Runtime Task Scheduling Using Imitation Learning for Heterogeneous Many-Core Systems Krishnakumar, A; Arda, S E; Goksoy, A A; Mandal, S K; Ogras, U Y; Sartor, A L; Marculescu, R IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 39 (11), pp. 4064-4077, 2020. Links@article{9211494,
title = {Runtime Task Scheduling Using Imitation Learning for Heterogeneous Many-Core Systems},
author = {A. {Krishnakumar} and S. E. {Arda} and A. A. {Goksoy} and S. K. {Mandal} and U. Y. {Ogras} and A. L. {Sartor} and R. {Marculescu}},
url = {https://ieeexplore.ieee.org/document/9211494},
doi = {10.1109/TCAD.2020.3012861},
year = {2020},
date = {2020-10-02},
journal = {IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems},
volume = {39},
number = {11},
pages = {4064-4077},
keywords = {},
pubstate = {published},
tppubtype = {article}
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DS3: A system-level domain-specific system-on-chip simulation framework Arda, Samet; Anish, NK; Goksoy, Ahmet Alper; Mack, Joshua; Kumbhare, Nirmal; Sartor, Anderson Luiz; Akoglu, Ali; Marculescu, Radu; Ogras, Umit Y IEEE Transactions on Computers, 2020. Links@article{arda2020ds3,
title = {DS3: A system-level domain-specific system-on-chip simulation framework},
author = {Samet Arda and NK Anish and Ahmet Alper Goksoy and Joshua Mack and Nirmal Kumbhare and Anderson Luiz Sartor and Ali Akoglu and Radu Marculescu and Umit Y Ogras},
url = {https://arxiv.org/abs/2003.09016},
year = {2020},
date = {2020-01-01},
journal = {IEEE Transactions on Computers},
publisher = {IEEE},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
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HiLITE: Hierarchical and Lightweight Imitation Learning for Power Management of Embedded SoCs Sartor, Anderson L; Krishnakumar, Anish; Arda, Samet E; Ogras, Umit Y; Marculescu, Radu IEEE Computer Architecture Letters, 19 (1), pp. 63–67, 2020. Links@article{sartor2020hilite,
title = {HiLITE: Hierarchical and Lightweight Imitation Learning for Power Management of Embedded SoCs},
author = {Anderson L Sartor and Anish Krishnakumar and Samet E Arda and Umit Y Ogras and Radu Marculescu},
url = {https://ieeexplore.ieee.org/document/9085952},
year = {2020},
date = {2020-01-01},
journal = {IEEE Computer Architecture Letters},
volume = {19},
number = {1},
pages = {63--67},
publisher = {IEEE},
keywords = {},
pubstate = {published},
tppubtype = {article}
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Runtime Task Scheduling using Imitation Learning for Heterogeneous Many-Core Systems Krishnakumar, Anish; Arda, Samet E; Goksoy, Alper A; Mandal, Sumit K; Ogras, Umit Y; Sartor, Anderson L; Marculescu, Radu arXiv preprint arXiv:2007.09361, 2020. Links@article{krishnakumar2020runtime,
title = {Runtime Task Scheduling using Imitation Learning for Heterogeneous Many-Core Systems},
author = {Anish Krishnakumar and Samet E Arda and Alper A Goksoy and Sumit K Mandal and Umit Y Ogras and Anderson L Sartor and Radu Marculescu},
url = {https://arxiv.org/abs/2007.09361},
year = {2020},
date = {2020-01-01},
journal = {arXiv preprint arXiv:2007.09361},
keywords = {},
pubstate = {published},
tppubtype = {article}
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Edge AI: Systems Design and ML for IoT Data Analytics Marculescu, Radu; Marculescu, Diana; Ogras, Umit Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, pp. 3565–3566, 2020. Links@inproceedings{marculescu2020edge,
title = {Edge AI: Systems Design and ML for IoT Data Analytics},
author = {Radu Marculescu and Diana Marculescu and Umit Ogras},
url = {https://sites.google.com/utexas.edu/edgeaitutorial/home?authuser=0},
year = {2020},
date = {2020-01-01},
booktitle = {Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining},
pages = {3565--3566},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
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From Physical Processes to Theoretical Foundations of Cyber-Physical Systems Design and Optimization Bogdan, Paul; Marculescu, Radu Principles of Cyber-Physical Systems: An Interdisciplinary Approach, pp. 3, 2020. Links@article{bogdan20201,
title = {From Physical Processes to Theoretical Foundations of Cyber-Physical Systems Design and Optimization},
author = {Paul Bogdan and Radu Marculescu},
url = {https://books.google.com/books?hl=en&lr=&id=2UUBEAAAQBAJ&oi=fnd&pg=PA3&dq=From+Physical+Processes+to+Theoretical+Foundations+of+Cyber-Physical+Systems+Design+and+Optimization&ots=MR0VdHIMSA&sig=vJz2eqBCDO8PDd6a2QEAQpKLyig#v=onepage&q=From%20Physical%20Processes%20to%20Theoretical%20Foundations%20of%20Cyber-Physical%20Systems%20Design%20and%20Optimization&f=false},
year = {2020},
date = {2020-01-01},
journal = {Principles of Cyber-Physical Systems: An Interdisciplinary Approach},
pages = {3},
publisher = {Cambridge University Press},
keywords = {},
pubstate = {published},
tppubtype = {article}
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Embedded Systems
Embedded systems are computer systems that perform dedicated functions while being parts of a larger system. Our research targets primarily heterogeneous many-core System on a Chip (SoC) platforms where communication happens via the network-on-chip. These SoCs should be designed to meet aggressive performance requirements, while coping with limited battery capacity, thermal design power, and real-time constraints. Over the years, we have considered deterministic, probabilistic, and statistical physics-inspired design paradigms. Lately, our research targets machine learning approaches (e.g., imitation and reinforcement learning) for performance and energy optimization and resource management in heterogeneous SoC platforms.
Cyber-Physical Systems
Cyber-physical systems (CPS) refer to a new generation of networked embedded systems that bring together sensing, computation, communication, control and actuation in order to sustain a continuous interaction with the physical world (e.g., processes taking place on electrical power grids, transportation and traffic roads, communication and financial networks, medical devices, smart buildings, etc.). Physical processes are predominantly non-stationary in nature and require time-dependent models for understanding their behavior. Our research focuses on accurate modeling physical processes to better understand the theoretical foundations of CPS design and optimization.