Publications
Converged Applications
Exploration of Domain-Aware Machine Learning for Grid Analytics (DAML-GA) – M Halappanavar
Conference Proceedings:
2021
Jain M., K. Gupta, A. Visweswara Sathanur, V. Chandan, and M. Halappanavar. 2021. "Transfer-Learnt Energy Models for Predicting Electricity Consumption in Buildings with Limited and Sparse Field Data." In American Control Conference (ACC 2021), May 25-28, 2021, New Orleans, LA, 2887-2894. Piscataway, New Jersey: IEEE. PNNL-SA-156692. doi:10.23919/ACC50511.2021.9483228
Presentations:
2020
Gupta K., M. Jain, A. Visweswara Sathanur, V. Chandan, and M. Halappanavar. 2020. "Learn from One, Apply to Many: Knowledge Transfer for Building Controls." Presented by M. Jain at Post Doctorate Symposium, Pacific Northwest National Laboratory, Richland, Washington. PNNL-SA-155770.
Other:
2020
Tumeo A., M. Halappanavar, J.T. Feo, and F. Petrini. 2020. "Introduction to the TOPC Special issue on Innovations in Systems for Irregular Applications – Part II." Pacific Northwest National Laboratory, Richland, Washington. PNNL-SA-155627. (This document introduces the Special issue on Innovations in Systems for Irregular Applications of the ACM Transactions on Parallel Computing)
Data-Model Convergence Application Flows – D Vrabie
Publications:
2019
Abhyankar S.G., S. Peles, and D.L. Vrabie. 2019. Power Grid Computational Challenges and Metrics for Hardware Accelerator Evaluation. Pacific Northwest National Laboratory, Richland, Washington. PNNL-29301.
Poster:
2019
Vrabie D.L. 2019. "DMC Application Challenges." Pacific Northwest National Laboratory, Richland, Washington. PNNL-SA-143678.
Holonic Approach toward Data-Model Convergence – S Choudhury
Publications:
2022
Nandanoori S., S. Guan, S. Kundu, S. Pal, K. Agarwal, Y. Wu, and S. Choudhury. 2022. "Graph Neural Network and Koopman Models for Learning Networked Dynamics: A Comparative Study on Power Grid Transients Prediction." IEEE Access 10. PNNL-SA-161313. doi:10.1109/ACCESS.2022.3160710
Conference Proceedings:
2021
Ahmed A., K.S. Sajan, A.K. Srivastava, and Y. Wu. 2021. "Anomaly Detection, Localization and Classification using Drifting Synchrophasor Data Streams." IEEE Transactions on Smart Grid. PNNL-SA-159464. doi:10.1109/TSG.2021.3054375.
Guan S., H. Ma, S. Choudhury, and Y. Wu. 2021. "GEDet: Detecting Erroneous Nodes with A Few Examples." In Proceedings of the 47th International Conference on Very Large Data Bases (VLDB 2021), August 16-20, 2021, Virtual, Online, 14, 2875 - 2878. PNNL-SA-160866. doi:10.14778/3476311.3476367
2020
Guan S., P. Lin, H. Ma, Y. Wu. 2020. ”GEDet: Adversarially Learned Few-shot Detection of Erroneous Nodes in Graphs.” In IEEE International Conference on Big Data (Best Paper Award)
Nandanoori S., S. Kundu, S. Pal, K. Agarwal, and S. Choudhury. 2020. "Model-Agnostic Algorithm for Real-Time Attack Identification in Power Grid using Koopman Modes." In IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids. PNNL-SA-154191. doi:10.1109/SmartGridComm47815.2020.9303022
Theory-Driven Reinforcement Learning: Understanding Complexity in Protein Dynamics - B Cannon
Publications:
2023
King E., J.T. Holzer, J.A. North, and W.R. Cannon. 2023. "An Approach to Learn Regulation to Maximize Growth and Entropy Production Rates in Metabolism." Frontiers in Systems Biology 3. PNNL-SA-170735. doi:10.3389/fsysb.2023.981866
Presentations:
2023
Cannon W.R. 03/14/2023. "Learning Control of Chemical Reaction Networks and Predicting their Emergent Properties." Richland, Washington. PNNL-SA-182802.
King E. 03/07/2023. "Predicting Cellular Regulation by Combining Statistical Thermodynamics, Control Theory, and Learning." Presented by E. King at American Physical Society March Meeting 2023, Las Vegas, Nevada. PNNL-SA-182592.
Software and Data Releases:
Pathway controlled optimization: https://github.com/pnnl/pathway_controlled_optimization
Synergistic Activities:
2023
W. R. Cannon, Steering Committee, NIH-NSF-DOE Interagency Multiscale Modeling Consortium.
W. R. Cannon, Session Organizer, Non Equilibrium Thermodynamics: From Chemical Reaction Networks to Natural Selection, American Physical Society March Meeting, 2023.
2022
Cannon W.R. 05/17/2022. "Slides/Lecture for UC Riverside class." Presented by W.R. Cannon at UC Riverside class, Zoom, California. PNNL-SA-173081.
W. R. Cannon, Session Organizer, Non Equilibrium Thermodynamics: From Chemical Reaction Networks to Natural Selection, American Physical Society March Meeting, 2022.
2021
Cannon, W. R., Conference Co-Organizer: Annual Meeting of the Society for Mathematical Biology, June 13-17, 2021. Virtual, http://smb2021.org
W. R. Cannon, Session Organizer, Non Equilibrium Thermodynamics: From Chemical Reaction Networks to Natural Selection, American Physical Society March Meeting, 2021.
Cannon, W. R., Co-Organizer, AAAS Session: Coupled Experimental and Multiscale Modeling Study of the Environmental Microbiome, Annual Meeting of the American Association for the Advancement of Science (AAAS), February 8, 2021, Virtual.
Causal Inference and ML Methods for MIP Analysis of Security Constrained Unit (SCY0) Commitment – J Holzer, J Zucker
Publications:
2024
Holzer J., J. Cottam, J. Li, C. Xie, G. Kestor, J. Zucker, and F. Pan. 2024. "Testing and Accelerating Computational Kernels for Fast Evaluation of Security Constraints with Contingencies on Multiple Branches." IEEE Transactions on Power Systems [under review 2024]. PNNL-SA-206377. doi:10.36227/techrxiv.173386277.78847129/v1
2023
King E., J.T. Holzer, J.A. North, and W.R. Cannon. 2023. "An Approach to Learn Regulation to Maximize Growth and Entropy Production Rates in Metabolism." Frontiers in Systems Biology 3. PNNL-SA-170735. doi:10.3389/fsysb.2023.981866
2022
Mohammad-Taheri S., J.D. Zucker, C.T. Hoyt, K. Sachs, V. Tewari, R. Ness, and O. Vitek. 2022. "Do-calculus enables estimation of causal effects in partially observed biomolecular pathways." Bioinformatics 38, no. Supplement_1:i350-i358. PNNL-SA-172208. doi:10.1093/bioinformatics/btac251
2021
Amin N., W. Byrd, J.A. Cottam, M. Parent, and J.D. Zucker. 10/20/2021. "A Pearl Pearl, or How to teach a good old-fashioned AI new tricks." Presented by J.D. Zucker at ProbProg 2021, Online Conference, United States. PNNL-SA-167618.
Bingham E., J. Koppel, A. Lew, R. Ness, Z. Tavares, S. Witty, and J.D. Zucker. 10/20/2021. "Causal Probabilistic Programing Without Tears." Presented by J.D. Zucker at ProbProg 2021, Online Conference, United States. PNNL-SA-167619.
Byrd W., G. Rosenblatt, M.J. Patton, T.K. Tran-Nguyen, J.D. Zucker, J.A. Cottam, and N. Amin. 2021. "Medikanren: a System for Biomedical Reasoning." In miniKanren 20: 2nd Annual miniKanren and Relational Programming Workshop. PNNL-SA-159519.
Kohler D., J.D. Zucker, V. Tewari, K. Sachs, R. Ness, and O. Vitek. 10/20/2021. "Explorations of causal probabilistic programming approaches for rule-based models of biological signaling pathways." Presented by J.D. Zucker at ProbProg 2021, Online Conference, United States. PNNL-SA-167588.
Presentations:
2021
Bingham E., J. Koppel, A. Lew, Z. Tavares, R. Ness, S. Witty, and J.D. Zucker. 10/20/2021. "Causal Probabilistic Programing Without Tears (Presentation)." Presented by S. Witty at ProbProg 2021, Online Conference, United States. PNNL-SA-167982.
Holzer J., J. Zucker, X. Lin, J. Cottam, F. Pan, A. Campbell, C. Joslyn, Z. Weems, Z. Hou. 2021. “SCY0: Causal inference and machine learning applications to SCUC” Physics Informed Machine Learning Workshop.
Holzer J., J. Zucker. 2021. “SCY0 Security constrained evaluation”, DMC Co-Design Workshop.
Zucker J.D. 11/04/2021. "Leveraging Structured Biological Knowledge for Counterfactual Inference: a Case Study of Viral Pathogenesis." Presented by J.D. Zucker at Western Washington Data-Driven Seminar Series, Online Conference, United States. PNNL-SA-168167.
2020
Holzer J.T., F. Pan, Y. Chen, and J.D. Zucker. 2020. "Fast evaluation and statistical analysis of security constraints in security constrained unit commitment." Presented by J.T. Holzer at INFORMS Annual Meeting 2020, Online Conference, United States. PNNL-SA-157685.
Internal Presentations:
2021
Cottam, J., J. Zucker. “The Y0 Causal Inference Engine” PNNL TechFest, June 21, 2021
Holzer J., J. Zucker. “SCY0 Security constraint evaluation” DMC Co-Design Workshop at PNNL, March 3, 2021
Holzer J., J. Zucker, X. Lin, J. Cottam, F. Pan, A. Campbell, C. Joslyn, Z. Weems, Z. Hou. “SCY0: Causal inference and machine learning applications to SCUC” Physics Informed Machine Learning Workshop at PNNL, February 16, 2021
IP Generation:
Co-design of Bayesian Inference Algorithms: https://gitlab.pnnl.gov/y0-scuc/dmc-hmc
SCUC Simulation, Data Generation, Training/Testing Pipeline: https://gitlab.pnnl.gov/y0-scuc/xavier-2019
SCUC Simulation and Security Constraint Evaluation Code: https://gitlab.pnnl.gov/y0-scuc
Y0 Causal Inference Engine: https://github.com/y0-causal-inference/y0
PACER – S Ghosh
Publications:
2022
Lee H., M. Jain, and S. Ghosh. 2022. "Sparse Deep Neural Network Inference using different Programming Models." In 2022 IEEE High Performance Extreme Computing. PNNL-SA-175380. doi:10.1109/HPEC55821.2022.9926362
Conference Proceedings:
2022
Chou H., and S. Ghosh. 2022. "Batched Graph Clustering on GPUs." In 31st International Conference on Parallel Architectures and Compilation Techniques (PACT). PNNL-SA-167802. https://doi.org/10.1145/3559009.3569655
Lee H., M. Jain, and S. Ghosh. 2022. "Sparse Deep Neural Network Inference using different Programming Models." In 2022 IEEE High Performance Extreme Computing. PNNL-SA-175380. doi:10.1109/HPEC55821.2022.9926362
Ghosh S. 2022. "Improved Distributed-memory Triangle Counting by Exploiting the Graph Structure." In IEEE High Performance Extreme Computing Conference (HPEC 2022), September 19-23, 2022, Virtual, Online, 1-6. Piscataway, New Jersey: IEEE. PNNL-SA-175362. doi:10.1109/HPEC55821.2022.9926376
Ghosh S., N.R. Tallent, and M. Halappanavar. 2022. "Characterizing Performance of Graph Neighborhood Communication Patterns." IEEE Transactions on Parallel and Distributed Systems 33, no. 4:915-928. PNNL-SA-152879. doi:10.1109/TPDS.2021.3101425
Jain M., S. Ghosh, and S. Nandanoori. 2022. "Workload Characterization of a Time Series Prediction System for Spatial-Temporal Data." In 19th ACM International Conference on Computing Frontiers. May 2022. New York, NY, USA, New York: Association for Computing Machinery. PNNL-SA-165281. doi:10.1145/3528416.3530242
2021
Ghosh S., A. Lumsdaine, C. Alsobrooks, M. Ruefenacht, A. Skjellum, and P.V. Bangalore. 2021. "Towards Modern C++ Language Bindings to MPI." In ExaMPI21: Workshop on Exascale MPI. PNNL-SA-166316. https://doi.org/10.1109/ExaMPI54564.2021.00009
Ghosh S., N.R. Tallent, M. Minutoli, M. Halappanavar, R. Peri, and A. Kalyanaraman. 2021. "Single-node Partitioned-Memory for Huge Graph Analytics: Cost and Performance Trade-offs." In Proceedings of the International Conference for High Performance Computing, Network, Storage and Analysis (SC 2021), November 14-19, 2021, Virtual, Online, Art. No. 55. New York, New York:Association for Computing Machinery. PNNL-SA-161359. doi:10.1145/3458817.3476156
Ghosh S., Y. Guo, P. Balaji, and A. Gebremedhin. 2021. "RMACXX: An Efficient High-Level C++ Interface over MPI-3 RMA." In Proceedings of the 21st IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing (CCGrid 2021), May 10-13, 2021, Virtual, 143-155. Piscataway, New Jersey: IEEE. PNNL-SA-158770. doi:10.1109/CCGrid51090.2021.00024
Domain Aware Deep-learning Algorithms Integrated with Scientific-computing Technologies (DADAIST) – J Drgona
Publications:
2023
Koch J.V., Z. Chen, A.R. Tuor, J. Drgona, and D.L. Vrabie. 2023. "Structural Inference of Networked Dynamical Systems with Universal Differential Equations." Chaos: An Interdisciplinary Journal of Nonlinear Science 33, no. 2:023103. PNNL-SA-174936. doi:10.1063/5.0109093
Legaard C.M., T. Schranz, G. Schweiger, J. Drgona, B. Falay, C. Gomes, and A. Iosifidis, et al. 2023. "Constructing Neural Network-Based Models for Simulating Dynamical Systems." ACM Computing Surveys 55, no. 11:Art. No. 236. PNNL-SA-168499. doi:10.1145/3567591
Li S., J. Drgona, S.G. Abhyankar, and L. Pileggi. 2023. "Power Grid Behavioral Patterns and Risks of Generalization in Applied Machine Learning." In International Workshop on Applied Machine Learning for Intelligent Energy Systems (AMLIES). PNNL-SA-184952. arXiv preprint arXiv:2304.10702
Li S., J. Drgona, A.R. Tuor, L. Pileggi, D.L Vrabie. 2023. "Homotopy Learning of Parametric Solutions to Constrained Optimization Problems", preprint.
Presentations:
2023
Drgona J. 04/18/2023. "Differentiable Programming for Modeling and Control of Dynamical Systems." Abstract submitted to Artificial Intelligence for Robust Engineering and Science Workshop (AIRES 4), Oak Ridge, Tennessee. PNNL-SA-181435.
Drgona J., A.R. Tuor, J.V. Koch, S.E. Dernbach, Z. Chen, S.G. Abhyankar, and E. King, et al. 01/12/2023. "Differentiable programming for modeling and control of energy systems." Presented by J. Drgona at 2023 Grid Science Winter School and Conference, Santa Fe, Nm, New Mexico. PNNL-SA-181241.
Koch J.V., Z. Chen, S.E. Dernbach, J. Drgona, A.R. Tuor, and D.L. Vrabie. 03/28/2023. "Structural Inference of Networked Dynamical Systems with Universal Differential Equations." Presented by J.V. Koch at AAAI Spring Symposium - Computational Approaches to Scientific Discovery, San Francisco, California. PNNL-SA-183163.
Koch J.V., Z. Chen, A.R. Tuor, J. Drgona, and D.L. Vrabie. 02/21/2023. "Structural Inference of Networked Dynamical Systems with Universal Differential Equations." Presented by J.V. Koch at Differential Equations for Data Science 2023, Online Conference, Japan. PNNL-SA-182036.
2022
Drgona J., A.R. Tuor, J.V. Koch, S.G. Abhyankar, E. King, Z. Chen, and S.S. Vasisht, et al. 10/21/2022. "Differentiable programming for modeling and control of dynamical systems." Presented by J. Drgona at Applied Math Colloquium at the University of Arizona, Tucson, Arizona. PNNL-SA-179095.
Drgona J., A.R. Tuor, D.L. Vrabie, J.V. Koch, Z. Chen, E. King, and S.G. Abhyankar, et al. 11/07/2022. "Differentiable programming for modeling and control of energy systems." Presented by J. Drgona at IEEE 8th World Forum on Internet of Things Yokohama, Japan, Online Conference, Washington. PNNL-SA-179703.
Drgona J., A.R. Tuor, D.L. Vrabie, J.V. Koch, E. King, S. Mukherjee, and W.E. Shaw Cortez, et al. 12/16/2022. "Differentiable programming for modeling and control of dynamical systems." Presented by J. Drgona at Invited Talk at COEP Tech University, Pune, "Online Conference", Washington. PNNL-SA-180734.
Conference Proceedings:
2022
King E., J. Drgona, A.R. Tuor, S.G. Abhyankar, C. Bakker, A. Bhattacharya, and D.L. Vrabie. 2022. "Koopman-based Differentiable Predictive Control for the Dynamics-Aware Economic Dispatch Problem." In American Control Conference (ACC 2022), June 8-10, 2022, Atlanta, GA, 2194-2201. Piscataway, New Jersey: IEEE. PNNL-SA-167421. doi:10.23919/ACC53348.2022.9867379
Software and Data Releases:
Contributions to 1.3 release of Neuromancer https://github.com/pnnl/neuromancer
Synergistic Activities:
2023
Drgona J. Co-Organizer, International Workshop on Applied Machine Learning for Intelligent Energy Systems (AMLIES), ACM e-Energy Conference, 2023. https://sinberbest.berkeley.edu/amlies/2023
Drgona J. Organizer, ACC Workshop on Differentiable Programming for Modeling and Control of Dynamical Systems, 2023 American Control Conference (ACC), 2023. https://d-biswa.github.io/Differentiable-SysCon/
2022
Drgona J. Co-Organizer, NeurIPS 2022 Workshop: Tackling Climate Change with Machine Learning, Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS), 2022. https://www.climatechange.ai/events/neurips2022
Drgona J. Co-Organizer, Third ACM SIGEnergy Workshop on Reinforcement Learning for Energy Management in Buildings & Cities (RLEM), 9th ACM International Conference on Systems for Energy-Efficient Built Environments (BuildSys 2022), 2022. https://rlem-workshop.net/
Heterogeneous Computing
Transfer Learning for Building Energy Modeling (TransBeam) – M Jain, K Gupta, A Visweswara Sathanur, V Chandan, M Halappanavar
Presentations:
2021
Jain M., K. Gupta, A. Visweswara Sathanur, V. Chandan, and M. Halappanavar. 2021. "Transfer-Learnt Models for Predicting Electricity Consumption in Buildings with Limited and Sparse Field Data." Presented by M. Jain at ACC 2021, Virtual, Washington. PNNL-SA-161496.
IP Generation:
Invention Releases
IPID: 32167 - TransBeam Software
Open Source
Software and Data Releases:
TransBeam: https://github.com/jainmilan/transBEAM
Hybrid Advanced Workflows (HAW) – VG Castellana
Conference Proceedings:
2022
Ashraf R.A., and R. Gioiosa. 2022. "Exploring the Use of Novel Spatial Accelerators in Scientific Applications." In Proceedings of the ACM/SPEC International Conference on Performance Engineering (ICPE 2022), April 9-13, 2022, Beijing, China, 47-58. New York, New York: Association for Computing Machinery. PNNL-SA-169884. doi:10.1145/3489525.3511690
Wu N., V.G. Castellana, and H. Kaiser. 2022. "Towards Superior Software Portability with SHAD and HPX C++ Libraries." In Proceedings of the 19th ACM International Conference on Computing Frontiers (CF 2022), May 17-19, 2022, Turin, Italy, 251-257. New York, New York: Association for Computing Machinery. PNNL-SA-171823. doi:10.1145/3528416.3530784
2021
Castellana V.G., and M. Minutoli. 2021. "Productive Programming of Distributed Systems with the SHAD C++ Library." In Proceedings of the 30th International Symposium on High-Performance Parallel and Distributed Computing (HPDC '21), June 21-25, 2021, Virtual, Online, 263 -264. New York, New York: Association for Computing Machinery. PNNL-SA-162110. doi:10.1145/3431379.3462765
2020
Azad M., M.M. Aznaveh, S. Beamer, M. Blanco, J. Chen, L. D'Alessandro, and R. Dathathri, et al. 2020. "Evaluation of Graph Analytics Frameworks Using the GAP Benchmark Suite." In IEEE International Symposium on Workload Characterization (IISWC 2020), October 27-30, 2020, Beijing, China, 216-227. Piscataway, New Jersey: IEEE. PNNL-SA-154466. doi:10.1109/IISWC50251.2020.00029
Drocco M., V.G. Castellana, and M. Minutoli. 2020. "Practical Distributed Programming in C++." In Proceedings of the 29th International Symposium on High-Performance Parallel and Distributed Computing, June 23-26, 2020, Stockholm, Sweden, 35-39. New York, New York: Association for Computing Machinery. PNNL-SA-143911. doi:10.1145/3369583.3392680
Gioiosa R., B. Mutlu, S. Lee, J.S. Vetter, G. Picierro, and M. Cesati. 2020. "The Minos Computing Library: Efficient Parallel Programming for Extremely Heterogeneous Systems." In Proceedings of the 13th Workshop on General Purpose Processing Using GPU, February 23, 2020, San Diego, CA. Association for Computing Machinery. New York, New York. PNNL-SA-150725. doi:10.1145/3366428.3380770
Kamatar A.V., R.D. Friese, and R. Gioiosa. 2020. "Locality-Aware Scheduling for Scalable Heterogeneous Environments." In IEEE/ACM International Workshop on Runtime and Operating Systems for Supercomputers (ROSS 2020), November 13, 2020, Virtual Event, 50-58. Los Alamitos, California: IEEE Computer Society. PNNL-SA-157073. doi:10.1109/ROSS51935.2020.00011
Presentations:
2020
Castellana V.G. 2020. "Hybrid Advanced Workflows." Presented by V.G. Castellana at University of Utah Lightning Talks. Richland, Washington. PNNL-SA-153119.
Castellana V.G., M. Drocco, M. Minutoli, and J.T. Feo. 2020. "SHAD P3HPC." Presented by V.G. Castellana at P3HPC Workshop. Online Conference, United States. PNNL-SA-155911.
Feo J.T., and V.G. Castellana. 2020. "Analyzing Network of Networks at Scale." Presented by J.T. Feo at Chesapeake Large Scale Analytics Conference. Virtual, Washington. PNNL-SA-156999.
Lumsdaine, A. 2020. “Graph Data Structures.” Presented by Vito Castellana at Winter 20 C++ Standard Meeting. Prague, Czech Republic.
2019
Castellana V. 2019. “Practical Distributed C++ Programming with SHAD.” CLSAC 19 International Conference. Annapolis, MD, USA.
Drocco M., V.G. Castellana, and M. Minutoli. 2019. "Practical Distributed Programming in C++." Richland, Washington. PNNL-SA-143913.
IP Generation:
Invention Releases
IR: 31846 - SHADES: The SHAD Exploration System
Open Source (also featured on DOE code software center)
Software and Data Releases:
SHAD: https://github.com/pnnl/shad
SHADES: https://github.com/pnnl/shades
MCL: https://github.com/pnnl/MCL
Software-Defined Architecture for Data Analysis (SO(DA)2) – A Tumeo
Publications:
2022
Curzel S., N. Bohm Agostini, V.G. Castellana, M. Minutoli, A.M. Limaye, J.B. Manzano Franco, and J. Zhang, et al. 2022. "End-to-end Synthesis of Dynamically Controlled Machine Learning Accelerators." IEEE Transactions on Computers 71, no. 12:3074 - 3087. PNNL-SA-169650. doi:10.1109/TC.2022.3211430
2021
Tan C., C. Xie, T. Geng, A. Marquez, A. Tumeo, K.J. Barker, and A. Li. 2021. "ARENA: Asynchronous Reconfigurable Accelerator Ring to Enable Data-Centric Parallel Computing." IEEE Transactions on Parallel and Distributed Systems 32, no. 12:2880-2892. PNNL-SA-152862. doi:10.1109/TPDS.2021.3081074
Wang X., A. Tumeo, J.D. Leidel, J. Li, and Y. Chen. 2021. "HAM: Hotspot-Aware Manager for Improving Communications with 3D-Stacked Memory." IEEE Transactions on Computers 70, no. 6:833 - 848. PNNL-SA-161294. doi:10.1109/TC.2021.3066982
Conference Proceedings:
2022
Bohm Agostini N., S. Curzel, A.M. Limaye, V.C. Amatya, M. Minutoli, V.G. Castellana, and J.B. Manzano Franco, et al. 2022. "The SODA Approach: Leveraging High-Level Synthesis for Hardware/Software Co-design and Hardware Specialization: Invited." In Proceedings of the 59th ACM/IEEE Design Automation Conference (DAC 2022), July 10-14, 2022, San Francisco, CA, 1359-1362. New York, New York: Association for Computing Machinery. PNNL-SA-172445. doi:10.1145/3489517.3530628
Tan C., N. Bohm Agostini, T. Geng, C. Xie, J. Li, A. Li, and K.J. Barker, et al. 2022. "DRIPS: Dynamic Rebalancing of Pipelined Streaming Applications on CGRAs." In IEEE International Symposium on High-Performance Computer Architecture (HPCA 2022), April 2-6, 2022, Seoul, Korea, 304-316. Piscataway, New Jersey: IEEE. PNNL-SA-165149. doi:10.1109/HPCA53966.2022.00030
Tan C., T. Tambe, J. Zhang, B. Fang, T. Geng, G. Wei, and D. Brooks, et al. 2022. "ASAP: Automatic Synthesis of Area-Efficient and Precision-Aware CGRAs." In Proceedings of the 36th ACM International Conference on Supercomputing (ICS 2022), June 28-30, 2022, Virtual, Online, Paper No. 4. New York, New York: Association for Computing Machinery. PNNL-SA-172791. doi:10.1145/3524059.3532359
2021
Castellana V.G., A. Tumeo, and F. Ferrandi. 2021. "High-Level Synthesis of Parallel Specifications Coupling Static and Dynamic Controllers." In IEEE International Parallel & Distributed Processing Symposium (IPDPS 2021), May 17-21, 2021, Virtual, Online, Paper No. 9460500. Piscataway, New Jersey: IEEE. PNNL-SA-157406. doi:10.1109/IPDPS49936.2021.00028
Curzel S., N. Bohm Agostini, S. Song, I. Dagli, A.M. Limaye, C. Tan, and M. Minutoli, et al. 2021. "Automated Generation of Integrated Digital and Spiking Neuromorphic Machine Learning Accelerators." In IEEE/ACM International Conference On Computer Aided Design (ICCAD 2021), November 1-4, 2021, Munich, Germany, 1-7. Piscataway, New Jersey: IEEE. PNNL-SA-166239. doi:10.1109/ICCAD51958.2021.9643474
Ferrandi F., V.G. Castellana, S. Curzel, P. Fezzardi, M. Fiorito, M. Lattuada, and M. Minutoli, et al. 2021. "Invited: Bambu: an Open-Source Research Framework for the High-Level Synthesis of Complex Applications." In 58th ACM/IEEE Design Automation Conference (DAC 2021), December 5-9, 2021, San Francisco, CA, 1327-1330. Piscataway, New Jersey: IEEE. PNNL-SA-160619. doi:10.1109/DAC18074.2021.9586110
Tan C., T. Geng, C. Xie, N. Bohm Agostini, J. Li, A. Li, and K.J. Barker, et al. 2021. "DynPaC: Coarse-Grained, Dynamic, and Partially Reconfigurable Array for Streaming Applications." In IEEE 39th International Conference on Computer Design (ICCD 2021), October 24-27, 2021, Virtual, Online, 33-40. Piscataway, New Jersey: IEEE. PNNL-SA-163151. doi:10.1109/ICCD53106.2021.00018
Tan C., C. Xie, A. Li, K.J. Barker, and A. Tumeo. 2021. "AURORA: Automated Refinement of Coarse-Grained Reconfigurable Accelerators." In Design Automation and Test In Europe (DATE 2021), February 1-5, 2021, Virtual, Online, 2021, 1388 - 1393; Paper No. 9473955. Piscataway, New Jersey: IEEE. PNNL-SA-156552. doi:10.23919/DATE51398.2021.9473955
2020
Geng T., A. Li, R. Shi, C. Wu, T. Wang, Y. Li, and P. Haghi, et al. 2020. "AWB-GCN: A Graph Convolutional Network Accelerator with Runtime Workload Rebalancing." In Proceedings 53rd IEEE/ACM International Symposium on Microarchitecture (MICRO), October 17-21, 2020, Athens, Greece, 922-936. Piscataway, New Jersey: IEEE. PNNL-SA-146537. doi:10.1109/MICRO50266.2020.00079
Limaye A., A. Tumeo, T. Adegbija. 2020. "Energy Characterization of Graph Workloads". In Journal of Sustainable Computing: Informatics and Systems - Journal publication for the International Green Computing Symposium. PNNL-SA-144164
Minutoli M., V.G. Castellana, C. Tan, J. Manzano, V. Amatya, A. Tumeo, D. Brooks, G.-Y. Wei. 2020. "SODA: a New Synthesis Infrastructure for Agile Hardware Design of Machine Learning Accelerators”, Invited paper. In ICCAD 2020: the 39th International Conference on Computer-Aided Design. Pages 1–7 - PNNL-SA-155356
Minutoli M., M. Drocco, M. Halappanavar, A. Tumeo, A. Kalyanaraman. 2020. "cuRipples: Influence Maximization on Multi-GPU Systems”. In ICS 2020: International Conference on SuperComputing. Article No.: 12 Pages 1–11* PNNL-SA-148460
Minutoli M., P. Sambaturu, M. Halappanavar, A. Tumeo, A. Kalyanaraman, and A.K. Vullinati. 2020. "PREEMPT: Scalable Epidemic Interventions Using Submodular Optimization on Multi-GPU Systems." In International Conference for High Performance Computing, Network, Storage and Analysis (SC2020), November 9-19, 2020, Atlanta, GA, 1-15. Piscataway, New Jersey: IEEE. PNNL-SA-152817. doi:10.1109/SC41405.2020.00059
Tan C., C. Xie, A. Li, A. Tumeo. 2020. "OpenCGRA, A Unified Framework for Modeling, Testing, and Evaluating CGRAs”, In ICCD 2020: 38th International Conference on Computer Design (ICCD 2020), October 18-21, 2020, 381-388. Piscataway, New Jersey: IEEE. PNNL-SA-152863. doi:10.1109/ICCD50377.2020.00070
Tumeo A., V.G. Castellana, M. Minutoli, J. Manzano, V. Amatya, D. Brooks, G.Y. Wei. 2020. "Software Defined Accelerators from Learning Tools Environment’”, Invited paper. In DAC 2020: Design Automation Conference. Pp. 1-6 - PNNL-SA-152847
2019
Castellana V.G., M. Minutoli, A. Tumeo, M. Lattuada, P. Fezzardi, and F. Ferrandi. 2019. "Software Defined Architectures for Data Analytics”, Invited paper. In ASPDAC 2019: Asia and South Pacific Design Automation Conference. Pages 711–718 PNNL-SA-139669
Presentations:
2021
Tan C., and A. Tumeo. "DynPaC: Coarse-Grained, Dynamic, and Partially Reconfigurable Array for Streaming Applications." The 39th IEEE International Conference on Computer Design, Best Paper Award. October 24 - 27, 2021. PNNL-SA-167148. https://www.youtube.com/watch?v=EWOJQrRZNE0
2020
Tumeo A. "Intelligent Design Space Exploration for High-Level and System Synthesis." International Workshop on Machine Learning for Software Hardware Co-Design (MLSH'20) at PACT 2020 PNNL-SA-156842.
Tumeo A. "Software Defined Accelerators from Learning Tools Environment." CLSAC 2020: Chesapeake Large Scale Analytics Conference, Random Access Session presentation. PNNL-SA-156925.
Tumeo A. "Intelligent Design Space Exploration for High-Level and System Synthesis." AIDArc at ISCA, 2020. PNNL-SA-153440.
Tumeo A. "Data Model Convergence: a case for Software Defined Architectures." SuperComputing Frontiers Europe, 2020. PNNL-SA-152314.
2019
Tumeo A. "Big Graph Analytics – The System Perspective." Dagstuhl Seminar on Big Graph Processing, 2019. PNNL-SA-149960.
Tumeo A. "Data Model Convergence: a case for Software Defined Architectures." ARM Research Summit, 2019. PNNL-SA-147255.
Tumeo A. "Data Model Convergence: a case for Software Defined Architectures." ACM Computing Frontiers, 2019. PNNL-SA-142492.
Software and Data Releases:
Bambu: https://panda.deib.polimi.it/?page_id=31
Datasets for energy characterization of graph workloads: https://github.com/ankurlimaye/energy-characterization-of-graph-workloads-data
OpenCGRA: https://github.com/pnnl/OpenCGRA
SODA-OPT: https://github.com/pnnl/soda-opt
SODA Toolchain Production Docker Image: https://hub.docker.com/r/agostini01/soda
Synergistic Activities:
2021
DAC 2021 - Special Session on Next Generation Opensource Tools for Hardware Specialization
GrAPL 2021 - IPDPS Workshop on Graphs: Architectures, Programming, and Learning
IA3 2021 - 11th SC Workshop on Irregular Applications: Architectures and Algorithms
ICS 2021 - PandA-Bambu tutorial
2020
DAC 2020 - Special Session on Agile Hardware development for Extreme Specialization
GrAPL 2020 - IPDPS Workshop on Graphs: Architectures, Programming, and Learning
IA3 2020 - 10th SC Workshop on Irregular Applications: Architectures and Algorithms
ICCAD 2020 - Special Session on OpenSource tools for Agile Hardware Design
2019
IA3 2019 - 9th SC Workshop on Irregular Applications: Architectures and Algorithms
PACT 2019 - PandA-Bambu tutorial
Editorial Contributions:
Tumeo A., F. Petrini, J. Feo, M.Halappanavar: Introduction to the TOPC Special Issue on Innovations in Systems for Irregular Applications, Part 2. ACM Trans. Parallel Comput. 7(4): 23:1-23:2 (2020)
Tumeo A., F. Petrini, J. Feo, M. Halappanavar: Introduction to the TOPC Special Issue on Innovations in Systems for Irregular Applications, Part 1. ACM Trans. Parallel Comput. 7(1): 1:1-1:2 (2020)
IP Generation:
ARENA: IP: 32213-E, https://github.com/pnnl/arena
Computational-Flow Architecture (CFA): Designing Non-Von-Neumann Architecture for Future Data-Centric Computing – A Li
Publications:
2023
Li Y., T. Geng, S.A. Stein, A. Li, and H. Yu. 2023. "GAAF: Searching Activation Functions for Binary Neural Networks through Genetic Algorithm." Tsinghua Science and Technology 28, no. 1:207 - 220. PNNL-SA-165349. doi:10.26599/TST.2021.9010084
2021
Geng T., A. Li, T. Wang, C. Wu, Y. Li, R. Shi, and W. Wu, et al. 2021. "O3BNN-R: An Out-Of-Order Architecture for High-Performance and Regularized BNN Inference." IEEE Transactions on Parallel and Distributed Systems 32, no. 1:199-213. PNNL-SA-148318. doi:10.1109/TPDS.2020.3013637
Li Y., T. Geng, A. Li, and H. Yu. 2021. "BCNN: Binary Complex Neural Network." Microprocessors and Microsystems 87. PNNL-SA-161063. doi:10.1016/j.micpro.2021.104359
Li A., and S. Su. 2021. "Accelerating Binarized Neural Networks via Bit-Tensor-Cores in Turing GPUs." IEEE Transactions on Parallel and Distributed Systems 32, no. 7:1878-1891. PNNL-SA-156570. doi:10.1109/TPDS.2020.3045828
Tan C., C. Xie, T. Geng, A. Marquez, A. Tumeo, K.J. Barker, and A. Li. 2021. "ARENA: Asynchronous Reconfigurable Accelerator Ring to Enable Data-Centric Parallel Computing." IEEE Transactions on Parallel and Distributed Systems 32, no. 12:2880-2892. PNNL-SA-152862. doi:10.1109/TPDS.2021.3081074
2020
Li A. and S. Su. 2020. "Accelerating Binarized Neural Networks via Bit-Tensor-Cores in Turing GPUs." IEEE Transactions on Parallel and Distributed Systems. PNNL-SA-156570. doi:10.1109/TPDS.2020.3045828
Wang T., T. Geng, A. Li, X. Jin, and M. Herbordt. 2020. "FPDeep: Scalable Acceleration of CNN Training on Deeply-Pipelined FPGA Clusters." IEEE Transactions on Computers 68, no. 8:1143 - 1158. PNNL-SA-140455. doi:10.1109/TC.2020.3000118
Conference Proceedings:
2022
Chen J., N.R. Tallent, K.J. Barker, X. Shen, H. Sung, and A. Li. 2022. "Bit-GraphBLAS: Bit-Level Optimizations of Matrix-Centric Graph Processing on GPU." In IEEE International Parallel and Distributed Processing Symposium (IPDPS 2022), May 30-June 03, 2022, Virtual, Online, 515-525. Los Alamitos, California: IEEE Computer Society. PNNL-SA-161317. doi:10.1109/IPDPS53621.2022.00056
Peng H., S. Huang, S. Chen, B. Li, T. Geng, A. Li, and W. Jiang, et al. 2022. "A Length Adaptive Algorithm-Hardware Co-design of Transformer on FPGA Through Sparse Attention and Dynamic Pipelining." In Proceedings of the 59th ACM/IEEE Design Automation Conference (DAC 2022), July 10-14, 2022, San Francisco, CA, 1135-1140. New York, New York: Association for Computing Machinery. PNNL-SA-170686. doi:10.1145/3489517.3530585
Tan C., N. Bohm Agostini, T. Geng, C. Xie, J. Li, A. Li, and K.J. Barker, et al. 2022. "DRIPS: Dynamic Rebalancing of Pipelined Streaming Applications on CGRAs." In IEEE International Symposium on High-Performance Computer Architecture (HPCA 2022), April 2-6, 2022, Seoul, Korea, 304-316. Piscataway, New Jersey: IEEE. PNNL-SA-165149. doi:10.1109/HPCA53966.2022.00030
Tan C., T. Tambe, J. Zhang, B. Fang, T. Geng, G. Wei, and D. Brooks, et al. 2022. "ASAP: Automatic Synthesis of Area-Efficient and Precision-Aware CGRAs." In Proceedings of the 36th ACM International Conference on Supercomputing (ICS 2022), June 28-30, 2022, Virtual, Online, Paper No. 4. New York, New York: Association for Computing Machinery. PNNL-SA-172791. doi:10.1145/3524059.3532359
You H., T. Geng, Y. Zhang, A. Li, and Y. Lin. 2022. "GCoD: Graph Convolutional Network Acceleration via Dedicated Algorithm and Accelerator Co-Design." In The 28th IEEE International Symposium on High-Performance Computer Architecture (HPCA 2022), April 2-6, 2022, Virtual, Online, 460-474. Los Alamitos, California: IEEE Computer Society. PNNL-SA-161518. doi:10.1109/HPCA53966.2022.00041
Zhang C., S. Jin, T. Geng, J. Tian, A. Li, and D. Tao. 2022. "CEAZ: Accelerating Parallel I/O Via Hardware-Algorithm Co-Designed Adaptive Lossy Compression." In Proceedings of the 36th ACM International Conference on Supercomputing (ICS 2022), June 28-30, 2022, Virtual, Online, Paper No.: 12. New York, New York: Association for Computing Machinery. PNNL-SA-161283. doi:10.1145/3524059.3532362
2021
Feng B., Y. Wang, T. Geng, A. Li, and Y. Ding. 2021. "APNN-TC: Accelerating Arbitrary Precision Neural Networks on Ampere GPU Tensor Cores." In International Conference for High Performance Computing, Networking, Storage and Analysis: Science and Beyond (SC 2021), November 14-19, 2021, Virtual, Online, Art. No. 37. Los Alamitos, California: IEEE Computer Society. PNNL-SA-161389. doi:10.1145/3458817.3476157
Geng T., C. Wu, C. Tan, C. Xie, A. Guo, P. Haghi, and S. He, et al. 2021. "A Survey: Handling Irregularities in Neural Network Acceleration with FPGAs." In IEEE High Performance Extreme Computing Conference (HPEC 2021), September 20-24, 2021, Virtual, Online, 1-8. Piscataway, New Jersey: IEEE. PNNL-SA-165315. doi:10.1109/HPEC49654.2021.9622877
Geng T., C. Wu, Y. Zhang, C. Tan, C. Xie, H. You, and M. Herbordt, et al. 2021. "I-GCN: A Graph Convolutional Network Accelerator with Runtime Locality Enhancement through Islandization." In Proceedings of the 54th IEEE/ACM Annual International Symposium on Microarchitecture (MICRO 2021), October 18-22, 2021, Virtual, Online, 1051 - 1063. Los Alamitos, California: IEEE Computer Society. PNNL-SA-161514. doi:10.1145/3466752.3480113
Manu D., Y. Sheng, J. Yang, J. Deng, T. Geng, A. Li, and C. Ding, et al. 2021. "FL-DISCO: Federated Generative Adversarial Network for Graph-based Molecule Drug Discovery: Special Session Paper." In IEEE/ACM International Conference On Computer Aided Design (ICCAD 2021), November 1-4, 2021, Munich, Germany, 1-7. Piscataway, New Jersey: IEEE. PNNL-SA-166598. doi:10.1109/ICCAD51958.2021.9643440
Peng H., S. Chen, Z. Wang, J. Yang, S. Weitze, T. Geng, and A. Li, et al. 2021. "Optimizing FPGA-based Accelerator Design for Large-Scale Molecular Similarity Search (Special Session Paper)." In IEEE/ACM International Conference On Computer Aided Design (ICCAD 2021), November 1-4, 2021, Munich, Germany, 1-7. Piscataway, New Jersey: IEEE. PNNL-SA-166147. doi:10.1109/ICCAD51958.2021.9643528
Peng H., S. Huang, T. Geng, A. Li, W. Jiang, H. Liu, and S. Wang, et al. 2021. "Accelerating Transformer-based Deep Learning Models on FPGAs using Column Balanced Block Pruning." In Proceedings of the 22nd International Symposium on Quality Electronic Design (ISQED 2021), April 7-9, 2021, Santa Clara, CA, 142-148. Piscataway, New Jersey: IEEE. PNNL-SA-159983. doi:10.1109/ISQED51717.2021.9424344
Peng H., S. Zhou, S. Weitze, J. Li, S. Islam, T. Geng, and A. Li, et al. 2021. "Binary Complex Neural Network Acceleration on FPGA." In IEEE 32nd International Conference on Application-specific Systems, Architectures and Processors (ASAP 2021), July 7-9, 2021, Virtual, 1, 85-92. Los Alamitos, California: IEEE Computer Society. PNNL-SA-165575. doi:10.1109/ASAP52443.2021.00021
Tan C., T. Geng, C. Xie, N. Bohm Agostini, J. Li, A. Li, and K.J. Barker, et al. 2021. "DynPaC: Coarse-Grained, Dynamic, and Partially Reconfigurable Array for Streaming Applications." In IEEE 39th International Conference on Computer Design (ICCD 2021), October 24-27, 2021, Virtual, Online, 33-40. Piscataway, New Jersey: IEEE. PNNL-SA-163151. doi:10.1109/ICCD53106.2021.00018
Tan C., C. Xie, A. Li, K.J. Barker, and A. Tumeo. 2021. "AURORA: Automated Refinement of Coarse-Grained Reconfigurable Accelerators." In Design Automation and Test In Europe (DATE 2021), February 1-5, 2021, Virtual, Online, 2021, 1388 - 1393; Paper No. 9473955. Piscataway, New Jersey: IEEE. PNNL-SA-156552. doi: 10.23919/DATE51398.2021.9473955
2020
Geng T., A. Li, R. Shi, C. Wu, T. Wang, Y. Li, and P. Haghi, et al. 2020. "AWB-GCN: A Graph Convolutional Network Accelerator with Runtime Workload Rebalancing." In Proceedings 53rd IEEE/ACM International Symposium on Microarchitecture (MICRO), October 17-21, 2020, Athens, Greece, 922-936. Piscataway, New Jersey: IEEE. PNNL-SA-146537. doi:10.1109/MICRO50266.2020.00079
Geng T., C. Wu, C. Tan, B. Fang, A. Li, and M. Herbordt. 2020. "CQNN: a CGRA-based QNN Framework." In 2020 IEEE High-Performance Extreme Computing Conference (HPEC ‘20), September 22-24, 2020, Waltham, MA, 1-7. Piscataway, New Jersey: IEEE. PNNL-SA-153940. doi:10.1109/HPEC43674.2020.9286194
Tan C., C. Xie, A. Li, K.J. Barker, and A. Tumeo. 2020. "Open CGRA: An Open-Source Unified Framework for Modeling, Testing, and Evaluating CGRAs." In IEEE 38th International Conference on Computer Design (ICCD 2020), October 18-21, 2020, 381-388. Piscataway, New Jersey: IEEE. PNNL-SA-152863. doi:10.1109/ICCD50377.2020.00070
2019
Li A., T. Geng, T. Wang, M. Herbordt, S. Song, and K.J. Barker. 2019. "BSTC: A Novel Binarized-Soft-Tensor-Core Design for Accelerating Bit-Based Approximated Neural Nets." In International Conference for High Performance Computing, Networking, Storage, and Analysis, November 17-22, 2019, Denver, CO, Article No a38. Los Alamitos, California: IEEE Computer Society. PNNL-SA-142851. doi:10.1145/3295500.3356169
IP Generation:
ARENA: IP: 32213-E, https://github.com/pnnl/arena
OpenCGRA: IP ID No. 32031-E, https://github.com/pnnl/OpenCGRA
TCBNN: IP ID No. 31925-E https://github.com/pnnl/TCBNN
Application-Algorithm-Architecture Co-Design for Large-Scale, Sparse Tensor/Matrix Methods (HiParTI) – J Li
Publications:
2020
Hein E., S. Eswar, A. Yasar, J. Li, J.S. Young, T. Conte, and U. Catalyurek, et al. 2020. "Programming Strategies for Irregular Algorithms on the Emu Chick." ACM Transactions on Parallel Computing 7, no. 4: Article No. 25. PNNL-SA-144460. doi:10.1145/3418077
2019
Hein E., S. Eswar, A. YASAR, J. Li J, J.S. Young, T. Conte, and U. Catalyurek, et al. 2019. "Programming Strategies for Irregular Algorithms on the Emu Chick." arXiv. PNNL-SA-144460.
Li J, Y. Ma, X. Wu, A. Li, K. Barker. 2019. PASTA: A Parallel Sparse Tensor Algorithm Benchmark Suite. CCF Transactions on High-Performance Computing. PNNL-SA-140675.
Young J.S., E. Hein, S. Eswar, P. Lavin, J. Li, J. Riedy, R. Vuduc, T. Conte. 2019. A Microbenchmark Characterization of the Emu Chick. Journal of Parallel Computing. PNNL-SA-143941.
Conference Proceedings:
2021
Liu J., D. Li, R. Gioiosa, and J. Li. 2021. "Athena: High-Performance Sparse Tensor Contraction Sequence on Heterogeneous Memory. " In Proceedings of the ACM International Conference on Supercomputing (ICS 2021) June 14-17, 2021, Virtual, Online, 190 - 202. New York, New York: Association for Computing Machinery. PNNL-SA-159741. doi:10.1145/3447818.3460355
Liu J., J. Ren, R. Gioiosa, D. Li, J. Li. Sparta: High-Performance, Element-Wise Sparse Tensor Contraction on Heterogeneous Memory. Principles and Practice of Parallel Programming (PPoPP). 2021. (Accepted) PNNL-SA-155439.
Xie C., J. Chen, J.S. Firoz, J. Li, S. Song, K.J. Barker, and M.V. Raugas, et al. 2021. "Fast and Scalable Sparse Triangular Solver for Multi-GPU Based HPC Architectures." In 50th International Conference on Parallel Processing (ICPP-21), August 9-12, 2021, Lermont, IL, Article No. 53, pages 1-11. New York, New York: Association for Computing Machinery. PNNL-SA-150878. doi:10.1145/3472456.3472478
2020
Li J., M. Lakshminarasimhan, X. Wu, A. Li, C. Olschanowsky, and K.J. Barker. 2020. "A Sparse Tensor Benchmark Suite for CPUs and GPUs." In IEEE International Symposium on Workload Characterization (IISWC 2020), October 27-30, 2020, Beijing, China, 193-204. Piscataway, New Jersey: IEEE. PNNL-SA-142736. doi:10.1109/IISWC50251.2020.00027
Wu X., Y. Yi, D.Tian, J. Li. Generic, Sparse Tensor Core for Neural Networks. 1st International Workshop on Machine Learning for Software Hardware Co-Design (MLSH), in conjunction with the 29th International Conference on Parallel Architectures and Compilation Techniques (PACT). 2020. PNNL-SA-150292.
2019
Nisa I., J. Li, A. Sukumaran-Rajam, P. Rawat, S. Krishnamoorthy, P. Sadayappan. An Efficient Mixed-Mode Representation of Sparse Tensors. ACM/IEEE International Conference for High-Performance Computing, Networking, Storage, and Analysis (SC). 2019. PNNL-SA-142737.
Posters:
2020
Li J., M. Lakshminarasimhan, X. Wu, Ang Li, C. Olschanowsky, K. Barker. A Parallel Sparse Tensor Benchmark Suite on CPUs and GPUs. Principles and Practice of Parallel Programming (PPoPP). 2020. (Poster) PNNL-SA-150292.
Miao Z., J. C. Calhoun, R. Ge, J. Li. Sparsity-Aware Distributed Tensor Decomposition. ACM/IEEE International Conference for High-Performance Computing, Networking, Storage, and Analysis (SC). 2020. (Poster) PNNL-SA-155621
IP Generation:
A Parallel Sparse Tensor Algorithm Benchmark Suite (PASTA) https://gitlab.com/tensorworld/pasta
HiParTI: A Hierarchical Parallel Tensor Infrastructure https://github.com/pnnl/HiParTI
Segmented Global Address Space (SGAS): A Memory-Centric Programming Model and Runtime – A Lumsdaine
Conference Proceedings:
2021
Lumsdaine A., L. D'Alessandro, K. Deweese, J.S. Firoz, T. Liu, S. Mcmillan, and J.P. Ratzloff, et al. 2022. “NWGraph: A Library of Generic Graph Algorithms and Data Structures in C++20.” In 36th European Conference on Object-Oriented Programming (ECOOP 2022), June 6-10, 2022, Berlin, Germany. Leibniz International Proceedings in Informatics, LIPIcs, edited by K. Ali and J. Vitek, 222, 31:1 – 31:28. Dagstuhl: Schloss agstuhl – Leibniz-Zentrum. PNNL-SA-173390. doi:10.4230/LIPIcs.ECOOP.2022.31
2020
Azad M., M.M. Aznaveh, S. Beamer, M. Blanco, J. Chen, L. D'Alessandro, and R. Dathathri, et al. 2020. "Evaluation of Graph Analytics Frameworks Using the GAP Benchmark Suite." In IEEE International Symposium on Workload Characterization (IISWC 2020), October 27-30, 2020, Beijing, China. 216-227. IEEE. Piscataway, New Jersey. PNNL-SA-154466. doi:10.1109/IISWC50251.2020.00029
Liu X.T., M. Halappanavar, K. J. Barker, A. Lumsdaine, and A. H. Gebremedhin. 2020. “Direction-optimizing label propagation and its application to community detection.” In Proceedings of the 17th ACM International Conference on Computing Frontiers, CF 2020, Catania, Sicily, Italy, May 11-13, 2020, 2020, pp. 192–201, doi: 10.1145/3387902.3392634.
IP Generation:
P17093: Graph Library Proposal to ISO C++ Standards Committee
Fixing Amdahl’s Law within the Limits of Accelerated Systems (FALLACY) – A Marquez
Publications:
2021
Tan C., C. Xie, T. Geng, A. Marquez, A. Tumeo, K.J. Barker, and A. Li. 2021. "ARENA: Asynchronous Reconfigurable Accelerator Ring to Enable Data-Centric Parallel Computing." IEEE Transactions on Parallel and Distributed Systems 32, no. 12:2880-2892. PNNL-SA-152862. doi:10.1109/TPDS.2021.3081074
2020
Kilic O.O., C. Xie, N.R. Tallent, A. Marquez, and R.D. Friese. 2020. "Fast Memory Tracing for Reducing the Dominant Cost of Computation." Online Conference, Washington. PNNL-SA-153966.
Kilic O.O., C. Xie, N.R. Tallent, A. Marquez, and R.D. Friese. 2020. "Fallacy Fixing Amdahl’s Law within the Limits of Accelerated Systems." Richland, Washington. PNNL-SA-152249.
Kilic O.O., N.R. Tallent, and R.D. Friese. 2020. "Rapid Memory Footprint Access Diagnostics." In IEEE International Symposium on Performance Analysis of Systems and Software. PNNL-SA-155625.
Marquez A., N.R. Tallent, O.O. Kilic, C. Xie, and R.D. Friese. 2020. "FALLACY Fixing Amdahl’s Law within the Limits of Accelerated Systems." Richland, Washington. PNNL-SA-153427.
Conference Proceedings:
2022
Kilic O.O., N.R. Tallent, Y. Suriyakumar, C. Xie, A. Marquez, and S. Eranian. 2022. "MemGaze: Rapid and Effective Load-Level Memory Trace Analysis." In IEEE International Conference on Cluster Computing (CLUSTER 2022), September 5-8, 2022, Heidelberg, Germany, 484-495. Piscataway, New Jersey: IEEE. PNNL-SA-174803. doi:10.1109/CLUSTER51413.2022.00058
IP Generation:
MemGaze: https://github.com/pnnl/memgaze
A Compiler Infrastructure for Data-Model Convergence (DuoMO) – G Kestor
Publications:
2021
Kestor G. 2021. "COMET: Domain Specific Compilation in Multi-level IR." Online, Washington. PNNL-SA-168331.
Kestor G., E. Mutlu, and R. Gioiosa. 2021. "Co-Design through Domain-Specific Compilation Framework." Abstract submitted to ASCR Workshop on Reimagining Codesign, Online, Washington. PNNL-SA-160162.
Tian R., L. Guo, and G. Kestor. 2021. "Sparse tensor algebra optimizations in MLIR." In 2021 LLVM DEVELOPERS' MEETING. PNNL-SA-168325.
Tian R., L. Guo, J. Li, B. Ren, and G. Kestor. 2021. "A High Performance Sparse Tensor Algebra Compiler in MLIR." In IEEE/ACM 7th Workshop on the LLVM Compiler Infrastructure in HPC (LLVM-HPC 2021), November 14, 2021, St. Louis, MO, 27-38. Piscataway, New Jersey: IEEE. PNNL-SA-168094. doi:10.1109/LLVMHPC54804.2021.00009
2020
Kestor G. 2020. "DuoMO: A compiler infrastructure for Data MOdel convergence." Presented by G. Kestor at University of Utah Lightning Talks, Richland, Washington. PNNL-SA-151951.
Mutlu E., R. Tian, B. Ren, S. Krishnamoorthy, R. Gioiosa, J. Pienaar, and G. Kestor. 2020. "COMET: A Domain-Specific Compilation of High-Performance Computational Chemistry." Presented by E. Mutlu at MLIR Design Meeting, Online Meeting, United States. PNNL-SA-157864.
Mutlu E., R. Tian, B. Ren, S. Krishnamoorthy, R. Gioiosa, J. Pienaar, and G. Kestor. 2020. "COMET: A Domain-Specific Compilation of High-Performance Computational Chemistry." Presented by E. Mutlu at The Workshop on Languages and Compilers for Parallel Computing, Online Conference, New York. PNNL-SA-157110.
Tian R., and G. Kestor. 2020. "Automatic code generation for Sparse computational kernels in MLIR." Online, Washington. PNNL-SA-168328.
Conference Proceedings:
2022
Mutlu E., R. Tian, B. Ren, S. Krishnamoorthy, R. Gioiosa, J. Pienaar, and G. Kestor. 2022. "COMET: A Domain-Specific Compilation of High-Performance Computational Chemistry." In Proceedings of the 33rd International Workshop on Languages and Compilers for Parallel Computing, (LCPC 2020), October 14-16 2020, Virtual, Online. Lecture Notes in Computer Science, edited by B. Chapman, J. Moreira, 13149, 87 - 103. PNNL-SA-155440. doi:10.1007/978-3-030-95953-1_7
2021
Jeong G., G. Kestor, P. Chatarasi, A. Parashar, P. Tsa, S. Rajamanickam, and R. Gioiosa, et al. 2021. "Union: A Unified HW-SW Co-Design Ecosystem in MLIR for Evaluating Tensor Operations on Spatial Accelerators." In Proceedings of the 30th International Conference on Parallel Architectures and Compilation Techniques (PACT 2021), September 22-29, 2021, Atlanta, GA, 30-44. Los Alamitos, California: IEEE Computer Society. PNNL-SA-168329. doi:10.1109/PACT52795.2021.00010
Tian R., L. Guo, J. Li, B. Ren, and G. Kestor. 2021. "A High Performance Sparse Tensor Algebra Compiler in MLIR." In IEEE/ACM 7th Workshop on the LLVM Compiler Infrastructure in HPC (LLVM-HPC 2021), November 14, 2021, St. Louis, MO, 27-38. Piscataway, New Jersey: IEEE. PNNL-SA-168094. doi:10.1109/LLVMHPC54804.2021.00009
2020
Mutlu E., R. Tian, B. Ren, S. Krishnamoorthy, R. Gioiosa, J. Pienaar, and G. Kestor. 2022. "COMET: A Domain-Specific Compilation of High-Performance Computational Chemistry." In Proceedings of the 33rd International Workshop on Languages and Compilers for Parallel Computing, (LCPC 2020), October 14-16, 2020, Virtual, Online. Lecture Notes in Computer Science, edited by B. Chapman, J. Moreira, 13149, 87 - 103. PNNL-SA-155440. doi:10.1007/978-3-030-95953-1_7
IP Generation
COMET: https://github.com/pnnl/COMET
Application-Algorithm-Architecture Co-Design for Large-Scale, Sparse Tensor/Matrix Methods (HiParTI) – C Xie
Publications:
2021
Xie C., J. Chen, J.S. Firoz, J. Li, S. Song, K.J. Barker, and M.V. Raugas, et al. 2021. "Fast and Scalable Sparse Triangular Solver for Multi-GPU Based HPC Architectures." In 50th International Conference on Parallel Processing (ICPP-21), August 9-12, 2021, Lermont, IL, Article No. 53, pages 1-11. New York, New York: Association for Computing Machinery. PNNL-SA-150878. doi:10.1145/3472456.3472478
2020
Hein E., S. Eswar, A. Yasar, J. Li, J.S. Young, T. Conte, and U. Catalyurek, et al. 2020. "Programming Strategies for Irregular Algorithms on the Emu Chick." ACM Transactions on Parallel Computing 7, no. 4: Article No. 25. PNNL-SA-144460. doi:10.1145/3418077
Li J., M. Lakshminarasimhan, X. Wu, A. Li, C. Olschanowsky, and K.J. Barker. 2020. "A Sparse Tensor Benchmark Suite for CPUs and GPUs." In IEEE International Symposium on Workload Characterization (IISWC 2020), October 27-30, 2020, Beijing, China, 193-204. Piscataway, New Jersey: IEEE. PNNL-SA-142736. doi:10.1109/IISWC50251.2020.00027
Navier: Dataflow Architecture for Computation Chemistry – R Gioiosa
Publications:
2022
Ashraf R.A., and R. Gioiosa. 2022. "Exploring the Use of Novel Spatial Accelerators in Scientific Applications." In Proceedings of the ACM/SPEC International Conference on Performance Engineering (ICPE 2022), April 9-13, 2022, Beijing, China, 47-58. New York, New York: Association for Computing Machinery. PNNL-SA-169884. doi:10.1145/3489525.3511690
Mutlu E., R. Tian, B. Ren, S. Krishnamoorthy, R. Gioiosa, J. Pienaar, and G. Kestor. 2022. "COMET: A Domain-Specific Compilation of High-Performance Computational Chemistry." In Proceedings of the 33rd International Workshop on Languages and Compilers for Parallel Computing (LCPC 2020), October 14-16 2020, Virtual, Online. Lecture Notes in Computer Science, edited by B. Chapman, J. Moreira, 13149, 87 - 103. PNNL-SA-155440. doi:10.1007/978-3-030-95953-1_7
2021
Liu J., J. Ren, R. Gioiosa, D. Li, and J. Li. 2021."Sparta: high-performance, element-wise sparse tensor contraction on heterogeneous memory." In Proceedings of the 26th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (PPoPP '21). Association for Computing Machinery, New York, NY, USA, 318–333. PNNL-SA-155439. doi: 10.1145/3437801.3441581
2020
Kamatar A.V., R.D. Friese, and R. Gioiosa. 2020. "Locality-Aware Scheduling for Scalable Heterogeneous Environments." In IEEE/ACM International Workshop on Runtime and Operating Systems for Supercomputers (ROSS 2020), November 13, 2020, Virtual Event, 50-58. Los Alamitos, California: IEEE Computer Society. PNNL-SA-157073. doi:10.1109/ROSS51935.2020.00011
Presentations:
2022
Gioiosa R. "Re-Imagining HW/SW Co-Design: a Flexible, Composable, and Agile approach." Invited talk at the 2022 CRNCH Summit, GTech, Virtual
Gioiosa R. "Introduction to Navier." Collaboration meeting with AMD/Xilinx.
Gioiosa R. "MCL Overview." Collaboration meeting with AMD/Xilinx.
Kestor G. and R. Gioiosa. "Introduction to COMET." Collaboration meeting with AMD/Xilinx.
2021
Gioiosa R. 10/01/2021. "Programming Extremely Heterogeneous Systems with the Minos Computing Library." Presented by R. Gioiosa at Computational Research Leadership Council (CRLC) Seminar Series, Online Conference, United States. PNNL-SA-168061.
Gioiosa R. "Re-Imagining HW/SW Co-Design for Extremely Heterogeneous Systems." Invited keynote at the 2021 Heterogeneity in Computing Workshop, in conjunction with IPDPS21, VirtuaI.
Software and Data Releases:
MCL v 0.5
MCL v 0.6
Synergistic Activities:
2023
PPoPP2023 - Basic MCL Programming tutorial
2022
PPoPP2022 - Basic MCL Programming tutorial
2021
PPoPP2021 - Basic MCL Programming tutorial
ICS2021 - Basic MCL Programming tutorial