Publications

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1.

Shail Dave; Tony Nowatzki; Aviral Shrivastava

Explainable-DSE: An Agile and Explainable Exploration of Efficient Hardware/Software Codesigns of Deep Learning Accelerators Using Bottleneck Analysis Proceedings Article

In: Proceedings of the 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS), 2024, (Won Silver Medal at ACM Student Research Competition 2022-23 (Host: ACM SIGBED)).

Abstract | BibTeX | Tags: Accelerated Computing, Machine Learning, Machine Learning Accelerators | Links:

2.

Shail Dave; Aviral Shrivastava

Automating the Architectural Execution Modeling and Characterization of Domain-Specific Architectures Conference

Proceedings of the TECHCON, 2023.

Abstract | BibTeX | Tags: Accelerated Computing, Machine Learning, Machine Learning Accelerators | Links:

3.

Yi Hu; Chaoran Zhang; Edward Andert; Harshul Singh; Aviral Shrivastava; James Laudon; Yanqi Zhou; Bob Iannucci; Carlee Joe-Wong

GiPH: Generalizable Placement Learning for Adaptive Heterogeneous Computing Proceedings Article

In: Proceedings of the Sixth Conference on Machine Learning and Systems (MLSys), 2023.

BibTeX | Tags: Accelerated Computing, Machine Learning, Machine Learning Accelerators, Real-Time Systems

4.

Behnaz Ranjbar; Florian Klemme; Paul R. Genssler; Hussam Amrouch; Jinhyo Jung; Shail Dave; Hwisoo So; Kyongwoo Lee; Aviral Shrivastava; Ji-Yung Lin; Pieter Weckx; Subrat Mishra; Francky Catthoor; Dwaipayan Biswas; Akash Kumar

Learning-Oriented Reliability Improvement of Computing Systems From Transistor to Application Level Proceedings Article

In: Proceedings of the 26th International Conference on Design Automation and Test in Europe (DATE), 2023.

BibTeX | Tags: Efficient Embedded Computing, Error Correction, Error Resilience, Machine Learning, Machine Learning Accelerators, Soft Error | Links:

5.

Aviral Shrivastava; Xiaobo Sharon Hu

Report on the 2022 Embedded Systems Week (ESWEEK) Journal Article

In: IEEE Design & Test, vol. 40, iss. 1, pp. 108-111, 2023.

Abstract | BibTeX | Tags: Accelerated Computing, CPS, Efficient Embedded Computing, Error Resilience, Machine Learning Accelerators, Real-Time Systems | Links:

6.

Shail Dave; Alberto Marchisio; Muhammad Abdullah Hanif; Amira Guesmi; Aviral Shrivastava; Ihsen Alouani; Muhammad Shafique

Special Session: Towards an Agile Design Methodology for Efficient, Reliable, and Secure ML Systems Proceedings Article

In: Proceedings of the 2022 IEEE 40th VLSI Test Symposium (VTS), 2022.

Abstract | BibTeX | Tags: Accelerated Computing, Efficient Embedded Computing, Error Resilience, Machine Learning, Machine Learning Accelerators, Soft Error | Links:

7.

Shail Dave; Aviral Shrivastava

Design Space Description Language for Automated and Comprehensive Exploration of Next-Gen Hardware Accelerators Workshop

Workshop on Languages, Tools, and Techniques for Accelerator Design (LATTE), 2022, (co-located with ACM International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS).).

Abstract | BibTeX | Tags: Accelerated Computing, CGRA, Machine Learning, Machine Learning Accelerators | Links:

8.

Shail Dave; Riyadh Baghdadi; Tony Nowatzki; Sasikanth Avancha; Aviral Shrivastava; Baoxin Li

Hardware Acceleration of Sparse and Irregular Tensor Computations of ML Models: A Survey and Insights Journal Article

In: Proceedings of the IEEE (PIEEE), 2021, (arXiv: 2007.00864).

BibTeX | Tags: Accelerated Computing, CGRA, Low-power Computing, Machine Learning, Machine Learning Accelerators | Links:

9.

Shail Dave; Aviral Shrivastava; Youngbin Kim; Sasikanth Avancha; Kyoungwoo Lee

dMazeRunner: Optimizing Convolutions on Dataflow Accelerators Proceedings Article

In: ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020, (Invited).

BibTeX | Tags: Accelerated Computing, Machine Learning, Machine Learning Accelerators | Links:

10.

Shail Dave; Youngbin Kim; Sasikanth Avancha; Kyoungwoo Lee; Aviral Shrivastava

DMazeRunner: Executing Perfectly Nested Loops on Dataflow Accelerators Journal Article

In: ACM Transactions on Embedded Computing Systems (TECS), vol. 18, no. 5s, 2019, (Special Issue on ESWEEK 2019 - Proceedings of the International Conference on Hardware/Software Codesign and System Synthesis (CODES+ISSS)).

BibTeX | Tags: Accelerated Computing, Machine Learning, Machine Learning Accelerators | Links: