Dynamically Updatable Ternary Segmented Aging Bloom Filter for OpenFlow-Compliant Low-Power Packet Processing. - Sheng-Chun Kao; Ding-Yuan Lee; Ting-Sheng Chen; An-Yeu Wu (IEEE/ACM Trans. Netw., 2018)

Reinforcement learning based interconnection routing for adaptive traffic optimization. - Sheng-Chun Kao; Chao-Han Huck Yang; Pin-Yu Chen; Xiaoli Ma; Tushar Krishna (NOCS, 2019)

GAMMA: Automating the HW Mapping of DNN Models on Accelerators via Genetic Algorithm. - Sheng-Chun Kao; Tushar Krishna (ICCAD, 2020)

ConfuciuX: Autonomous Hardware Resource Assignment for DNN Accelerators using Reinforcement Learning. - Sheng-Chun Kao; Geonhwa Jeong; Tushar Krishna (MICRO, 2020)

Generative Design of Hardware-aware DNNs. - Sheng-Chun Kao; Arun Ramamurthy; Tushar Krishna (CoRR, 2020)

Conditional Neural Architecture Search. - Sheng-Chun Kao; Arun Ramamurthy; Reed Williams; Tushar Krishna (CoRR, 2020)

Extending Sparse Tensor Accelerators to Support Multiple Compression Formats. - Eric Qin 001; Geonhwa Jeong; William Won; Sheng-Chun Kao; Hyoukjun Kwon; Sudarshan Srinivasan; Dipankar Das 002; Gordon Euhyun Moon; Sivasankaran Rajamanickam; Tushar Krishna (IPDPS, 2021)

E3: A HW/SW Co-design Neuroevolution Platform for Autonomous Learning in Edge Device. - Sheng-Chun Kao; Tushar Krishna (ISPASS, 2021)

Domain-specific Genetic Algorithm for Multi-tenant DNNAccelerator Scheduling. - Sheng-Chun Kao; Tushar Krishna (CoRR, 2021)

ATTACC the Quadratic Bottleneck of Attention Layers. - Sheng-Chun Kao; Suvinay Subramanian; Gaurav Agrawal; Tushar Krishna (CoRR, 2021)

DiGamma: Domain-aware Genetic Algorithm for HW-Mapping Co-optimization for DNN Accelerators. - Sheng-Chun Kao; Michael Pellauer; Angshuman Parashar; Tushar Krishna (DATE, 2022)

MAGMA: An Optimization Framework for Mapping Multiple DNNs on Multiple Accelerator Cores. - Sheng-Chun Kao; Tushar Krishna (HPCA, 2022)

Demystifying Map Space Exploration for NPUs. - Sheng-Chun Kao; Angshuman Parashar; Po-An Tsai; Tushar Krishna (IISWC, 2022)

DNNFuser: Generative Pre-Trained Transformer as a Generalized Mapper for Layer Fusion in DNN Accelerators. - Sheng-Chun Kao; Xiaoyu Huang; Tushar Krishna (CoRR, 2022)

Training Recipe for N: M Structured Sparsity with Decaying Pruning Mask. - Sheng-Chun Kao; Amir Yazdanbakhsh; Suvinay Subramanian; Shivani Agrawal; Utku Evci; Tushar Krishna (CoRR, 2022)

A Formalism of DNN Accelerator Flexibility. - Sheng-Chun Kao; Hyoukjun Kwon; Michael Pellauer; Angshuman Parashar; Tushar Krishna (Proc. ACM Meas. Anal. Comput. Syst., 2022)

Domain-aware Genetic Algorithms for Hardware and Mapping Optimization for Efficient DNN Acceleration. - Sheng-Chun Kao (2022)

FLAT: An Optimized Dataflow for Mitigating Attention Bottlenecks. - Sheng-Chun Kao; Suvinay Subramanian; Gaurav Agrawal; Amir Yazdanbakhsh; Tushar Krishna (ASPLOS (2), 2023)

JaxPruner: A concise library for sparsity research. - Joo Hyung Lee; Wonpyo Park; Nicole Mitchell; Jonathan Pilault; Johan S. Obando-Ceron; Han-Byul Kim; Namhoon Lee; Elias Frantar; Yun Long; Amir Yazdanbakhsh; Shivani Agrawal; Suvinay Subramanian; et al. (CoRR, 2023)

Jaxpruner: A Concise Library for Sparsity Research. - Joo Hyung Lee; Wonpyo Park; Nicole Mitchell; Jonathan Pilault; Johan Samir Obando Ceron; Han-Byul Kim; Namhoon Lee; Elias Frantar; Yun Long; Amir Yazdanbakhsh; Woohyun Han; Shivani Agrawal; et al. (CPAL, 2024)

Progressive Gradient Flow for Robust N: M Sparsity Training in Transformers. - Abhimanyu Rajeshkumar Bambhaniya; Amir Yazdanbakhsh; Suvinay Subramanian; Sheng-Chun Kao; Shivani Agrawal; Utku Evci; Tushar Krishna (CoRR, 2024)

NonGEMM Bench: Understanding the Performance Horizon of the Latest ML Workloads with NonGEMM Workloads. - Rachid Karami; Hemanth Kota; Sheng-Chun Kao; Hyoukjun Kwon (CoRR, 2024)

Progressive Gradient Flow for Robust N:M Sparsity Training in Transformers. - Abhimanyu Rajeshkumar Bambhaniya; Amir Yazdanbakhsh; Suvinay Subramanian; Sheng-Chun Kao; Shivani Agrawal; Utku Evci; Tushar Krishna (CPAL, 2025)