Olivia Weng

18 papers A 3Misc 2Journal 11Unranked 2
YearRankTypeTitle / Venue / Authors
2026 — conf
PrioriFI: More Informed Fault Injection for Edge Neural Networks.
ASPLOS (2)
Olivia Weng, Andres Meza, Nhan Tran, Ryan Kastner
2025 A conf
Greater than the Sum of its LUTs: Scaling Up LUT-based Neural Networks with AmigoLUT.
FPGA
Olivia Weng, Marta Andronic, Danial Zuberi, Jiaqing Chen, Caleb Geniesse, George A. Constantinides, Nhan Tran, Nicholas J. Fraser, Javier Mauricio Duarte, Ryan Kastner
2025 J jnl
Loss Landscape Analysis for Reliable Quantized ML Models for Scientific Sensing.
CoRR
Tommaso Baldi, Javier Campos, Olivia Weng, Caleb Geniesse, Nhan Tran, Ryan Kastner, Alessandro Biondi
2024 J jnl
Architectural Implications of Neural Network Inference for High Data-Rate, Low-Latency Scientific Applications.
CoRR
Olivia Weng, Alexander Redding, Nhan Tran, Javier Mauricio Duarte, Ryan Kastner
2024 — conf
Pentimento: Data Remanence in Cloud FPGAs.
ASPLOS (2)
Colin Drewes, Olivia Weng, Andres Meza, Alric Althoff, David Kohlbrenner, Ryan Kastner, Dustin Richmond
2024 Misc conf
Reliable edge machine learning hardware for scientific applications.
VTS
Tommaso Baldi, Javier Campos, Benjamin Hawks, Jennifer Ngadiuba, Nhan Tran, Daniel Diaz, Javier M. Duarte, Ryan Kastner, Andres Meza, Melissa Quinnan, Olivia Weng, Caleb Geniesse, Amir Gholami, Michael W. Mahoney, Vladimir Loncar, Philip C. Harris, Joshua Agar, Shuyu Qin
2024 J jnl
Reliable edge machine learning hardware for scientific applications.
CoRR
Tommaso Baldi, Javier Campos, Benjamin Hawks, Jennifer Ngadiuba, Nhan Tran, Daniel Diaz, Javier M. Duarte, Ryan Kastner, Andres Meza, Melissa Quinnan, Olivia Weng, Caleb Geniesse, Amir Gholami, Michael W. Mahoney, Vladimir Loncar, Philip C. Harris, Joshua Agar, Shuyu Qin
2024 J jnl
Tailor: Altering Skip Connections for Resource-Efficient Inference.
ACM Trans. Reconfigurable Technol. Syst.
Olivia Weng, Gabriel Marcano, Vladimir Loncar, Alireza Khodamoradi, G. Abarajithan, Nojan Sheybani, Andres Meza, Farinaz Koushanfar, Kristof Denolf, Javier Mauricio Duarte, Ryan Kastner
2024 J jnl
Turn on, Tune in, and Listen up: Maximizing Side-Channel Recovery in Cross-Platform Time-to-Digital Converters.
ACM Trans. Reconfigurable Technol. Syst.
Colin Drewes, Tyler Sheaves, Olivia Weng, Keegan Ryan, Bill Hunter, Christopher McCarty, Ryan Kastner, Dustin Richmond
2023 A conf
Adapting Skip Connections for Resource-Efficient FPGA Inference.
FPGA
Olivia Weng, Gabriel Marcano, Vladimir Loncar, Alireza Khodamoradi, Nojan Sheybani, Farinaz Koushanfar, Kristof Denolf, Javier Mauricio Duarte, Ryan Kastner
2023 J jnl
Pentimento: Data Remanence in Cloud FPGAs.
CoRR
Colin Drewes, Olivia Weng, Andres Meza, Alric Althoff, David Kohlbrenner, Ryan Kastner, Dustin Richmond
2023 J jnl
Tailor: Altering Skip Connections for Resource-Efficient Inference.
CoRR
Olivia Weng, Gabriel Marcano, Vladimir Loncar, Alireza Khodamoradi, Nojan Sheybani, Farinaz Koushanfar, Kristof Denolf, Javier Mauricio Duarte, Ryan Kastner
2023 A conf
Turn on, Tune in, Listen up: Maximizing Side-Channel Recovery in Time-to-Digital Converters.
FPGA
Colin Drewes, Olivia Weng, Keegan Ryan, Bill Hunter, Christopher McCarty, Ryan Kastner, Dustin Richmond
2022 J jnl
Open-source FPGA-ML codesign for the MLPerf Tiny Benchmark.
CoRR
Hendrik Borras, Giuseppe Di Guglielmo, Javier M. Duarte, Nicolò Ghielmetti, Benjamin Hawks, Scott Hauck, Shih-Chieh Hsu, Ryan Kastner, Jason Liang, Andres Meza, Jules Muhizi, Tai Nguyen, Rushil Roy, Nhan Tran, Yaman Umuroglu, Olivia Weng, Aidan Yokuda, Michaela Blott
2021 Misc conf
A Tunable Dual-Edge Time-to-Digital Converter.
FCCM
Colin Drewes, Steven Harris, Winnie Wang, Richard Appen, Olivia Weng, Ryan Kastner, William Hunter, Christopher McCarty, Dustin Richmond
2021 J jnl
Applications and Techniques for Fast Machine Learning in Science.
CoRR
Allison McCarn Deiana, Nhan Tran, Joshua Agar, Michaela Blott, Giuseppe Di Guglielmo, Javier M. Duarte, Philip C. Harris, Scott Hauck, Mia Liu, Mark S. Neubauer, Jennifer Ngadiuba, Seda Ogrenci Memik, Maurizio Pierini, Thea Aarrestad, Steffen Bähr, Jürgen Becker, Anne-Sophie Berthold, Richard J. Bonventre, Tomás E. Müller-Bravo, Markus Diefenthaler, Zhen Dong, Nick Fritzsche, Amir Gholami, Ekaterina Govorkova, Kyle J. Hazelwood, Christian Herwig, Babar Khan, Sehoon Kim, Thomas Klijnsma, Yaling Liu, Kin Ho Lo, Tri Nguyen, Gianantonio Pezzullo, Seyedramin Rasoulinezhad, Ryan A. Rivera, Kate Scholberg, Justin Selig, Sougata Sen, Dmitri Strukov, William Tang, Savannah Thais, Kai Lukas Unger, Ricardo Vilalta, Belinavon Krosigk, Thomas K. Warburton, Maria Acosta Flechas, Anthony Aportela, Thomas Calvet, Leonardo Cristella, Daniel Diaz, Caterina Doglioni, Maria Domenica Galati, Elham E Khoda, Farah Fahim, Davide Giri, Benjamin Hawks, Duc Hoang, Burt Holzman, Shih-Chieh Hsu, Sergo Jindariani, Iris Johnson, Raghav Kansal, Ryan Kastner, Erik Katsavounidis, Jeffrey D. Krupa, Pan Li, Sandeep Madireddy, Ethan Marx, Patrick McCormack, Andres Meza, Jovan Mitrevski, Mohammed Attia Mohammed, Farouk Mokhtar, Eric A. Moreno, Srishti Nagu, Rohin Narayan, Noah Palladino, Zhiqiang Que, Sang Eon Park, Subramanian Ramamoorthy, Dylan S. Rankin, Simon Rothman, Ashish Sharma, Sioni Summers, Pietro Vischia, Jean-Roch Vlimant, Olivia Weng
2021 J jnl
Hardware-efficient Residual Networks for FPGAs.
CoRR
Olivia Weng, Alireza Khodamoradi, Ryan Kastner
2021 J jnl
Neural Network Quantization for Efficient Inference: A Survey.
CoRR
Olivia Weng