feature Extraction in AI workflows and how to leverage CHTC using small zips, Snakemake and caching.

Sameer D'Costa, a scientist with the Computational Biology Group at the Great Lakes Bioenergy Research Center, is investigating Zymomonas mobilis (bacteria) that is really good at turning sugar into alcohol and could be engineered for industrial use. D'Costa share his deep learning computational plan and workflow to compute complees in Z. Mobilis.

Pegasus is a widely used scientific workflow management system built on top of HTCondor DAGMan. This talk will highlight how Pegasus is deployed within the NSF ACCESS ecosystem and the NAIRR Pilot. We will cover access point deployments, including the hosted ACCESS Pegasus platform (Open OnDemand and Jupyter), workflow execution nodes in HPC environments, and a JupyterLab-based access point within the Purdue Anvil Composable Subsystem. On the execution side, we will discuss several provisioning strategies, including HTCondor Annex, custom virtual machines on the Jetstream2 cloud, simple glidein configurations for campus clusters, and a dynamically autoscaled TestPool environment designed for workflow development and testing.

Ariana Negreiro disusses the Digital Livestock Lab at the UW-Madison Dept of Animal and Dairy Sciences which focuses on research applications of ML and computer vision for farm management and genetic selection. Negreiro disucssed the data processing pipeline and the CHTC Resources (HTCondor, Pelican and DAGMAN) that they rely upon for their work.

Christina Koch, OSG Rsearcher Facilitation Lead, and Tim Cartwright, OSG Campus Coordinator, discuss how buildling the community of contributors is an inseparable aspect of providing the OSDF, OSPool and OSStore.

Irvin Lopez-Audetat discusses the Monitoring Infrastructure for Network and Computing Environment Research (MINCER) project that aims to provide a foundation for in-depth insight and analysis of distributed heterogeneous computing environments, supporting and enhancing research and education in computer and network systems. Our approach is to work in conjunction with the Open Science Grid (OSG).

Wheat, Senior Professor of Computer Science at Oral Roberts University, discusses the campus CC* awards, contributing to the OSPool and its impact on the ORU faculty and students.

NSF NCAR’s labs and programs collectively cover a breadth of research topics in Earth system science, from the effects of the Sun on Earth's atmosphere to the role of the ocean in weather and climate prediction, as well as supporting and training the next-generation of Earth system scientists. However, with the current legacy `download and analyze’ model followed by most of our remote users, we are not realizing the full research potential of NCAR’s wealth of datasets. Our goal is to integrate NCAR’s curated data collections with the OSDF data and compute fabric to broaden access capabilities. In this talk, we present progress on this collaboration and demonstrate geoscience workflows which ingest data from NCAR’s Research Data Archive using pelicanFS via OSDF caches.

Kevin Thompson from the Office of Advanced Cyberinfrastructure of the National Science Foundation discussed the Camus Cyberinfrastructure (CC*) vision. Thompson discusses the CC* Program that is Coordinated in networking, compute and storage. Thompson also discusses the contributors to the OSPool and the services of the OSDF.

Sarvani Chadalapaka discusses UC Merced's Cyberinfrastructre and Research Technologies Mission and both its contribution and use of OSG resources, noting that they chose OSG because of its alignment with CC* requirements, pre-proposal and deployment support and training and onboarding support.

Patricia Tran, bioinformatics and computational pipeline scientist, bioinformatics research support service, discusses working with big data in biology and the requirements to be scalable, flexible and use high throughput computing.

Peter Pizzimenti, Associate Director of Research Computing at Syracuse University, discusses why Syracuse invests in research computing, What it takes to support research computing and where they are going.

Join Brian Bockelman, Douglas Thain, Ewa Deelman, Manish Parashar, Miron Livny, and Peter Couvares for a panel discussion on translational computer science.

Michael Couso, a research computing support supervisor, discussed how the University of Montana became a contributor to the OSPool. Couso discussed connecting to the OSPool and opening the door to a broad community and the process of scaling up and growing outward.

CHTC Fellows discuss the work and goals of their Fellows Projects - for CHTC and Pelican

Jason Kwan presents on the use of high-throughput computing in metagenomics research, discussing how CHTC allows for large-scale searches and metagenomic assemblies that require a lot of RAM.

The OSG David Swanson award is awarded each year in memory of David Swanson to an attendee of the OSG School who has gone on to do interesting things. This year's recipient, Brandi Pessman, presents on how spiders respond to rising noise levels in cities. Using high-throughput computing, Brandi digitally reconstructed spider webs to track spider movements during web construction.

Recent technological advances have revealed an enormous diversity of lifeforms by sequencing their genomes. There are now millions of available genomes, each comprised of thousands of genes. The universe of newly discovered genes is expanding far faster than our ability to study them in the laboratory. Here, Erik Wright presents how high-throughput computing is unlocking the function of novel genes at an unfathomable scale.

Christina Koch presents on facilitation impacts at HTC25. Lead Research Computing Facilitator Christine Koch describes the facilitation services provided to researchers and ways to connect. In addition, Koch discusses PATh's role as a resource provider for NAIRR and building a data community.

Miron Livny provides the opening remarks for HTC25. Livny discusses the Center for High Throughput Computing (CHTC) vision: Distributed high throughput computing and research computing facilitation are powerful enables or scientific discovery; The value proposition of throughput computing for researchers with AI workloads, and translational (computer) science. He also discusses that building a lasting relationship with a community requires an evolving value proposition and mutual trust.

Prakriti Garg presents on using throughput computing to study the gene regulatory network using network inference and unsupervised learning

Oana Carja discusses using the OSPool and high throughput computing in the field of biological evolution, with the aim of understanding the rules that govern evolutionary processes.