MASR: A Modular Accelerator for Sparse RNNs. - Udit Gupta; Brandon Reagen; Lillian Pentecost; Marco Donato; Thierry Tambe; Alexander M. Rush; Gu-Yeon Wei; David Brooks 001 (PACT, 2019)

AdaptivFloat: A Floating-point based Data Type for Resilient Deep Learning Inference. - Thierry Tambe; En-Yu Yang; Zishen Wan; Yuntian Deng; Vijay Janapa Reddi; Alexander M. Rush; David Brooks 001; Gu-Yeon Wei (CoRR, 2019)

Algorithm-Hardware Co-Design of Adaptive Floating-Point Encodings for Resilient Deep Learning Inference. - Thierry Tambe; En-Yu Yang; Zishen Wan; Yuntian Deng; Vijay Janapa Reddi; Alexander M. Rush; David Brooks 001; Gu-Yeon Wei (DAC, 2020)

A Scalable Bayesian Inference Accelerator for Unsupervised Learning. - Glenn G. Ko; Yuji Chai; Marco Donato; Paul N. Whatmough; Thierry Tambe; Rob A. Rutenbar; Gu-Yeon Wei; David Brooks 001 (Hot Chips Symposium, 2020)

A 3mm2 Programmable Bayesian Inference Accelerator for Unsupervised Machine Perception using Parallel Gibbs Sampling in 16nm. - Glenn G. Ko; Yuji Chai; Marco Donato; Paul N. Whatmough; Thierry Tambe; Rob A. Rutenbar; David Brooks 001; Gu-Yeon Wei (VLSI Circuits, 2020)

EdgeBERT: Optimizing On-Chip Inference for Multi-Task NLP. - Thierry Tambe; Coleman Hooper; Lillian Pentecost; En-Yu Yang; Marco Donato; Victor Sanh; Alexander M. Rush; David Brooks 001; Gu-Yeon Wei (CoRR, 2020)

Robomorphic computing: a design methodology for domain-specific accelerators parameterized by robot morphology. - Sabrina M. Neuman; Brian Plancher; Thomas Bourgeat; Thierry Tambe; Srinivas Devadas; Vijay Janapa Reddi (ASPLOS, 2021)

SM6: A 16nm System-on-Chip for Accurate and Noise-Robust Attention-Based NLP Applications : The 33rd Hot Chips Symposium - August 22-24, 2021. - Thierry Tambe; En-Yu Yang; Glenn G. Ko; Yuji Chai; Coleman Hooper; Marco Donato; Paul N. Whatmough; Alexander M. Rush; David Brooks 001; Gu-Yeon Wei (HCS, 2021)

9.8 A 25mm2 SoC for IoT Devices with 18ms Noise-Robust Speech-to-Text Latency via Bayesian Speech Denoising and Attention-Based Sequence-to-Sequence DNN Speech Recognition in 16nm FinFET. - Thierry Tambe; En-Yu Yang; Glenn G. Ko; Yuji Chai; Coleman Hooper; Marco Donato; Paul N. Whatmough; Alexander M. Rush; David Brooks 001; Gu-Yeon Wei (ISSCC, 2021)

EdgeBERT: Sentence-Level Energy Optimizations for Latency-Aware Multi-Task NLP Inference. - Thierry Tambe; Coleman Hooper; Lillian Pentecost; Tianyu Jia; En-Yu Yang; Marco Donato; Victor Sanh; Paul N. Whatmough; Alexander M. Rush; David Brooks 001; Gu-Yeon Wei (MICRO, 2021)

Quantifying and Maximizing the Benefits of Back-End Noise Adaption on Attention-Based Speech Recognition Models. - Coleman Hooper; Thierry Tambe; Gu-Yeon Wei (CoRR, 2021)

AutoSoC: Automating Algorithm-SOC Co-design for Aerial Robots. - Srivatsan Krishnan; Thierry Tambe; Zishen Wan; Vijay Janapa Reddi (CoRR, 2021)

GoldenEye: A Platform for Evaluating Emerging Numerical Data Formats in DNN Accelerators. - Abdulrahman Mahmoud; Thierry Tambe; Tarek Aloui; David Brooks 001; Gu-Yeon Wei (DSN, 2022)

ASAP: automatic synthesis of area-efficient and precision-aware CGRAs. - Cheng Tan 002; Thierry Tambe; Jeff Jun Zhang; Bo Fang 002; Tong Geng; Gu-Yeon Wei; David Brooks 001; Antonino Tumeo; Ganesh Gopalakrishnan; Ang Li 006 (ICS, 2022)

Specialized Accelerators and Compiler Flows: Replacing Accelerator APIs with a Formal Software/Hardware Interface. - Bo-Yuan Huang 001; Steven Lyubomirsky; Yi Li; Mike He; Thierry Tambe; Gus Henry Smith; Akash Gaonkar; Vishal Canumalla; Gu-Yeon Wei; Aarti Gupta; Zachary Tatlock; Sharad Malik (CoRR, 2022)

VaPr: Variable-Precision Tensors to Accelerate Robot Motion Planning. - Yu-Shun Hsiao; Siva Kumar Sastry Hari; Balakumar Sundaralingam; Jason Yik; Thierry Tambe; Charbel Sakr; Stephen W. Keckler; Vijay Janapa Reddi (IROS, 2023)

A 12nm 18.1TFLOPs/W Sparse Transformer Processor with Entropy-Based Early Exit, Mixed-Precision Predication and Fine-Grained Power Management. - Thierry Tambe; Jeff Zhang 001; Coleman Hooper; Tianyu Jia; Paul N. Whatmough; Joseph Zuckerman; Maico Cassel dos Santos; Erik Jens Loscalzo; Davide Giri; Kenneth L. Shepard; Luca P. Carloni; Alexander M. Rush; et al. (ISSCC, 2023)

CAMEL: Co-Designing AI Models and Embedded DRAMs for Efficient On-Device Learning. - Sai Qian Zhang; Thierry Tambe; Nestor Cuevas; Gu-Yeon Wei; David Brooks 001 (CoRR, 2023)

A 16-nm SoC for Noise-Robust Speech and NLP Edge AI Inference With Bayesian Sound Source Separation and Attention-Based DNNs. - Thierry Tambe; En-Yu Yang; Glenn G. Ko; Yuji Chai; Coleman Hooper; Marco Donato; Paul N. Whatmough; Alexander M. Rush; David Brooks 001; Gu-Yeon Wei (IEEE J. Solid State Circuits, 2023)

CAMEL: Co-Designing AI Models and eDRAMs for Efficient On-Device Learning. - Sai Qian Zhang; Thierry Tambe; Nestor Cuevas; Gu-Yeon Wei; David Brooks 001 (HPCA, 2024)

JointNF: Enhancing DNN Performance through Adaptive N: M Pruning across both Weight and Activation. - Sai Qian Zhang; Thierry Tambe; Gu-Yeon Wei; David Brooks 001 (ISLPED, 2024)

14.5 A 12nm Linux-SMP-Capable RISC-V SoC with 14 Accelerator Types, Distributed Hardware Power Management and Flexible NoC-Based Data Orchestration. - Maico Cassel dos Santos; Tianyu Jia; Joseph Zuckerman; Martin Cochet; Davide Giri; Erik Jens Loscalzo; Karthik Swaminathan; Thierry Tambe; Jeff Jun Zhang; Alper Buyuktosunoglu; Kuan-Lin Chiu; Giuseppe Di Guglielmo; et al. (ISSCC, 2024)

Application-level Validation of Accelerator Designs Using a Formal Software/Hardware Interface. - Bo-Yuan Huang 001; Steven Lyubomirsky; Yi Li; Mike He; Gus Henry Smith; Thierry Tambe; Akash Gaonkar; Vishal Canumalla; Andrew Cheung; Gu-Yeon Wei; Aarti Gupta; Zachary Tatlock; et al. (ACM Trans. Design Autom. Electr. Syst., 2024)

BlockDialect: Block-wise Fine-grained Mixed Format Quantization for Energy-Efficient LLM Inference. - Wonsuk Jang; Thierry Tambe (CoRR, 2025)

GainSight: Application-Guided Profiling for Composing Heterogeneous On-Chip Memories in AI Hardware Accelerators. - Peijing Li; Matthew Hung; Yiming Tan; Konstantin Hoßfeld; Jake Cheng Jiajun; Shuhan Liu; Lixian Yan; Xinxin Wang; H.-S. Philip Wong; Thierry Tambe (CoRR, 2025)

Token Sequence Compression for Efficient Multimodal Computing. - Yasmine Omri; Parth Shroff; Thierry Tambe (CoRR, 2025)

OpenGCRAM: An Open-Source Gain Cell Compiler Enabling Design-Space Exploration for AI Workloads. - Xinxin Wang; Lixian Yan; Shuhan Liu; Luke Upton; Zhuoqi Cai; Yiming Tan; Shengman Li; Koustav Jana; Peijing Li; Jesse Cirimelli-Low; Thierry Tambe; Matthew Guthaus; et al. (CoRR, 2025)

Towards Memory Specialization: A Case for Long-Term and Short-Term RAM. - Peijing Li; Muhammad Shahir Abdurraman; Rachel Cleaveland; Sergey Legtchenko; Philip Levis; Ioan A. Stefanovici; Thierry Tambe; David Tennenhouse; Caroline Trippel (CoRR, 2025)