Publications

Google Scholar

ORCID ID

Publications

Journal, Conference, and Workshop Papers

• Mapping Spiking Neural Networks to Heterogeneous Crossbar Architectures using Integer Linear Programming, Devin Pohl, Aaron Young, Kazi Asifuzzaman, Narasinga Rao Miniskar, Jeffrey S. Vetter, To be published in DATE’25, 2025.
• Neuromorphic Computing for Nuclear Safeguards, A. D. Nicholson, J. Ghawaly, C. Schuman, B. Witherspoon, A. Young, M. Swinney, 2024 IEEE Nuclear Science Symposium (NSS), Medical Imaging Conference (MIC) and Room Temperature Semiconductor Detector Conference (RTSD), 2024.
• Neuro-Spark: A Submicrosecond Spiking Neural Networks Architecture for In-Sensor Filtering, Narsinga Rao Miniskar, Aaron R. Young, Kazi Asifuzzaman, Shruti Kulkarni, Prasanna Date, Alice Bean, 2024 International Conference on Neuromorphic Systems (ICONS), 2024.
• OR22-Neuromorphic Rad Detector-PD3Ra Final Report, James Ghawaly, Andrew Nicholson, Cathrine Schuman, Mathew Swinney, Brett Witherspoon, Aaron Young, Final Report, ORNL/SPR-2024/3423, 2024.
• Deep Co-design, with Cross-discipline Teams, Leveraging State of the Art Technology to Push Neuromorphic Computing Forward, Aaron Young, ASCR Neuromorphic Computing for Science Workshop, 2024.
• Smart pixel sensors: towards on-sensor filtering of pixel clusters with deep learning, Jieun Yoo, Jennet Dickinson, Morris Swartz, Giuseppe Di Guglielmo, Alice Bean, Douglas Berry, Manuel Blanco Valentin, Karri DiPetrillo, Farah Fahim, Lindsey Gray, James Hirschauer, Shruti R Kulkarni, Ron Lipton, Petar Maksimovic, Corrinne Mills, Mark S Neubauer, Benjamin Parpillon, Gauri Pradhan, Chinar Syal, Nhan Tran, Dahai Wen, and Aaron Young, Machine Learning: Science and Technology, Volume 5, Number 3, 2024.
• IRIS Reimagined: Advancements in Intelligent Runtime System for Task-Based Programming, Narasinga Rao Miniskar, Seyong Lee, Johnston Beau, Aaron Young, Mohammad Alaul Haque Monil, Valero-Pedro Lara, and Jeffrey S Vetter, WAMTA 2024, 2024.
• Event-Driven Sensing and Embedded Neuromorphic Platforms for Gamma Radiation Monitoring, Brett Witherspoon, Aaron Young, Proceedings of the Great Lakes Symposium on VLSI 2024, 2024.
• An FPGA-Based Neuromorphic Processor with All-to-All Connectivity, Disha Maheshwari, Aaron Young, Prasanna Date, Shruti Kulkarni, Brett Witherspoon, Narsinga Rao Miniskar, 2023 IEEE International Conference on Rebooting Computing (ICRC), 2023.
• Arithmetic Primitives for Efficient Neuromorphic Computing, Ahna Wurm, Rebecca Seay, Prasanna Date, Shruti Kulkarni, Aaron Young, Jeffrey Vetter, 2023 IEEE International Conference on Rebooting Computing (ICRC), 2023.
• Smart pixel sensors: towards on-sensor filtering of pixel clusters with deep learning (arXiv), Jieun Yoo, Jennet Dickinson, Morris Swartz, Giuseppe Di Guglielmo, Alice Bean, Douglas Berry, Manuel Blanco Valentin, Karri DiPetrillo, Farah Fahim, Lindsey Gray, James Hirschauer, Shruti R. Kulkarni, Ron Lipton, Petar Maksimovic, Corrinne Mills, Mark S. Neubauer, Benjamin Parpillon, Gauri Pradhan, Chinar Syal, Nhan Tran, Dahai Wen, Aaron Young, arXiv, 2023.
• On-Sensor Data Filtering using Neuromorphic Computing for High Energy Physics Experiments, Shruti R. Kulkarni, Aaron Young, Prasanna Date, Narasinga Rao Miniskar, Jeffrey Vetter, Farah Fahim, Benjamin Parpillon, Jennet Dickinson, Nhan Tran, Jieun Yoo, Corrinne Mills, Morris Swartz, Petar Maksimovic, Catherine Schuman, Alice Bean, ICONS ‘23: Proceedings of the 2023 International Conference on Neuromorphic Systems, 2023.
• Performance Optimization Study of the Neuromorphic Radiation Anomaly Detector, James Ghawaly, Aaron Young, Andrew Nicholson, Brett Witherspoon, Nick Prins, Mathew Swinney, Cihangir Celik, Catherine Schuman, Karan Patel, ICONS ‘23: Proceedings of the 2023 International Conference on Neuromorphic Systems, 2023.
• On-Sensor Data Filtering using Neuromorphic Computing for High Energy Physics Experiments (arXiv), Shruti R. Kulkarni, Aaron Young, Prasanna Date, Narasinga Rao Miniskar, Jeffrey S. Vetter, Farah Fahim, Benjamin Parpillon, Jennet Dickinson, Nhan Tran, Jieun Yoo, Corrinne Mills, Morris Swartz, Petar Maksimovic, Catherine D. Schuman, Alice Bean, arXiv: Accepted at ICONS 2023, 2023.
• A 3D Implementation of Convolutional Neural Network for Fast Inference, Narasinga Rao Miniskar, Pruek Vanna-Iampikul, Aaron Young, Sung Kyu Lim, Frank Liu, Jieun Yoo, Corrinne Mills, Nhan Tran, Farah Fahim, Jeffrey S Vetter, 2023 IEEE International Symposium on Circuits and Systems (ISCAS), 2023.
• Abisko: Deep codesign of an architecture for spiking neural networks using novel neuromorphic materials, Jeffrey S. Vetter, Prasanna Date, Farah Fahim, Shruti R. Kulkarni, Petro Maksymovych, A. Alec Talin, Marc Gonzalez Tallada, Pruek Vanna-iampikul, Aaron R. Young, David Brooks, Yu Cao, Wei Gu-Yeon, Sung Kyu Lim, Frank Liu, Matthew Marinella, Bobby Sumpter and Narasinga Rao Miniskar, The International Journal of High Performance Computing Applications, 2023.
• Encoding Integers and Rationals on Neuromorphic Computers using Virtual Neuron, Prasanna Date, Shruti Kulkarni, Aaron Young, Catherine Schuman, Thomas Potok, Jeffrey Vetter, Sci Rep 13, 2022.
• Virtual Neuron: A Neuromorphic Approach for Encoding Numbers, Prasanna Date, Shruti Kulkarni, Aaron Young, Catherine Schuman, Thomas Potok, Jeffrey S. Vetter, 2022 IEEE International Conference on Rebooting Computing (ICRC), 2022.
• Encoding Integers and Rationals on Neuromorphic Computers using Virtual Neuron (arXiv), Prasanna Date, Shruti Kulkarni, Aaron Young, Catherine Schuman, Thomas Potok, Jeffrey Vetter, arXiv: Accepted at Sci Rep 13, 2022.
• Adrastea: An Efficient FPGA Design Environment for Heterogeneous Scientific Computing and Machine Learning, Aaron R. Young, Narasinga Rao Miniskar, Frank Liu, Willem Blokland, Jeffrey S. Vetter, Smoky Mountains Computational Sciences and Engineering Conference (SMC 2022), 2023.
• Ultra Low Latency Machine Learning for Scientific Edge Applications , Narasinga Rao Miniskar, Aaron Young, Frank Liu, Willem Blokland, Anthony Cabrera, Jeffery S. Vetter, 2022 32nd International Conference on Field-Programmable Logic and Applications (FPL), 2022.
• A survey on processing-in-memory techniques: Advances and challenges, Kazi Asifuzzaman, Narasinga Rao Miniskar, Aaron R. Young, Frank Liu, Jeffrey S. Vetter, Memories - Materials, Devices, Circuits and Systems, 2022.
• A Neuromorphic Algorithm for Radiation Anomaly Detection, James Ghawaly, Aaron Young, Dan Archer, Nick Prins, Brett Witherspoon, Catherine Schuman, Proceedings of the International Conference on Neuromorphic Systems 2022, 2022.
• Design and Analysis of CXL Performance Models for Tightly-Coupled Heterogeneous Computing, Anthony M. Cabrera, Aaron R. Young, Jeffrey S. Vetter, ExHET ‘22: Proceedings of the 1st International Workshop on Extreme Heterogeneity Solutions, 2022.
• Heterogeneous Memory System Framework for HPC, Kazi Asifuzzaman, Narasinga Rao Miniskar, Aaron R. Young, Frank Liu, and Jeffrey S. Vetter, ASCR Workshop on the Management and Storage of Scientific Data, 2022.
• A Hierarchical Task Scheduler for Heterogeneous Computing, Narasinga Rao Miniskar, Frank Liu, Aaron R. Young, Dwaipayan Chakraborty, Jeffrey S. Vetter, International Conference on High Performance Computing, 2021, 57-76.
• Toward Evaluating High-Level Synthesis Portability and Performance between Intel and Xilinx FPGAs, Anthony Cabrera, Aaron Young, Jacob Lambert, Zhili Xiao, Amy An, Seyong Lee, Zheming Jin, Jungwon Kim, Jeremy Buhler, Roger Chamberlain, and Jeffrey Vetter, IWOCL’21: International Workshop on OpenCL, 2021.
• Emerging Heterogeneous Systems Provide Great Opportunities for Codesign, Aaron R. Young, Jeffrey S. Vetter, Frank Liu, Narasinga Rao Miniskar, Sarat Sreepathi, and Anthony M. Cabrera, ASCR Workshop on Reimagining Codesign, 2021.
• SNACC: The Scaled-up Neuromorphic Array Communications Controller, Aaron R. Young, PhD Dissertation, University of Tennessee, 2020.
• Scaled-up Neuromorphic Array Communications Controller (SNACC) for Large-scale Neural Networks, A. R. Young, A. Z. Foshie, M. E. Dean, J. S. Plank, G. S. Rose, J. P. Mitchell, and C. D. Schuman, IJCNN: The International Joint Conference on Neural Networks, 2020.
• A Review of Spiking Neuromorphic Hardware Communication Systems, A. R. Young, M. E. Dean, J. S. Plank and G. S. Rose, in IEEE Access, vol. 7, pp. 135606-135620, 2019.
• Understanding Selection and Diversity for Evolution of Spiking Recurrent Neural Networks, Catherine D. Shuman, Grant Bruer, Aaron R. Young, Mark Dean and James S. Plank, IJCNN: The International Joint Conference on Neural Networks, 2018.
• Neuromorphic Array Communications Controller to Support Large-Scale Neural Networks, Aaron R. Young, Mark E. Dean, James S. Plank, Garrett S. Rose and Catherine D. Schuman, IJCNN: The International Joint Conference on Neural Networks, 2018.
• Scalable High-Speed Communications for Neuromorphic Systems, Young, A. Masters Thesis, University of Tennessee, 2017.
• DANNA: A Neuromorphic Software Ecosystem, Adam Disney, John Reynolds, Catherine D. Schuman, Aleksander Klibisz, Aaron Young, and James S. Plank, Biologically Inspired Cognitive Architectures, Volume 9, 2016.
• Second Creek Monitoring, Whitaker, Haley; Young, Aaron; Wagner, Ryan; Haque, Saajid; Parrott, Benjamin; and Fagan, Richard, (2016). Chancellor’s Honors Program Projects.

Reports

• Hardware Evaluation Analytical Modeling and Node Simulation: Benefits of Tighter GPU Integration, Brian Austin, Ray Bair, Kevin Barker, Anthony Cabrera, Andrew Chien, Nan Ding, Jesun Firoz, Khaled Ibrahim, Joseph Manzano, Vitali Morozov, Tan Nguyen, Leonid Oliker, Joshua Suetterlein, Li Tang, Jeffrey Vetter, Samuel Williams, Kazutomo Yoshii, Aaron Young, Lawrence Berkeley National Laboratory, ECP-HIHE01-35, 2021.

Posters

• Poster: Neuromorphic Array Communications Controller, Aaron R. Young and Mark E. Dean, JDRD Symposium, 2019.
• Poster: DANNA Neuromorphic Application Development Kit Demo, Mark Dean, Aaron Young, Parker Mitchell, Patricia Eckhart, John Reynolds, Grant Bruer, Adam Disney, James Plank, and Catherine Schuman. 5th Neuro Inspired Computational Elements Workshop (NICE 2017), 2017.

Patents

• Hierarchical task scheduling for accelerators, Narasinga Rao Miniskar, Frank Y Liu, Aaron R Young, Jeffrey S Vetter, Dwaipayan Chakraborty, US-17542022, 2022.

Awards

• R&D 100 Award Winner for IRIS-SDK: Intelligent Runtime System for Extremely Heterogeneous Computer Architectures, 2024