Publications

Publications by the DataSpaces group:

  1. Wang, Z., et al (2022). "Adaptive Elasticity Policies for Staging-Based In Situ Visualization." Future Generation Computer Systems. 142: 75-89.
  2. Zhang, B., et al (2022). "Assembling Portable In-Situ Workflow from Heterogeneous Components using Data Reorganization." 2022 22nd IEEE International Symposium on Cluster, Cloud and Internet Computing (CCGrid)
  3. Subedi, P., et al (2021). "RISE: Reducing I/O Contention in Staging-based Extreme-Scale In-situ Workflows." 2021 IEEE International Conference on Cluster Computing (CLUSTER), IEEE.
  4. Wang, Z., et al. (2021). "Facilitating Staging-based Unstructured Mesh Processing to Support Hybrid In-Situ Workflows." 2021 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), IEEE.
  5. Jin, T., et al. (2020). "Towards Autonomic Data Management for Staging-based Coupled Scientific Workflows." Journal of Parallel and Distributed Computing 146: 35-51.
  6. Wang, Z., et al. (2020). "Staging Based Task Execution for Data-driven, In-Situ Scientific Workflows." 2020 IEEE International Conference on Cluster Computing (CLUSTER), IEEE.
  7. Duan, S., et al. (2020). "CoREC: Scalable and Resilient In-memory Data Staging for In-situ Workflows." ACM Transactions on Parallel Computing (TOPC).
  8. Zhang, B., et al. (2020). "Toward Resilient Heterogeneous Computing Workflow through Kokkos-DataSpaces Integration.", Sandia National Lab.(SNL-CA), Livermore, CA (United States).
  9. Duan, S. et all (2019). "Addressing Data Resiliency for Staging Based Scientific Workflows.", Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (SC19).
  10. Subedi, P., et al. (2019). "Leveraging Machine Learning for Anticipatory Data Delivery in Extreme Scale in-situ Workflows." 2019 IEEE International Conference on Cluster Computing (CLUSTER), IEEE.
  11. Duan, S., et al. (2018). "Scalable Data Resilience for in-memory data staging." 2018 IEEE International Parallel and Distributed Processing Symposium (IPDPS), IEEE.
  12. Subedi, P., et al. (2018). "Stacker: an autonomic Data Movement Engine for Extreme-scale Data Staging-based In-situ Workflows." SC18: International Conference for High Performance Computing, Networking, Storage and Analysis, IEEE.
  13. Aktas, M. F., et al. (2017). "WA-DataSpaces: Exploring the Data Staging Abstractions for Wide-area Distributed Scientific Workflows." 2017 46th International Conference on Parallel Processing (ICPP), IEEE.                        
  14. Jin, T., et al. (2017). "Adaptive Data Placement in Multi-Tiered Data Staging Runtime." New Frontiers in High Performance Computing and Big Data, IOS Press: 175-196.
  15. Zhang, F., et al. (2017). "In‐memory Staging and Data‐centric Task Placement for Coupled Scientific Simulation Workflows." Concurrency and Computation: Practice and Experience 29(12): e4147.
  16. Sun, Q., et al. (2016). "In-staging Data Placement for Asynchronous Coupling of Task-based Scientific Workflows." 2016 Second International Workshop on Extreme Scale Programming Models and Middlewar (ESPM2), IEEE.
  17. Romanus, M., et al. (2016). "Persistent Data Staging Services for Data Intensive in-situ Scientific Workflows." Proceedings of the ACM International Workshop on Data-Intensive Distributed Computing.
  18. Zhang, F., et al. (2014). "XpressSpace: a Programming Framework for Coupling Partitioned Global Address Space Simulation Codes." Concurrency and Computation: Practice and Experience 26(3): 644-661.
  19. Docan, C., et al. (2012). "DataSpaces: an Interaction and Coordination Framework for Coupled Simulation Workflows." Cluster Computing 15(2): 163-181.
  20. Zhang, F., et al. (2012). "Enabling In-situ Execution of Coupled Scientific Workflow on Multi-core Platform". 2012 IEEE 26th International Parallel and Distributed Processing Symposium, IEEE.
  21. Docan, C., et al. (2011). "Moving the Code to the Data: Dynamic Code Eeployment Using ActiveSpaces." 2011 IEEE International Parallel & Distributed Processing Symposium, IEEE.
  22. Zhang, F., et al. (2011). "Enabling Multi-physics Coupled Simulations within the PGAS Programming Framework." 2011 11th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, IEEE.
  23. Zheng, F., et al. (2010). "PreDatA: Preparatory Data Analytics on Peta-scale Machines." 2010 IEEE International Symposium on Parallel & Distributed Processing (IPDPS), IEEE.
  24. Zhang, F., et al. (2010). "DADS: a Dynamic and Adaptive Data Space for Interacting Parallel Applications." Proceedings of the IASTED International Conference on Parallel and Distributed Computing and Systems (PDCS 2010), Marina Del Rey.
  25. Docan, C., et al. (2010). "Enabling hJgh‐speed Asynchronous Data Extraction and Transfer using DART." Concurrency and Computation: Practice and Experience 22(9): 1181-1204.
  26. Docan, C., et al. (2010). "Experiments with Memory-to-Memory Coupling for End-to-End Fusion Simulation Workflows." 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing, IEEE."
  27. Docan, C., et al. (2008). "DART: a Substrate for High Speed Asynchronous Data I/O." Proceedings of the 17th international symposium on High performance distributed computing.
  28. Bhat, V., et al. (2007). "Experiments with In-transit Processing for Data Intensive Grid Workflows." 2007 8th IEEE/ACM International Conference on Grid Computing, IEEE.
  29. Bhat, V., et al. (2007). "A Self-managing Wide-area Data Streaming Service." Cluster Computing 10(4): 365-383.
  30. Docan, C., et al. (2007). "High Speed Asynchronous Data Transfers on the Cray XT3." Cray User Group Conference.
  31. Bhat, V., et al. (2006). "Enabling Self-managing Applications using Model-based Online Control Strategies." 2006 IEEE International Conference on Autonomic Computing, IEEE.