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CFU Playground: Full-Stack Open-Source Framework for Tiny Machine Learning (tinyML) Acceleration on FPGAs


Jan 05, 2022
Shvetank Prakash, Tim Callahan, Joseph Bushagour, Colby Banbury, Alan V. Green, Pete Warden, Tim Ansell, Vijay Janapa Reddi


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The People's Speech: A Large-Scale Diverse English Speech Recognition Dataset for Commercial Usage


Nov 17, 2021
Daniel Galvez, Greg Diamos, Juan Ciro, Juan Felipe Cerón, Keith Achorn, Anjali Gopi, David Kanter, Maximilian Lam, Mark Mazumder, Vijay Janapa Reddi

* Part of 2021 Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 

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Roofline Model for UAVs:A Bottleneck Analysis Tool for Designing Compute Systems for Autonomous Drones


Nov 13, 2021
Srivatsan Krishnan, Zishen Wan, Kshitij Bhardwaj, Aleksandra Faust, Vijay Janapa Reddi


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Analyzing and Improving Fault Tolerance of Learning-Based Navigation Systems


Nov 09, 2021
Zishen Wan, Aqeel Anwar, Yu-Shun Hsiao, Tianyu Jia, Vijay Janapa Reddi, Arijit Raychowdhury

* Accepted in 58th ACM/IEEE Design Automation Conference (DAC), 2021 

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MedPerf: Open Benchmarking Platform for Medical Artificial Intelligence using Federated Evaluation


Oct 08, 2021
Alexandros Karargyris, Renato Umeton, Micah J. Sheller, Alejandro Aristizabal, Johnu George, Srini Bala, Daniel J. Beutel, Victor Bittorf, Akshay Chaudhari, Alexander Chowdhury, Cody Coleman, Bala Desinghu, Gregory Diamos, Debo Dutta, Diane Feddema, Grigori Fursin, Junyi Guo, Xinyuan Huang, David Kanter, Satyananda Kashyap, Nicholas Lane, Indranil Mallick, Pietro Mascagni, Virendra Mehta, Vivek Natarajan, Nikola Nikolov, Nicolas Padoy, Gennady Pekhimenko, Vijay Janapa Reddi, G Anthony Reina, Pablo Ribalta, Jacob Rosenthal, Abhishek Singh, Jayaraman J. Thiagarajan, Anna Wuest, Maria Xenochristou, Daguang Xu, Poonam Yadav, Michael Rosenthal, Massimo Loda, Jason M. Johnson, Peter Mattson


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GRiD: GPU-Accelerated Rigid Body Dynamics with Analytical Gradients


Sep 14, 2021
Brian Plancher, Sabrina M. Neuman, Radhika Ghosal, Scott Kuindersma, Vijay Janapa Reddi

* 8 pages, 5 figures, 1 data table 

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AutoSoC: Automating Algorithm-SOC Co-design for Aerial Robots


Sep 13, 2021
Srivatsan Krishnan, Thierry Tambe, Zishen Wan, Vijay Janapa Reddi

* Class Project for CS249r: Special Topics on Edge Computing (Autonomous Machines) 

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RoboRun: A Robot Runtime to Exploit Spatial Heterogeneity


Aug 30, 2021
Behzad Boroujerdian, Radhika Ghosal, Jonathan Cruz, Brian Plancher, Vijay Janapa Reddi

* will be published in Design Automation Conference (DAC) 2021 

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Sniffy Bug: A Fully Autonomous Swarm of Gas-Seeking Nano Quadcopters in Cluttered Environments


Jul 12, 2021
Bardienus P. Duisterhof, Shushuai Li, Javier Burgués, Vijay Janapa Reddi, Guido C. H. E. de Croon


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MLPerf Tiny Benchmark


Jun 28, 2021
Colby Banbury, Vijay Janapa Reddi, Peter Torelli, Jeremy Holleman, Nat Jeffries, Csaba Kiraly, Pietro Montino, David Kanter, Sebastian Ahmed, Danilo Pau, Urmish Thakker, Antonio Torrini, Peter Warden, Jay Cordaro, Giuseppe Di Guglielmo, Javier Duarte, Stephen Gibellini, Videet Parekh, Honson Tran, Nhan Tran, Niu Wenxu, Xu Xuesong

* TinyML Benchmark 

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Gradient Disaggregation: Breaking Privacy in Federated Learning by Reconstructing the User Participant Matrix


Jun 10, 2021
Maximilian Lam, Gu-Yeon Wei, David Brooks, Vijay Janapa Reddi, Michael Mitzenmacher

* ICML 2021 

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Widening Access to Applied Machine Learning with TinyML


Jun 09, 2021
Vijay Janapa Reddi, Brian Plancher, Susan Kennedy, Laurence Moroney, Pete Warden, Anant Agarwal, Colby Banbury, Massimo Banzi, Matthew Bennett, Benjamin Brown, Sharad Chitlangia, Radhika Ghosal, Sarah Grafman, Rupert Jaeger, Srivatsan Krishnan, Maximilian Lam, Daniel Leiker, Cara Mann, Mark Mazumder, Dominic Pajak, Dhilan Ramaprasad, J. Evan Smith, Matthew Stewart, Dustin Tingley

* Understanding the underpinnings of the TinyML edX course series: https://www.edx.org/professional-certificate/harvardx-tiny-machine-learning 

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MAVFI: An End-to-End Fault Analysis Framework with Anomaly Detection and Recovery for Micro Aerial Vehicles


May 27, 2021
Yu-Shun Hsiao, Zishen Wan, Tianyu Jia, Radhika Ghosal, Arijit Raychowdhury, David Brooks, Gu-Yeon Wei, Vijay Janapa Reddi

* 14 pages, 16 figures 

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Few-Shot Keyword Spotting in Any Language


Apr 22, 2021
Mark Mazumder, Colby Banbury, Josh Meyer, Pete Warden, Vijay Janapa Reddi

* Submitted to INTERSPEECH 2021 

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RL-Scope: Cross-Stack Profiling for Deep Reinforcement Learning Workloads


Mar 04, 2021
James Gleeson, Srivatsan Krishnan, Moshe Gabel, Vijay Janapa Reddi, Eyal de Lara, Gennady Pekhimenko

* RL-Scope is an open-source tool available at https://github.com/UofT-EcoSystem/rlscope . Proceedings of the 4th MLSys Conference, 2021. Changes: camera ready for MLSys publication -- shorten abstract, add acknowledgements, minor grammar fixes 

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Data Engineering for Everyone


Feb 23, 2021
Vijay Janapa Reddi, Greg Diamos, Pete Warden, Peter Mattson, David Kanter


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Machine Learning-Based Automated Design Space Exploration for Autonomous Aerial Robots


Feb 05, 2021
Srivatsan Krishnan, Zishen Wan, Kshitij Bharadwaj, Paul Whatmough, Aleksandra Faust, Sabrina Neuman, Gu-Yeon Wei, David Brooks, Vijay Janapa Reddi


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MLPerf Mobile Inference Benchmark: Why Mobile AI Benchmarking Is Hard and What to Do About It


Dec 03, 2020
Vijay Janapa Reddi, David Kanter, Peter Mattson, Jared Duke, Thai Nguyen, Ramesh Chukka, Kenneth Shiring, Koan-Sin Tan, Mark Charlebois, William Chou, Mostafa El-Khamy, Jungwook Hong, Michael Buch, Cindy Trinh, Thomas Atta-fosu, Fatih Cakir, Masoud Charkhabi, Xiaodong Chen, Jimmy Chiang, Dave Dexter, Woncheol Heo, Guenther Schmuelling, Maryam Shabani, Dylan Zika


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MicroNets: Neural Network Architectures for Deploying TinyML Applications on Commodity Microcontrollers


Oct 25, 2020
Colby Banbury, Chuteng Zhou, Igor Fedorov, Ramon Matas Navarro, Urmish Thakker, Dibakar Gope, Vijay Janapa Reddi, Matthew Mattina, Paul N. Whatmough

* 10 pages, 8 figures, 3 tables, appendix 

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TensorFlow Lite Micro: Embedded Machine Learning on TinyML Systems


Oct 20, 2020
Robert David, Jared Duke, Advait Jain, Vijay Janapa Reddi, Nat Jeffries, Jian Li, Nick Kreeger, Ian Nappier, Meghna Natraj, Shlomi Regev, Rocky Rhodes, Tiezhen Wang, Pete Warden


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Benchmarking TinyML Systems: Challenges and Direction


Mar 10, 2020
Colby R. Banbury, Vijay Janapa Reddi, Max Lam, William Fu, Amin Fazel, Jeremy Holleman, Xinyuan Huang, Robert Hurtado, David Kanter, Anton Lokhmotov, David Patterson, Danilo Pau, Jae-sun Seo, Jeff Sieracki, Urmish Thakker, Marian Verhelst, Poonam Yadav

* 5 pages, 1 figure, 2 tables 

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Quantized Neural Network Inference with Precision Batching


Feb 26, 2020
Maximilian Lam, Zachary Yedidia, Colby Banbury, Vijay Janapa Reddi


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MLPerf Inference Benchmark


Nov 06, 2019
Vijay Janapa Reddi, Christine Cheng, David Kanter, Peter Mattson, Guenther Schmuelling, Carole-Jean Wu, Brian Anderson, Maximilien Breughe, Mark Charlebois, William Chou, Ramesh Chukka, Cody Coleman, Sam Davis, Pan Deng, Greg Diamos, Jared Duke, Dave Fick, J. Scott Gardner, Itay Hubara, Sachin Idgunji, Thomas B. Jablin, Jeff Jiao, Tom St. John, Pankaj Kanwar, David Lee, Jeffery Liao, Anton Lokhmotov, Francisco Massa, Peng Meng, Paulius Micikevicius, Colin Osborne, Gennady Pekhimenko, Arun Tejusve Raghunath Rajan, Dilip Sequeira, Ashish Sirasao, Fei Sun, Hanlin Tang, Michael Thomson, Frank Wei, Ephrem Wu, Lingjie Xu, Koichi Yamada, Bing Yu, George Yuan, Aaron Zhong, Peizhao Zhang, Yuchen Zhou


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