| Online data analysis and reduction: An important Co-design motif for extreme-scale computers | 1 | 0.35 | 2021 |
| ExaWorks: Workflows for Exascale | 0 | 0.34 | 2021 |
| Bootstrapping in-situ workflow auto-tuning via combining performance models of component applications | 0 | 0.34 | 2021 |
| In-situ workflow auto-tuning through combining component models | 0 | 0.34 | 2021 |
| A Population Data-Driven Workflow For Covid-19 Modeling And Learning | 1 | 0.36 | 2021 |
| DeepClone: Lightweight State Replication of Deep Learning Models for Data Parallel Training | 1 | 0.36 | 2020 |
| High-bypass Learning: Automated Detection of Tumor Cells That Significantly Impact Drug Response | 0 | 0.34 | 2020 |
| DeepFreeze: Towards Scalable Asynchronous Checkpointing of Deep Learning Models | 3 | 0.40 | 2020 |
| Parsl: Pervasive Parallel Programming in Python. | 8 | 0.53 | 2019 |
| MPI jobs within MPI jobs: A practical way of enabling task-level fault-tolerance in HPC workflows | 1 | 0.35 | 2019 |
| Understanding Scalability and Fine-Grain Parallelism of Synchronous Data Parallel Training | 1 | 0.35 | 2019 |
| Performance, Energy, and Scalability Analysis and Improvement of Parallel Cancer Deep Learning CANDLE Benchmarks | 4 | 0.41 | 2019 |
| Extreme-Scale Dynamic Exploration of a Distributed Agent-Based Model With the EMEWS Framework. | 1 | 0.35 | 2018 |
| High-throughput cancer hypothesis testing with an integrated PhysiCell-EMEWS workflow. | 0 | 0.34 | 2018 |
| Portable and Reusable Deep Learning Infrastructure with Containers to Accelerate Cancer Studies | 0 | 0.34 | 2018 |
| Parsl - Scalable Parallel Scripting in Python. | 0 | 0.34 | 2018 |
| Methodology for the Rapid Development of Scalable HPC Data Services. | 0 | 0.34 | 2018 |
| Toward Understanding I/O Behavior in HPC Workflows. | 3 | 0.41 | 2018 |
| CANDLE/Supervisor: a workflow framework for machine learning applied to cancer research. | 10 | 0.53 | 2018 |
| Streaming supercomputing needs workflow-enabled programming-in-the-large. | 0 | 0.34 | 2017 |
| Experimental evaluation of a flexible I/O architecture for accelerating workflow engines in ultrascale environments. | 1 | 0.37 | 2017 |
| Report on the first workshop on negative and null results in eScience. | 0 | 0.34 | 2017 |
| Supporting task-level fault-tolerance in HPC workflows by launching MPI jobs inside MPI jobs | 0 | 0.34 | 2017 |
| Computing Just What You Need: Online Data Analysis and Reduction at Extreme Scales | 6 | 0.44 | 2017 |
| Flexible Data-Aware Scheduling for Workflows over an In-memory Object Store | 3 | 0.42 | 2016 |
| From desktop to Large-Scale Model Exploration with Swift/T. | 1 | 0.41 | 2016 |
| Challenges and Opportunities for Dataflow Processing on Exascale Computers. | 0 | 0.34 | 2016 |
| Big Data Remote Access Interfaces for Light Source Science | 3 | 0.42 | 2015 |
| Toward Interlanguage Parallel Scripting for Distributed-Memory Scientific Computing | 2 | 0.38 | 2015 |
| Interlanguage parallel scripting for distributed-memory scientific computing | 2 | 0.39 | 2015 |
| Lessons Learned from Building In Situ Coupling Frameworks | 9 | 0.52 | 2015 |
| Porting Ordinary Applications to Blue Gene/Q Supercomputers | 0 | 0.34 | 2015 |
| Petascale Tcl with NAMD, VMD, and Swift/T | 4 | 0.45 | 2014 |
| Big Data Staging with MPI-IO for Interactive X-ray Science | 2 | 0.39 | 2014 |
| Compiler Techniques for Massively Scalable Implicit Task Parallelism | 15 | 0.74 | 2014 |
| Networking Materials Data: Accelerating Discovery at Experimental Facilities. | 0 | 0.34 | 2014 |
| Evaluating storage systems for scientific data in the cloud | 3 | 0.40 | 2014 |
| Compiler Optimization for Extreme-Scale Scripting | 0 | 0.34 | 2014 |
| Design and evaluation of the gemtc framework for GPU-enabled many-task computing | 14 | 0.91 | 2014 |
| Swift/T: scalable data flow programming for many-task applications | 14 | 0.73 | 2013 |
| Turbine: A Distributed-memory Dataflow Engine for High Performance Many-task Applications | 16 | 0.73 | 2013 |
| JETS: Language and System Support for Many-Parallel-Task Workflows | 2 | 0.39 | 2013 |
| MTC envelope: defining the capability of large scale computers in the context of parallel scripting applications | 11 | 0.56 | 2013 |
| Parallelizing the execution of sequential scripts | 10 | 0.69 | 2013 |
| Dataflow coordination of data-parallel tasks via MPI 3.0 | 8 | 0.60 | 2013 |
| Swift/T: Large-Scale Application Composition via Distributed-Memory Dataflow Processing | 34 | 1.11 | 2013 |
| Reusability in Science: From Initial User Engagement to Dissemination of Results. | 1 | 0.37 | 2013 |
| Design and analysis of data management in scalable parallel scripting | 19 | 0.72 | 2012 |
| Many-Task Computing and Blue Waters | 6 | 0.50 | 2012 |
| Turbine: a distributed-memory dataflow engine for extreme-scale many-task applications | 12 | 0.62 | 2012 |
