no code implementations • 11 May 2022 • Sabrina M. Neuman, Brian Plancher, Bardienus P. Duisterhof, Srivatsan Krishnan, Colby Banbury, Mark Mazumder, Shvetank Prakash, Jason Jabbour, Aleksandra Faust, Guido C. H. E. de Croon, Vijay Janapa Reddi
Machine learning (ML) has become a pervasive tool across computing systems.
no code implementations • 5 Jan 2022 • Shvetank Prakash, Tim Callahan, Joseph Bushagour, Colby Banbury, Alan V. Green, Pete Warden, Tim Ansell, Vijay Janapa Reddi
We present CFU Playground, a full-stack open-source framework that enables rapid and iterative design of machine learning (ML) accelerators for embedded ML systems.
1 code implementation • 14 Jun 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
Advancements in ultra-low-power tiny machine learning (TinyML) systems promise to unlock an entirely new class of smart applications.
no code implementations • 7 Jun 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
Broadening access to both computational and educational resources is critical to diffusing machine-learning (ML) innovation.
1 code implementation • 3 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.
1 code implementation • 21 Oct 2020 • Colby Banbury, Chuteng Zhou, Igor Fedorov, Ramon Matas Navarro, Urmish Thakker, Dibakar Gope, Vijay Janapa Reddi, Matthew Mattina, Paul N. Whatmough
To address this challenge, neural architecture search (NAS) promises to help design accurate ML models that meet the tight MCU memory, latency and energy constraints.
Ranked #1 on
Keyword Spotting
on Google Speech Commands V2 12
no code implementations • 26 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.