Dot-product engine for neuromorphic computing: programming 1T1M crossbar to accelerate matrix-vector multiplication. - Miao Hu 002; John Paul Strachan; Zhiyong Li; Emmanuelle M. Grafals; Noraica Davila; Catherine Graves; Sity Lam; Ning Ge 001; Jianhua Joshua Yang; R. Stanley Williams (DAC, 2016)

Generalize or Die: Operating Systems Support for Memristor-Based Accelerators. - Pedro Bruel; Sai Rahul Chalamalasetti; Chris I. Dalton; Izzat El Hajj; Alfredo Goldman; Catherine Graves; Wen-Mei W. Hwu; Phil Laplante; Dejan S. Milojicic; Geoffrey Ndu; John Paul Strachan (ICRC, 2017)

Regular Expression Matching with Memristor TCAMs. - Catherine E. Graves; Wen Ma; Xia Sheng; Brent Buchanan; Le Zheng; Sity Lam; Xuema Li; Sai Rahul Chalamalasetti; Lennie Kiyama; Martin Foltin; Matthew P. Hardy; John Paul Strachan (ICRC, 2018)

Large Memristor Crossbars for Analog Computing. - Can Li; Yunning Li; Hao Jiang 017; Wenhao Song; Peng Lin; Zhongrui Wang; J. Joshua Yang; Qiangfei Xia; Miao Hu 002; Eric Montgomery; Jiaming Zhang; Noraica Dávila; et al. (ISCAS, 2018)

Regular Expression Matching with Memristor TCAMs for Network Security. - Catherine E. Graves; Wen Ma; Xia Sheng; Brent Buchanan; Le Zheng; Sity Lam; Xuema Li; Sai Rahul Chalamalasetti; Lennie Kiyama; Martin Foltin; John Paul Strachan; Matthew P. Hardy (NANOARCH, 2018)

The Art and Science of Constructing a Memristor Model: Updated. - Suhas Kumar; Gary Gibson; Catherine E. Graves; Matthew D. Pickett; John Paul Strachan; R. Stanley Williams (Handbook of Memristor Networks, 2019)

High performance, power efficient hardware accelerators: emerging devices, circuits and architecture co-design. - Catherine Graves (CF, 2019)

Future Computing Systems (FCS) to Support "Understanding" Capability. - Raymond G. Beausoleil; Thomas Van Vaerenbergh; Kirk Bresniker; Catherine Graves; Kimberly Keeton; Suhas Kumar; Can Li; Dejan S. Milojicic; Sergey Serebryakov; John Paul Strachan (ICRC, 2019)

Analog content addressable memories with memristors. - Can Li; Catherine E. Graves; Darrin Miller; John Paul Strachan (CoRR, 2019)

Tree-based machine learning performed in-memory with memristive analog CAM. - Giacomo Pedretti; Catherine E. Graves; Can Li; Sergey Serebryakov; Xia Sheng; Martin Foltin; Ruibin Mao; John Paul Strachan (CoRR, 2021)

A general tree-based machine learning accelerator with memristive analog CAM. - Giacomo Pedretti; Sergey Serebryakov; John Paul Strachan; Catherine E. Graves (ISCAS, 2022)

Experimentally realized memristive memory augmented neural network. - Ruibin Mao; Bo Wen; Yahui Zhao; Arman Kazemi; Ann Franchesca Laguna; Michael T. Niemier; X. Sharon Hu; Xia Sheng; Catherine E. Graves; John Paul Strachan; Can Li (CoRR, 2022)

ReRAM-based graph attention network with node-centric edge searching and hamming similarity. - Ruibin Mao; Xia Sheng; Catherine Graves; Cong Xu; Can Li (DAC, 2023)

Design Space Exploration of Analog CAM for Tree-Based Models. - Aishwarya Natarajan; Luca Buonanno; Todd Richmond; David Vickers; Xia Sheng; John Moon; Darrin Miller; Giacomo Pedretti; Catherine Graves; Jim Ignowski (MWSCAS, 2023)

X-TIME: An in-memory engine for accelerating machine learning on tabular data with CAMs. - Giacomo Pedretti; John Moon; Pedro Bruel; Sergey Serebryakov; Ron M. Roth; Luca Buonanno; Tobias Ziegler 006; Cong Xu; Martin Foltin; Paolo Faraboschi; Jim Ignowski; Catherine E. Graves (CoRR, 2023)

CAMSHAP: Accelerating Machine Learning Model Explainability with Analog CAM. - John Moon; Giacomo Pedretti; Pedro Bruel; Sergey Serebryakov; Omar Eldash; Luca Buonanno; Catherine E. Graves; Paolo Faraboschi; Jim Ignowski (ICCAD, 2024)

Solving Boolean satisfiability problems with resistive content addressable memories. - Giacomo Pedretti; Fabian Böhm; Tinish Bhattacharya; Arne Heittmann; Xiangyi Zhang; Mohammad Hizzani; George Higgins Hutchinson; Dongseok Kwon; John Moon; Elisabetta Valiante; Ignacio Rozada; Catherine E. Graves; et al. (CoRR, 2025)