Most recent first

  1. Scaling deep learning for cancer with advanced workflow storage integration
    Justin M. Wozniak, Philip E. Davis, Tong Shu, Jonathan Ozik, Nicholson Collier, Manish Parashar, Ian Foster, Thomas Brettin, and Rick Stevens.
    Proc. Machine Learning in High Performance Computing Environments (MLHPC) at SC 2018.

  2. CANDLE/Supervisor: A workflow framework for machine learning applied to cancer research
    Justin M. Wozniak, Rajeev Jain, Prasanna Balaprakash, Jonathan Ozik, Nicholson Collier, John Bauer, Fangfang Xia, Thomas Brettin, Rick Stevens, Jamaludin Mohd-Yusof, Cristina Garcia Cardona, Brian Van Essen, and Matthew Baughman.
    BMC Bioinformatics, accepted for 2018.

  3. The relation of local order to material properties in relaxor ferroelectrics
    Matthew J. Krogstad, Peter M. Gehring, Stephan Rosenkranz, Raymond Osborn, Feng Ye, Yaohua Liu, Jacob P. C. Ruff, W. Chen, Justin M. Wozniak, Haosu Luo, Omar Chmaissem, Zuo-Guang Ye, and Daniel Phelan.
    Nature Materials 17, 2018.

  4. Extreme-scale dynamic exploration of a distributed agent-based model with the EMEWS framework
    Jonathan Ozik, Nicholson T. Collier, Justin M. Wozniak, Charles Macal, and Gary An.
    IEEE Transactions on Computational Social Systems 5(3), 2018.

  5. Auxetic metamaterials from disordered networks
    Daniel R. Reid, Nidhi Pashine, Justin M. Wozniak, Heinrich Jaeger, Andrea Liu, Sidney Nagel, and Juan de~Pablo.
    Proceedings of the National Academy of Sciences, 2018.

  6. Launching MPI applications inside MPI applications
    Matthieu Dorier, Justin M. Wozniak, and Robert Ross.
    Proc. WORKS @ SC 2017.
    [PDF]

  7. CANDLE/Supervisor: A workflow framework for machine learning applied to cancer research
    Justin M. Wozniak, Rajeev Jain, Prasanna Balaprakash, Jonathan Ozik, Nicholson Collier, John Bauer, Fangfang Xia, Thomas Brettin, Rick Stevens, Jamaludin Mohd-Yusof, Cristina Garcia Cardona, Brian Van Essen, and Matthew Baughman.
    Proc. Computational Approaches for Cancer @ SC 2017.
    [PDF]

  8. High-throughput cancer hypothesis testing with an integrated PhysiCell-EMEWS workflow
    Jonathan Ozik, Nicholas Collier, Justin M. Wozniak, Charles Macal, Chase Cockrell, Samuel H. Friedman, Ahmadreza Ghaffarizadeh, Randy Heiland, Gary An, and Paul Macklin.
    Proc. Computational Approaches for Cancer @ SC 2017.
    [PDF]

  9. Computing just what you need: Online data analysis and reduction at extreme scales
    Ian Foster, Mark Ainsworth, Bryce Allen, Julie Bessac, Franck Cappello, Jong Youl Choi, Emil Constantinescu, Philip E. Davis, Sheng Di, Wendy Di, Hanqi Guo, Scott Klasky, Kerstin Kleese Van Dam, Tahsin Kurc, Qing Liu, Abid Malik, Kshitij Mehta, Klaus Mueller, Todd Munson, George Ostouchov, Manish Parashar, Tom Peterka, Line Pouchard, Dingwen Tao, Ozan Tugluk, Stefan Wild, Matthew Wolf, Justin M. Wozniak, Wei Xu, and Shinjae Yoo.
    Proc. EuroPar 2017.
    [PDF]

  10. High Performance Machine Learning and Evolutionary Computing to Develop Personalized Therapeutics
    Chase Cockrell, Jonathan Ozik, Nick Collier, Justin Wozniak, and Gary An.
    University of Chicago MindBytes Posters 2017. (Best poster, scalability and performance.)
    Poster: [PDF]

  11. Streaming supercomputing needs workflow-enabled programming-in-the-large
    Justin M. Wozniak, Jonathan Ozik, Daniel S. Katz, and Michael Wilde.
    Workshop on a Future Online Analysis Platform 2017.

  12. Experimental evaluation of a flexible I/O architecture for accelerating workflow engines in ultrascale environments
    Francisco Rodrigo Duro, Javier Garcia Blas, Florin Isaila, Jesus Carretero, Justin M. Wozniak, and Robert Ross.
    Parallel Computing 61, 2017.
    [PDF] [DOI]

  13. From desktop to large-scale model exploration with Swift/T
    Jonathan Ozik, Nicholson Collier, and Justin M. Wozniak.
    Proc. Winter Simulation Conference 2016.
    [PDF]

  14. High performance model exploration of mutation patterns in an agent-based model of colorectal cancer
    Jonathan Ozik, Nicholson Collier, Justin M. Wozniak, Charles Macal, Chase Cockrell, Melinda Stack, and Gary An.
    Computational Approaches for Cancer Workshop @ SC 2016. (Best paper.)
    [PDF]

  15. High performance calibration of a colorectal cancer natural history model with Incremental Mixture Importance Sampling
    Jonathan Ozik, Nicholson Collier, Justin M. Wozniak, Carolyn Rutter, and Jessica Hwang.
    Computational Approaches for Cancer Workshop at SC 2016.
    [PDF]

  16. Challenges and opportunities for dataflow processing on exascale computers
    Justin M. Wozniak, Michael Wilde, and Ian T. Foster.
    Proc. Data-Flow Execution Models for Extreme-Scale Computing at PACT 2016.
    [PDF]

  17. Flexible data-aware scheduling for workflows over an in-memory object store
    Francisco Rodrigo Duro, Javier Garcia Blas, Florin Isaila, Justin M. Wozniak, Jesus Carretero, and Robert Ross.
    Proc. CCGrid 2016.

  18. Modeling diffuse scattering using first-principles based methods
    Anh Ngo, Justin M. Wozniak, Jonathan Morris, Stephan Rosenkranz, Raymond Osborn, and Peter Zapol.
    Proc. Materials Research Society Fall Meeting 2015.
    Abstract: [TXT]

  19. Integrating big data tools for X-ray science
    Justin M. Wozniak.
    Talk at Joint Laboratory for Extreme-Scale Computing Workshop 2015.

  20. Many resident task computing in support of dynamic ensemble computations
    Jonathan Ozik, Nicholson Collier, and Justin M. Wozniak.
    Proc. MTAGS at SC 2015.
    [PDF]

  21. Lessons learned from building in situ coupling frameworks
    Matthieu Dorier, Matthieu Dreher, Tom Peterka, Justin M. Wozniak, Gabriel Antoniu, and Bruno Raffin.
    Proc. In Situ Infrastructures for Enabling Extreme-scale Analysis and Visualization @ SC 2015.
    [PDF]

  22. Interlanguage parallel scripting for distributed-memory scientific computing
    Justin M. Wozniak, Timothy G. Armstrong, Ketan C. Maheshwari, Daniel S. Katz, Michael Wilde, and Ian T. Foster.
    Proc. WORKS @ SC 2015.
    [PDF]

  23. Swift: Extreme-scale, implicitly parallel scripting
    Timothy G. Armstrong, Justin M. Wozniak, Michael Wilde, and Ian T. Foster.
    In: Programming Models for Parallel Computing,2015.
    [PDF]

  24. Swift: Parallel scripting for simulation ensembles
    Justin M. Wozniak.
    ExMatEx all-hands meeting 2015.

  25. Accelerating the experimental feedback loop: Data streams at the APS
    Ian Foster, Tekin Bicer, Raj Kettimuthu, Michael Wilde, Justin M. Wozniak, Francesco de Carlo, Ben Blaiszik, Kyle Chard, and Ray Osborn.
    Proc. STREAM 2015.
    [PDF]

  26. Big data tools for light source science
    Justin M. Wozniak.
    Talk at Cornell High Energy Synchrotron Source 2015.

  27. Swift/T: Dataflow composition of Tcl scripts for petascale computing
    Justin M. Wozniak, Timothy G. Armstrong, Michael Wilde, and Ian Foster.
    Proc. Annual Tcl/Tk Conference 2015.
    [PDF] Slides: [PPTX]

  28. Porting ordinary applications to Blue Gene/Q supercomputers
    Ketan Maheshwari, Justin Wozniak, Timothy Armstrong, Daniel S. Katz, T. Andrew Binkowski, Xiaoliang Zhong, Olle Heinonen, Dmitry Karpeyev, and Michael Wilde.
    Proc. eScience 2015.
    [PDF]

  29. Single crystal diffuse scattering: Beyond the workflow
    Ray Osborn et al.
    APS Users Meeting 2015.
    Slides: [PPTX]

  30. Toward interlanguage parallel scripting for distributed-memory scientific computing
    Justin M. Wozniak, Timothy G. Armstrong, Ketan C. Maheshwari, Daniel S. Katz, Michael Wilde, and Ian T. Foster.
    Proc. CLUSTER 2015.

  31. Swift parallel scripting for fast, productive beamline data analysis
    Hemant Sharma, Justin M. Wozniak, Jun Park, Guy Jennings, Ian Foster, Jonathan Almer, Raymond Osborn, and Michael Wilde.
    APS Users Meeting 2015.

  32. Implicitly parallel functional dataflow for DOE science workflows
    Daniel S. Katz, Michael Wilde, and Justin M. Wozniak.
    Proc. Workshop on the Future of Scientific Workflows 2015.
    [PDF]

  33. Workflows at experimental facilities: Use cases from the Advanced Photon Source
    Ian Foster, Tekin Bicer, Raj Kettimuthu, Michael Wilde, Justin M. Wozniak, Francesco de Carlo, Ben Blaiszik, Kyle Chard, Francesco de Carlo, and Ray Osborn.
    Proc. Workshop on the Future of Scientific Workflows 2015.
    [PDF]

  34. Big data staging with MPI-IO for interactive X-ray science
    Justin M. Wozniak, Hemant Sharma, Timothy G. Armstrong, Michael Wilde, Jonathan D. Almer, and Ian Foster.
    Proc. Big Data Computing 2014.
    [PDF] Slides: [PDF]

  35. Exploiting data locality in Swift/T workflows using Hercules
    Francisco Rodrigo Duro, Javier Garcia Blas, Florin Isaila, Jesus Carretero, Justin M. Wozniak, and Robert Ross.
    Proc. NESUS Workshop 2014.
    [PDF]

  36. Case studies in dataflow composition of scalable high performance applications
    Justin M. Wozniak, Timothy G. Armstrong, Daniel S. Katz, Michael Wilde, and Ian T. Foster.
    Proc. Extreme-scale Programming Tools at SC 2014.

  37. Petascale Tcl with NAMD, VMD, and Swift/T
    James C. Phillips, John E. Stone, Kirby L. Vandivort, Timothy G. Armstrong, Justin M. Wozniak, Michael Wilde, and Klaus Schulten.
    Proc. High Performance Technical Computing in Dynamic Languages at SC 2014.
    [PDF]

  38. Language features for scalable distributed-memory dataflow computing
    Justin M. Wozniak, Michael Wilde, and Ian T. Foster.
    Proc. Data-Flow Execution Models for Extreme-Scale Computing at PACT 2014.
    [PDF]

  39. The assembly and management of scalable computational experiments
    Justin M. Wozniak.
    Computation Institute Fellow Nomination Talk 2014.

  40. Networking materials data: Accelerating discovery at an experimental facility
    Ian Foster, Rachana Ananthakrishnan, Ben Blaiszik, Kyle Chard, Ray Osborn, Steve Tuecke, Michael Wilde, and Justin M. Wozniak.
    Proc. Workshop on High Performance Computing, Grids and Clouds 2014.

  41. Compiler techniques for massively scalable implicit task parallelism
    Timothy G. Armstrong, Justin M. Wozniak, Michael Wilde, and Ian T. Foster.
    Proc. SC 2014.
    [PDF]

  42. Design and evaluation of the GeMTC framework for GPU-enabled many task computing
    Scott J. Krieder, Justin M. Wozniak, Timothy G. Armstrong, Michael Wilde, Daniel S. Katz, Benjamin Grimmer, Ian T. Foster, and Ioan Raicu.
    Proc. HPDC 2014.
    [PDF]

  43. Evaluating storage systems for scientific data in the cloud
    Ketan Maheshwari, Justin M. Wozniak, Hao Yang, Daniel S. Katz, Matei Ripeanu, Victor Zavala, and Michael Wilde.
    Proc. ScienceCloud 2014. (Best paper.)
    [PDF]

  44. Implicitly-parallel functional dataflow for productive cloud programming on Chameleon
    Scott Krieder, Ioan Raicu, Justin M. Wozniak, and Michael Wilde.
    Proc. NSFCloud Workshop on Experimental Support for Cloud Computing 2014.

  45. Toward computational experiment management via multi-language applications
    Justin M. Wozniak, Timothy G. Armstrong, Daniel S. Katz, Michael Wilde, and Ian T. Foster.
    DOE Workshop on Software Productivity for eXtreme scale Science (SWP4XS) 2014.
    [PDF]

  46. Productive composition of extreme-scale applications using implicitly parallel dataflow
    Michael Wilde, Justin M. Wozniak, Timothy G. Armstrong, Daniel S. Katz, and Ian T. Foster.
    DOE Workshop on Software Productivity for eXtreme scale Science (SWP4XS) 2014.
    [PDF]

  47. Parallel scripting for beamline science: Connecting Big Data and HPC
    Justin M. Wozniak.
    At BES Facilities Computing Working Group Technical Meeting 2014.

  48. Turbine: A distributed-memory dataflow engine for high performance many-task applications
    Justin M. Wozniak, Timothy G. Armstrong, Ketan Maheshwari, Ewing L. Lusk, Daniel S. Katz, Michael Wilde, and Ian T. Foster.
    Fundamenta Informaticae 28(3), 2013.
    [PDF]

  49. Extending the Galaxy portal with parallel and distributed execution capability
    Ketan Maheshwari, Alex Rodriguez, David Kelly, Ravi Madduri, Justin M. Wozniak, Michael Wilde, and Ian T. Foster.
    Proc. DataCloud 2013.
    [PDF]

  50. Dataflow coordination of data-parallel tasks via MPI 3.0
    Justin M. Wozniak, Tom Peterka, Timothy G. Armstrong, James Dinan, Ewing L. Lusk, Michael Wilde, and Ian T. Foster.
    Proc. EuroMPI 2013.
    [PDF]

  51. Reusability in science: From initial user engagement to dissemination of results
    Ketan Maheshwari, David Kelly, Scott J. Krieder, Justin M. Wozniak, Daniel S. Katz, Zhi-Gang Mei, and Mainak Mookherjee.
    Proc. Workshop on Sustainable Software for Science: Practice and Experiences at SC 2013.
    [PDF]

  52. Swift/T: Scalable data flow programming for distributed-memory task-parallel applications
    Justin M. Wozniak, Timothy G. Armstrong, Michael Wilde, Daniel S. Katz, Ewing Lusk, and Ian T. Foster.
    Proc. CCGrid 2013.
    [PDF]

  53. Evaluating cloud computing techniques for smart power grid design using parallel scripting
    Ketan Maheshwari, Ken Birman, Justin M. Wozniak, and Devin Van Zandt.
    Proc. CCGrid 2013.
    [PDF]

  54. A model for tracing and debugging large-scale task-parallel programs with MPE
    Justin M. Wozniak, Anthony Chan, Timothy G. Armstrong, Michael Wilde, Ewing Lusk, and Ian T. Foster.
    Proc. Workshop on Leveraging Abstractions and Semantics in High-performance Computing (LASH-C) at PPoPP 2013.
    [PDF]

  55. Rapid development of highly concurrent multi-scale simulators with Swift
    Justin M. Wozniak.
    ExMatEx all-hands meeting 2013.

  56. Swift+Chirp for synchrotron beamline data analysis
    Justin M. Wozniak.
    At Cooperative Computing Laboratory Workshop 2013.

  57. Turbine: A distributed-memory dataflow engine for extreme-scale many-task applications
    Justin M. Wozniak, Timothy G. Armstrong, Michael Wilde, Ketan Maheshwari, Daniel S. Katz, Matei Ripeanu, Ewing L. Lusk, and Ian T. Foster.
    Proc. Workshop on Scalable Workflow Enactment Engines and Technologies 2012.
    [PDF] Slides: [PDF]

  58. ExM: High level dataflow programming for extreme-scale systems
    Timothy G. Armstrong, Justin M. Wozniak, Michael Wilde, Ketan Maheshwari, Daniel S. Katz, Matei Ripeanu, Ewing L. Lusk, and Ian T. Foster.
    HotPar (poster series) 2012.
    [PDF] Poster: [PDF]