The Cooperative Computing Lab

We design software that enables our collaborators to easily harness large scale distributed systems such as clusters, clouds, and grids. We perform fundamental computer science research that enables new discoveries through computing in fields such as physics, chemistry, bioinformatics, biometrics, and data mining.

All of our softwares are open source and available on GitHub. We are always eager to welcome new collaborators—whether you want to explore our software, contribute to development, or receive support. Explore our tools to see how they can power your distributed computing needs, and visit the getting help section if you need assistance.

CCL Launches Redesigned Website (Jan 06, 2026)

Open Source Software

TaskVine is our third-generation workflow system for building scalable data intensive applications that run on HPC clusters, cloud services, and other clusters.

Floability is an NSF funded research project to enable the rapid and portable deployment of notebooks expressing complex scientific workflows across a wide range of cyberinfrastructure.

Work Queue is an application framework for creating and managing dynamic manager-worker style programs that scale up to tens of thousands of machines on clusters, clouds, and grids.

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Research Projects

XGFabric : Coupling Sensor Networks and HPC Facilities with Advanced Wireless Networks for Near Real-Time Simulation of Digital Agriculture (DOE ASCR)

This project will explore the design of systems for connecting remote wireless sensor networks with high performance computing systems.

SADE: A Safety-Aware Ecosystem of Reputable sUAS

The overall goal of the project is to develop technology for safety zones that permit only trusted drones to operate in congested or sensitive airspace.

Pledge: Accelerating Data Intensive Scientific Workflows with Consistency Contracts

Expresses workflow I/O intentions using consistency contracts to enable efficient, cluster-wide storage and execution optimizations.

NBFlow: From Notebook to Workflow and Back Again (CSSI Framework)

NBFlow brings together interactive notebook technologies (Jupyter), reproducibility tools (SciUnit), and distributed workflows (TaskVine) to enable easy execution of large-scale notebook workflows on heterogeneous HPC clusters.

TaskVine: A User Level Framework for Data Intensive Scientific Applications (CSSI Element)

TaskVine is open source software for building large scale data intensive dynamic workflows that run on HPC clusters, GPU clusters, and commercial clouds.

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Community Highlights

Workshop on Harmonizing Python Workflows at IEEE e-Science 2025

We helped host the Workshop on Harmonizing Python Workflows at IEEE International Conference on e-Science on Monday, 15 Sep 2025. This workshop is one compon…

OpenTopography + EEMT + Makeflow

The OpenTopography service provides online access to geospatial data and computational tools in support of earth sciences. The Effective Energy and Mass Tra…

Analyzing Agriculture with Work Queue

The Field Scanalyzer at the University of Arizona is a massive robot that uses sensors, cameras, and GPS devices to collect vast quantities of agricultural d…

Summer REU Projects

In summer 2019, REU students TJ Dasso and Eamon Marmion worked at the CCL on large scale distributed applications. They completed the integration between th…

IceCube Flies with Parrot and CVMFS

IceCube is a neutrino detector built at the South Pole by instrumenting about a cubic kilometer of ice with 5160 light sensors. The IceCube data is analyzed …

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Latest News and Posts

Jan 15, 2026	Graduate Students Share Research and Systems Insights at SC25
Jan 06, 2026	CCL Launches Redesigned Website
Dec 17, 2025	Accelerating Coffea Workflows with Persistent Preprocessing Cache
Dec 09, 2025	Exploring Execution Strategies and Compositional Trade-Offs in the Context of Large-Scale HEP Workflows
Dec 02, 2025	TaskVine Insights - Storage Management: Depth-Aware Pruning

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Recent Publications

xGFabric: Coupling Sensor Networks and HPC Facilities with Private 5G Wireless Networks for Real-Time Digital Agriculture

Liubov Kurafeeva, Alan Subedi, Ryan Hartung, Michael Fay, Avhishek Biswas, Shantenu Jha, Ozgur O. Kilic, Chandra Krintz, Andre Merzky, Douglas Thain, Mehmet C. Vuran, and Rich Wolski

In Workshop on Extreme-Scale Experiment-in-the-Loop Computing (XLOOP) at Supercomputing, 2025

Bib PDF

@inproceedings{xgfabric-xloop-2025,
  author = {Kurafeeva, Liubov and Subedi, Alan and Hartung, Ryan and Fay, Michael and Biswas, Avhishek and Jha, Shantenu and Kilic, Ozgur O. and Krintz, Chandra and Merzky, Andre and Thain, Douglas and Vuran, Mehmet C. and Wolski, Rich},
  title = {{xGFabric: Coupling Sensor Networks and HPC Facilities with Private 5G Wireless Networks for Real-Time Digital Agriculture}},
  booktitle = {{Workshop on Extreme-Scale Experiment-in-the-Loop Computing (XLOOP) at Supercomputing}},
  year = {2025},
  cclpaperid = {1005},
  keywords = {xgfabric},
}

Backpacks for Notebooks: Enabling Containerized Notebook Workflows in Distributed Environments

Md Saiful Islam, Talha Azaz, Raza Ahmad, A D M Shahadat Hossain, Furqan Baig, Shaowen Wang, Kevin Lannon, Tanu Malik, and Douglas Thain

In IEEE Conference on eScience, 2025

Bib PDF

@inproceedings{floability-escience-2025,
  author = {Islam, Md Saiful and Azaz, Talha and Ahmad, Raza and Hossain, A D M Shahadat and Baig, Furqan and Wang, Shaowen and Lannon, Kevin and Malik, Tanu and Thain, Douglas},
  title = {{Backpacks for Notebooks: Enabling Containerized Notebook Workflows in Distributed Environments}},
  booktitle = {{IEEE Conference on eScience}},
  pages = {9},
  year = {2025},
  cclpaperid = {1003},
  keywords = {floability}
}

Liberating the Data Aware Scheduler to Achieve Locality in Layered Scientific Workflow Systems

Colin Thomas and Douglas Thain

In IEEE Conference on eScience, 2025

Bib PDF

@inproceedings{liberating-escience-2025,
  author = {Thomas, Colin and Thain, Douglas},
  title = {{Liberating the Data Aware Scheduler to Achieve Locality in Layered Scientific Workflow Systems}},
  booktitle = {{IEEE Conference on eScience}},
  pages = {9},
  year = {2025},
  cclpaperid = {1004}
}

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