Search Results for author: Vijay Janapa Reddi

Found 43 papers, 18 papers with code

Leveraging Residue Number System for Designing High-Precision Analog Deep Neural Network Accelerators

no code implementations15 Jun 2023 Cansu Demirkiran, Rashmi Agrawal, Vijay Janapa Reddi, Darius Bunandar, Ajay Joshi

In addition, we show that RNS can reduce the energy consumption of the data converters within an analog accelerator by several orders of magnitude compared to a regular fixed-point approach.

Datasheets for Machine Learning Sensors

no code implementations15 Jun 2023 Matthew Stewart, Pete Warden, Yasmine Omri, Shvetank Prakash, Joao Santos, Shawn Hymel, Benjamin Brown, Jim MacArthur, Nat Jeffries, Brian Plancher, Vijay Janapa Reddi

Machine learning (ML) sensors offer a new paradigm for sensing that enables intelligence at the edge while empowering end-users with greater control of their data.

NeuroBench: Advancing Neuromorphic Computing through Collaborative, Fair and Representative Benchmarking

no code implementations10 Apr 2023 Jason Yik, Soikat Hasan Ahmed, Zergham Ahmed, Brian Anderson, Andreas G. Andreou, Chiara Bartolozzi, Arindam Basu, Douwe den Blanken, Petrut Bogdan, Sander Bohte, Younes Bouhadjar, Sonia Buckley, Gert Cauwenberghs, Federico Corradi, Guido de Croon, Andreea Danielescu, Anurag Daram, Mike Davies, Yigit Demirag, Jason Eshraghian, Jeremy Forest, Steve Furber, Michael Furlong, Aditya Gilra, Giacomo Indiveri, Siddharth Joshi, Vedant Karia, Lyes Khacef, James C. Knight, Laura Kriener, Rajkumar Kubendran, Dhireesha Kudithipudi, Gregor Lenz, Rajit Manohar, Christian Mayr, Konstantinos Michmizos, Dylan Muir, Emre Neftci, Thomas Nowotny, Fabrizio Ottati, Ayca Ozcelikkale, Noah Pacik-Nelson, Priyadarshini Panda, Sun Pao-Sheng, Melika Payvand, Christian Pehle, Mihai A. Petrovici, Christoph Posch, Alpha Renner, Yulia Sandamirskaya, Clemens JS Schaefer, André van Schaik, Johannes Schemmel, Catherine Schuman, Jae-sun Seo, Sadique Sheik, Sumit Bam Shrestha, Manolis Sifalakis, Amos Sironi, Kenneth Stewart, Terrence C. Stewart, Philipp Stratmann, Guangzhi Tang, Jonathan Timcheck, Marian Verhelst, Craig M. Vineyard, Bernhard Vogginger, Amirreza Yousefzadeh, Biyan Zhou, Fatima Tuz Zohora, Charlotte Frenkel, Vijay Janapa Reddi

The field of neuromorphic computing holds great promise in terms of advancing computing efficiency and capabilities by following brain-inspired principles.


Is TinyML Sustainable? Assessing the Environmental Impacts of Machine Learning on Microcontrollers

no code implementations27 Jan 2023 Shvetank Prakash, Matthew Stewart, Colby Banbury, Mark Mazumder, Pete Warden, Brian Plancher, Vijay Janapa Reddi

This article discusses both the potential of these TinyML applications to address critical sustainability challenges, as well as the environmental footprint of this emerging technology.

GPU-based Private Information Retrieval for On-Device Machine Learning Inference

1 code implementation26 Jan 2023 Maximilian Lam, Jeff Johnson, Wenjie Xiong, Kiwan Maeng, Udit Gupta, Yang Li, Liangzhen Lai, Ilias Leontiadis, Minsoo Rhu, Hsien-Hsin S. Lee, Vijay Janapa Reddi, Gu-Yeon Wei, David Brooks, G. Edward Suh

Together, for various on-device ML applications such as recommendation and language modeling, our system on a single V100 GPU can serve up to $100, 000$ queries per second -- a $>100 \times$ throughput improvement over a CPU-based baseline -- while maintaining model accuracy.

Information Retrieval Language Modelling +1

Edge Impulse: An MLOps Platform for Tiny Machine Learning

no code implementations2 Nov 2022 Shawn Hymel, Colby Banbury, Daniel Situnayake, Alex Elium, Carl Ward, Mat Kelcey, Mathijs Baaijens, Mateusz Majchrzycki, Jenny Plunkett, David Tischler, Alessandro Grande, Louis Moreau, Dmitry Maslov, Artie Beavis, Jan Jongboom, Vijay Janapa Reddi

Edge Impulse is a cloud-based machine learning operations (MLOps) platform for developing embedded and edge ML (TinyML) systems that can be deployed to a wide range of hardware targets.

Machine Learning Sensors

1 code implementation7 Jun 2022 Pete Warden, Matthew Stewart, Brian Plancher, Colby Banbury, Shvetank Prakash, Emma Chen, Zain Asgar, Sachin Katti, Vijay Janapa Reddi

Machine learning sensors represent a paradigm shift for the future of embedded machine learning applications.

BIG-bench Machine Learning

Zhuyi: Perception Processing Rate Estimation for Safety in Autonomous Vehicles

no code implementations6 May 2022 Yu-Shun Hsiao, Siva Kumar Sastry Hari, Michał Filipiuk, Timothy Tsai, Michael B. Sullivan, Vijay Janapa Reddi, Vasu Singh, Stephen W. Keckler

The processing requirement of autonomous vehicles (AVs) for high-accuracy perception in complex scenarios can exceed the resources offered by the in-vehicle computer, degrading safety and comfort.

Autonomous Vehicles

Tabula: Efficiently Computing Nonlinear Activation Functions for Secure Neural Network Inference

no code implementations5 Mar 2022 Maximilian Lam, Michael Mitzenmacher, Vijay Janapa Reddi, Gu-Yeon Wei, David Brooks

Multiparty computation approaches to secure neural network inference traditionally rely on garbled circuits for securely executing nonlinear activation functions.

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

no code implementations5 Jan 2022 Shvetank Prakash, Tim Callahan, Joseph Bushagour, Colby Banbury, Alan V. Green, Pete Warden, Tim Ansell, Vijay Janapa Reddi

In this paper, we present CFU Playground: a full-stack open-source framework that enables rapid and iterative design and evaluation of machine learning (ML) accelerators for embedded ML systems.

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

no code implementations17 Nov 2021 Daniel Galvez, Greg Diamos, Juan Ciro, Juan Felipe Cerón, Keith Achorn, Anjali Gopi, David Kanter, Maximilian Lam, Mark Mazumder, Vijay Janapa Reddi

The People's Speech is a free-to-download 30, 000-hour and growing supervised conversational English speech recognition dataset licensed for academic and commercial usage under CC-BY-SA (with a CC-BY subset).

speech-recognition Speech Recognition +1

Tabula: Efficiently Computing Nonlinear Activation Functions for Private Neural Network Inference

1 code implementation29 Sep 2021 Max Lam, Michael Mitzenmacher, Vijay Janapa Reddi, Gu-Yeon Wei, David Brooks

Multiparty computation approaches to private neural network inference require significant communication between server and client, incur tremendous runtime penalties, and cost massive storage overheads.

Few-Shot Keyword Spotting in Any Language

2 code implementations3 Apr 2021 Mark Mazumder, Colby Banbury, Josh Meyer, Pete Warden, Vijay Janapa Reddi

With just five training examples, we fine-tune the embedding model for keyword spotting and achieve an average F1 score of 0. 75 on keyword classification for 180 new keywords unseen by the embedding model in these nine languages.

Keyword Spotting Transfer Learning

Data Engineering for Everyone

no code implementations23 Feb 2021 Vijay Janapa Reddi, Greg Diamos, Pete Warden, Peter Mattson, David Kanter

This article shows that open-source data sets are the rocket fuel for research and innovation at even some of the largest AI organizations.

BIG-bench Machine Learning

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

1 code implementation8 Feb 2021 James Gleeson, Srivatsan Krishnan, Moshe Gabel, Vijay Janapa Reddi, Eyal de Lara, Gennady Pekhimenko

Deep reinforcement learning (RL) has made groundbreaking advancements in robotics, data center management and other applications.

Management reinforcement-learning +1

AutoPilot: Automating SoC Design Space Exploration for SWaP Constrained Autonomous UAVs

no code implementations5 Feb 2021 Srivatsan Krishnan, Zishen Wan, Kshitij Bhardwaj, Paul Whatmough, Aleksandra Faust, Sabrina Neuman, Gu-Yeon Wei, David Brooks, Vijay Janapa Reddi

Balancing a computing system for a UAV requires considering both the cyber (e. g., sensor rate, compute performance) and physical (e. g., payload weight) characteristics that affect overall performance.

Bayesian Optimization BIG-bench Machine Learning +1

Benchmarking TinyML Systems: Challenges and Direction

2 code implementations10 Mar 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

In this position paper, we present the current landscape of TinyML and discuss the challenges and direction towards developing a fair and useful hardware benchmark for TinyML workloads.


Quantized Neural Network Inference with Precision Batching

no code implementations26 Feb 2020 Maximilian Lam, Zachary Yedidia, Colby Banbury, Vijay Janapa Reddi

We present PrecisionBatching, a quantized inference algorithm for speeding up neural network execution on traditional hardware platforms at low bitwidths without the need for retraining or recalibration.

Language Modelling Natural Language Inference +1

GLADAS: Gesture Learning for Advanced Driver Assistance Systems

no code implementations2 Oct 2019 Ethan Shaotran, Jonathan J. Cruz, Vijay Janapa Reddi

To the best of our knowledge, GLADAS is the first system of its kind designed to provide an infrastructure for further research into human-AV interaction.

Hand Gesture Recognition Hand-Gesture Recognition +1

AdaptivFloat: A Floating-point based Data Type for Resilient Deep Learning Inference

no code implementations29 Sep 2019 Thierry Tambe, En-Yu Yang, Zishen Wan, Yuntian Deng, Vijay Janapa Reddi, Alexander Rush, David Brooks, Gu-Yeon Wei

Conventional hardware-friendly quantization methods, such as fixed-point or integer, tend to perform poorly at very low word sizes as their shrinking dynamic ranges cannot adequately capture the wide data distributions commonly seen in sequence transduction models.


Learning to Seek: Autonomous Source Seeking with Deep Reinforcement Learning Onboard a Nano Drone Microcontroller

1 code implementation25 Sep 2019 Bardienus P. Duisterhof, Srivatsan Krishnan, Jonathan J. Cruz, Colby R. Banbury, William Fu, Aleksandra Faust, Guido C. H. E. de Croon, Vijay Janapa Reddi

We present fully autonomous source seeking onboard a highly constrained nano quadcopter, by contributing application-specific system and observation feature design to enable inference of a deep-RL policy onboard a nano quadcopter.

Autonomous Navigation Efficient Exploration +2

Deep Reinforcement Learning for Cyber Security

no code implementations13 Jun 2019 Thanh Thi Nguyen, Vijay Janapa Reddi

The scale of Internet-connected systems has increased considerably, and these systems are being exposed to cyber attacks more than ever.

Intrusion Detection reinforcement-learning +1

Air Learning: A Deep Reinforcement Learning Gym for Autonomous Aerial Robot Visual Navigation

1 code implementation2 Jun 2019 Srivatsan Krishnan, Behzad Boroujerdian, William Fu, Aleksandra Faust, Vijay Janapa Reddi

We find that the trajectories on an embedded Ras-Pi are vastly different from those predicted on a high-end desktop system, resulting in up to 40% longer trajectories in one of the environments.

Benchmarking Reinforcement Learning (RL) +1

Domain Specific Approximation for Object Detection

no code implementations4 Oct 2018 Ting-Wu Chin, Chia-Lin Yu, Matthew Halpern, Hasan Genc, Shiao-Li Tsao, Vijay Janapa Reddi

There is growing interest in object detection in advanced driver assistance systems and autonomous robots and vehicles.

object-detection Object Detection

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