Olivia Weng

According to our database, Olivia Weng authored at least 17 papers between 2021 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Design Rules for Extreme-Edge Scientific Computing on AI Engines.

Zhenghua Ma, G. Abarajithan, Dimitrios Danopoulos, Olivia Weng, Francesco Restuccia, Ryan Kastner

CoRR, April, 2026

PrioriFI: More Informed Fault Injection for Edge Neural Networks.

Olivia Weng, Andres Meza, Nhan Tran, Ryan Kastner

Proceedings of the 31st ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2026

2025

Loss Landscape Analysis for Reliable Quantized ML Models for Scientific Sensing.

Tommaso Baldi, Javier Campos, Olivia Weng, Caleb Geniesse, Nhan Tran, Ryan Kastner, Alessandro Biondi

CoRR, February, 2025

Greater than the Sum of its LUTs: Scaling Up LUT-based Neural Networks with AmigoLUT.

Olivia Weng, Marta Andronic, Danial Zuberi, Jiaqing Chen, Caleb Geniesse, George A. Constantinides, Nhan Tran, Nicholas J. Fraser, Javier Mauricio Duarte, Ryan Kastner

Proceedings of the 2025 ACM/SIGDA International Symposium on Field Programmable Gate Arrays, 2025

2024

Turn on, Tune in, and Listen up: Maximizing Side-Channel Recovery in Cross-Platform Time-to-Digital Converters.

Colin Drewes, Tyler Sheaves, Olivia Weng, Keegan Ryan, Bill Hunter, Christopher McCarty, Ryan Kastner, Dustin Richmond

ACM Trans. Reconfigurable Technol. Syst., September, 2024

Tailor: Altering Skip Connections for Resource-Efficient Inference.

Olivia Weng, Gabriel Marcano, Vladimir Loncar, Alireza Khodamoradi, G. Abarajithan, Nojan Sheybani, Andres Meza, Farinaz Koushanfar, Kristof Denolf, Javier Mauricio Duarte, Ryan Kastner

ACM Trans. Reconfigurable Technol. Syst., March, 2024

Architectural Implications of Neural Network Inference for High Data-Rate, Low-Latency Scientific Applications.

Olivia Weng, Alexander Redding, Nhan Tran, Javier Mauricio Duarte, Ryan Kastner

CoRR, 2024

Reliable edge machine learning hardware for scientific applications.

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

Proceedings of the 42nd IEEE VLSI Test Symposium, 2024

Pentimento: Data Remanence in Cloud FPGAs.

Colin Drewes, Olivia Weng, Andres Meza, Alric Althoff, David Kohlbrenner, Ryan Kastner, Dustin Richmond

Proceedings of the 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2024

2023

Tailor: Altering Skip Connections for Resource-Efficient Inference.

Olivia Weng, Gabriel Marcano, Vladimir Loncar, Alireza Khodamoradi, Nojan Sheybani, Farinaz Koushanfar, Kristof Denolf, Javier Mauricio Duarte, Ryan Kastner

CoRR, 2023

Adapting Skip Connections for Resource-Efficient FPGA Inference.

Olivia Weng, Gabriel Marcano, Vladimir Loncar, Alireza Khodamoradi, Nojan Sheybani, Farinaz Koushanfar, Kristof Denolf, Javier Mauricio Duarte, Ryan Kastner

Proceedings of the 2023 ACM/SIGDA International Symposium on Field Programmable Gate Arrays, 2023

Turn on, Tune in, Listen up: Maximizing Side-Channel Recovery in Time-to-Digital Converters.

Colin Drewes, Olivia Weng, Keegan Ryan, Bill Hunter, Christopher McCarty, Ryan Kastner, Dustin Richmond

Proceedings of the 2023 ACM/SIGDA International Symposium on Field Programmable Gate Arrays, 2023

2022

Open-source FPGA-ML codesign for the MLPerf Tiny Benchmark.

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

CoRR, 2022

2021

Neural Network Quantization for Efficient Inference: A Survey.

Olivia Weng

CoRR, 2021

Applications and Techniques for Fast Machine Learning in Science.

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

CoRR, 2021

Hardware-efficient Residual Networks for FPGAs.

Olivia Weng, Alireza Khodamoradi, Ryan Kastner

CoRR, 2021

A Tunable Dual-Edge Time-to-Digital Converter.

Colin Drewes, Steven Harris, Winnie Wang, Richard Appen, Olivia Weng, Ryan Kastner, William Hunter, Christopher McCarty, Dustin Richmond

Proceedings of the 29th IEEE Annual International Symposium on Field-Programmable Custom Computing Machines, 2021