Benjamin Hawks

According to our database, Benjamin Hawks authored at least 8 papers between 2020 and 2024.

Collaborative distances:

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

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

2022

FastML Science Benchmarks: Accelerating Real-Time Scientific Edge Machine Learning.

Javier M. Duarte, Nhan Tran, Benjamin Hawks, Christian Herwig, Jules Muhizi, Shvetank Prakash, Vijay Janapa Reddi

CoRR, 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

QONNX: Representing Arbitrary-Precision Quantized Neural Networks.

Alessandro Pappalardo, Yaman Umuroglu, Michaela Blott, Jovan Mitrevski, Benjamin Hawks, Nhan Tran, Vladimir Loncar, Sioni Summers, Hendrik Borras, Jules Muhizi, Matthew Trahms, Shih-Chieh Hsu, Scott Hauck, Javier M. Duarte

CoRR, 2022

2021

Ps and Qs: Quantization-Aware Pruning for Efficient Low Latency Neural Network Inference.

Benjamin Hawks, Javier M. Duarte, Nicholas J. Fraser, Alessandro Pappalardo, Nhan Tran, Yaman Umuroglu

Frontiers Artif. Intell., 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

hls4ml: An Open-Source Codesign Workflow to Empower Scientific Low-Power Machine Learning Devices.

Farah Fahim, Benjamin Hawks, Christian Herwig, James Hirschauer, Sergo Jindariani, Nhan Tran, Luca P. Carloni, Giuseppe Di Guglielmo, Philip C. Harris, Jeffrey D. Krupa, Dylan S. Rankin, Manuel Blanco Valentin, Josiah D. Hester, Yingyi Luo, John Mamish, Seda Ogrenci Memik, Thea Aarrestad, Hamza Javed, Vladimir Loncar, Maurizio Pierini, Adrian Alan Pol, Sioni Summers, Javier M. Duarte, Scott Hauck, Shih-Chieh Hsu, Jennifer Ngadiuba, Mia Liu, Duc Hoang, Edward Kreinar, Zhenbin Wu

CoRR, 2021

2020

GPU-Accelerated Machine Learning Inference as a Service for Computing in Neutrino Experiments.

Michael Wang, Tingjun Yang, Maria Acosta Flechas, Philip C. Harris, Benjamin Hawks, Burt Holzman, Kyle Knoepfel, Jeffrey D. Krupa, Kevin Pedro, Nhan Tran

Frontiers Big Data, 2020