ReLeQ: A Reinforcement Learning Approach for Deep Quantization of Neural Networks. - Ahmed T. Elthakeb; Prannoy Pilligundla; Amir Yazdanbakhsh; Sean Kinzer; Hadi Esmaeilzadeh (CoRR, 2018)

Mixed-Signal Charge-Domain Acceleration of Deep Neural networks through Interleaved Bit-Partitioned Arithmetic. - Soroush Ghodrati; Hardik Sharma; Sean Kinzer; Amir Yazdanbakhsh; Kambiz Samadi; Nam Sung Kim; Doug Burger; Hadi Esmaeilzadeh (CoRR, 2019)

Mixed-Signal Charge-Domain Acceleration of Deep Neural Networks through Interleaved Bit-Partitioned Arithmetic. - Soroush Ghodrati; Hardik Sharma; Sean Kinzer; Amir Yazdanbakhsh; Jongse Park; Nam Sung Kim; Doug Burger; Hadi Esmaeilzadeh (PACT, 2020)

Planaria: Dynamic Architecture Fission for Spatial Multi-Tenant Acceleration of Deep Neural Networks. - Soroush Ghodrati; Byung Hoon Ahn; Joon Kyung Kim; Sean Kinzer; Brahmendra Reddy Yatham; Navateja Alla; Hardik Sharma; Mohammad Alian; Eiman Ebrahimi; Nam Sung Kim; Cliff Young; Hadi Esmaeilzadeh (MICRO, 2020)

A Computational Stack for Cross-Domain Acceleration. - Sean Kinzer; Joon Kyung Kim; Soroush Ghodrati; Brahmendra Reddy Yatham; Alric Althoff; Divya Mahajan 001; Sorin Lerner; Hadi Esmaeilzadeh (HPCA, 2021)

VeriGOOD-ML: An Open-Source Flow for Automated ML Hardware Synthesis. - Hadi Esmaeilzadeh; Soroush Ghodrati; Jie Gu 003; Shiyu Guo; Andrew B. Kahng; Joon Kyung Kim; Sean Kinzer; Rohan Mahapatra; Susmita Dey Manasi; Edwin Mascarenhas; Sachin S. Sapatnekar; Ravi Varadarajan; et al. (ICCAD, 2021)

Glimpse: mathematical embedding of hardware specification for neural compilation. - Byung Hoon Ahn; Sean Kinzer; Hadi Esmaeilzadeh (DAC, 2022)

Physically Accurate Learning-based Performance Prediction of Hardware-accelerated ML Algorithms. - Hadi Esmaeilzadeh; Soroush Ghodrati; Andrew B. Kahng; Joon Kyung Kim; Sean Kinzer; Sayak Kundu; Rohan Mahapatra; Susmita Dey Manasi; Sachin S. Sapatnekar; Zhiang Wang; Ziqing Zeng (MLCAD, 2022)

Yin-Yang: Programming Abstractions for Cross-Domain Multi-Acceleration. - Joon Kyung Kim; Byung Hoon Ahn; Sean Kinzer; Soroush Ghodrati; Rohan Mahapatra; Brahmendra Reddy Yatham; Shu-Ting Wang; Dohee Kim; Parisa Sarikhani; Babak Mahmoudi; Divya Mahajan 001; Jongse Park; et al. (IEEE Micro, 2022)

MESA: Microarchitecture Extensions for Spatial Architecture Generation. - Dong Kai Wang; Jiaqi Lou; Naiyin Jin; Edwin Mascarenhas; Rohan Mahapatra; Sean Kinzer; Soroush Ghodrati; Amir Yazdanbakhsh; Hadi Esmaeilzadeh; Nam Sung Kim (ISCA, 2023)

Domain-Specific Computational Storage for Serverless Computing. - Rohan Mahapatra; Soroush Ghodrati; Byung Hoon Ahn; Sean Kinzer; Shu-Ting Wang; Hanyang Xu 002; Lavanya Karthikeyan; Hardik Sharma; Amir Yazdanbakhsh; Mohammad Alian; Hadi Esmaeilzadeh (CoRR, 2023)

Performance Analysis of DNN Inference/Training with Convolution and non-Convolution Operations. - Hadi Esmaeilzadeh; Soroush Ghodrati; Andrew B. Kahng; Sean Kinzer; Susmita Dey Manasi; Sachin S. Sapatnekar; Zhiang Wang (CoRR, 2023)

Restoring the Broken Covenant Between Compilers and Deep Learning Accelerators. - Sean Kinzer; Soroush Ghodrati; Rohan Mahapatra; Byung Hoon Ahn; Edwin Mascarenhas; Xiaolong Li; Janarbek Matai; Liang Zhang; Hadi Esmaeilzadeh (CoRR, 2023)

Polymorphic Compilation for Cross-Domain Acceleration - Sean Kinzer (2023)

Tandem Processor: Grappling with Emerging Operators in Neural Networks. - Soroush Ghodrati; Sean Kinzer; Hanyang Xu 002; Rohan Mahapatra; Yoonsung Kim; Byung Hoon Ahn; Dong Kai Wang; Lavanya Karthikeyan; Amir Yazdanbakhsh; Jongse Park; Nam Sung Kim; Hadi Esmaeilzadeh (ASPLOS (2), 2024)

In-Storage Domain-Specific Acceleration for Serverless Computing. - Rohan Mahapatra; Soroush Ghodrati; Byung Hoon Ahn; Sean Kinzer; Shu-Ting Wang; Hanyang Xu 002; Lavanya Karthikeyan; Hardik Sharma; Amir Yazdanbakhsh; Mohammad Alian; Hadi Esmaeilzadeh (ASPLOS (2), 2024)

An Open-Source ML-Based Full-Stack Optimization Framework for Machine Learning Accelerators. - Hadi Esmaeilzadeh; Soroush Ghodrati; Andrew B. Kahng; Joon Kyung Kim; Sean Kinzer; Sayak Kundu; Rohan Mahapatra; Susmita Dey Manasi; Sachin S. Sapatnekar; Zhiang Wang; Ziqing Zeng (ACM Trans. Design Autom. Electr. Syst., 2024)

Performance Analysis of CNN Inference/Training with Convolution and Non-Convolution Operations on ASIC Accelerators. - Hadi Esmaeilzadeh; Soroush Ghodrati; Andrew B. Kahng; Sean Kinzer; Susmita Dey Manasi; Sachin S. Sapatnekar; Zhiang Wang (ACM Trans. Design Autom. Electr. Syst., 2025)