© 2026. All rights reserved.
© 2026. All rights reserved.
For the full list, please refer to Google Scholar.
ICCAD’26 Demystify AI Platform Design for Distributed Inference of Next-Generation LLMs
Abhimanyu Bambhaniya, Ritik Raj, Geonhwa Jeong, Souvik Kundu, Sudarshan Srinivasan, Midhilesh Elavazhagan, Madhu Kumar, Suvinay Subramanian, Tushar Krishna
In Proc. of the 45th International Conference on Computer-Aided Design (ICCAD)
Nov 2026 (To appear)
ICML’26 Unveiling the Potential of Quantization with MXFP4: Strategies for Quantization Error Reduction
Jatin Chhugani*, Geonhwa Jeong*, Bor-Yiing Su, Yunjie Pan, Hanmei Yang, Aayush Ankit, Jiecao Yu, Summer Deng, Yunqing Chen, Nadathur Satish, Changkyu Kim
In Proc. of the 43rd International Conference on Machine Learning (ICML)
July 2026
[Paper]
MLSys’26 Optimizing Deployment Configurations for LLM Inference
Sung Min Cho, Jaewon Lee, Chunqiang Tang, Yejin Lee, Geonhwa Jeong, Anca Agape, et al.
In Proc. of the 9th Annual Conference on Machine Learning and Systems (MLSys)
May 2026
[Paper]
MLSys’25 Enabling Unstructured Sparse Acceleration on Structured Sparse Accelerators
Geonhwa Jeong, Po-An Tsai, Abhimanyu Rajeshkumar Bambhaniya, Stephen W. Keckler, Tushar Krishna
In Proc. of the 8th Annual Conference on Machine Learning and Systems (MLSys)
May 2025
[Paper]
MLSys’25 FlexInfer: Flexible LLM Inference with CPU Computations
Seonjin Na, Geonhwa Jeong, Byunghoon Ahn, Aaron Jezghani, Jeffrey Young, Christopher J. Hughes, Tushar Krishna, Hyesoon Kim
In Proc. of the 8th Annual Conference on Machine Learning and Systems (MLSys)
May 2025
[Paper]
IISWC’24 Understanding Performance Implications of LLM Inference on CPUs
Seonjin Na, Geonhwa Jeong, Byunghoon Ahn, Jeffrey Young, Tushar Krishna, Hyesoon Kim
In Proc. of the IEEE International Symposium on Workload Characterization (IISWC)
Sep 2024
[Paper]
DAC’24 Algorithm-Hardware Co-Design of Distribution-Aware Logarithmic-Posit Encodings for Efficient DNN Inference
Akshat Ramachandran, Zishen Wan, Geonhwa Jeong, John Gustafson, Tushar Krishna
In Proc. of the 61st Annual Design Automation Conference (DAC)
June 2024
[Paper]
ICLR-SNN’23 SPARC : Understanding the True Cost of Sparse Accelerators
Abhimanyu Bambhaniya, Sheng-Chun Kao, Geonhwa Jeong, Suvinay Subramanian, Amir Yazdanbakhsh, Tushar Krishna
International Conference on Learning Representations Workshop on Sparsity in Neural Networks (SNN co-located with ICLR)
May 2023 (Not-archived)
ISPASS’23 Characterization of Data Compression in Datacenters
Geonhwa Jeong, Bikash Sharma, Nick Terrell, Abhishek Dhanotia, Zhiwei Zhao, Niket Agarwal, Arun Kejariwal, Tushar Krishna
In Proc. of the IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS)
Apr 2023 (Best Paper Candidate)
[Paper]
HPCA’23 VEGETA: Vertically-Integrated Extensions for Sparse/Dense GEMM Tile Acceleration on CPUs
Geonhwa Jeong, Sana Damani, Abhimanyu Bambhaniya, Eric Qin, Christopher J. Hughes, Sreenivas Subramoney, Hyesoon Kim, Tushar Krishna
In Proc. of the 29th IEEE International Symposium on High-Performance Computer Architecture (HPCA)
Feb 2023
[Paper]
ISPASS’22 Understanding Data Compression in Warehouse-Scale Datacenter Services
Geonhwa Jeong, Bikash Sharma, Nick Terrell, Abhishek Dhanotia, Zhiwei Zhao, Niket Agarwal, Arun Kejariwal, Tushar Krishna
In Proc. of the IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS)
May 2022
[Paper]
TPDS’22 Evaluating Spatial Accelerator Architectures with Tiled Matrix-Matrix Multiplication
Gordon E. Moon, Hyoukjun Kwon, Geonhwa Jeong, Prasanth Chatarasi, Sivasankaran Rajamanickam, Tushar Krishna
IEEE Transactions on Parallel and Distributed Systems (TPDS)
Apr 2022
[Paper]
DAC’21 RASA: Efficient Register-Aware Systolic Array Matrix Engine for CPU
Geonhwa Jeong, Eric Qin, Ananda Samajdar, Christopher J. Hughes, Sreenivas Subramoney, Hyesoon Kim, Tushar Krishna
In Proc. of the 58th Annual Design Automation Conference (DAC)
Dec 2021
[Paper]
PACT’21 Union: A Unified HW-SW Co-Design Ecosystem in MLIR for Evaluating Tensor Operations on Spatial Accelerators
Geonhwa Jeong, Gokcen Kestor, Prasanth Chatarasi, Angshuman Parashar, Po-An Tsai, Siva Rajamanickam, Roberto Gioiosa, Tushar Krishna
In Proc. of the 30th International Conference on Parallel Architectures and Compilation Techniques (PACT)
Sep 2021
[Paper]
IPDPS’21 Extending Sparse Tensor Accelerators to Support Multiple Compression Formats
Eric Qin, Geonhwa Jeong, William Won, Sheng-Chun Kao, Hyoukjun Kwon, Sudarshan Srinivasan, Dipankar Das, Gordon E. Moon, Sivasankaran Rajamanickam, Tushar Krishna
In Proc. of the 35th IEEE International Parallel & Distributed Processing Symposium (IPDPS)
May 2021
[Paper]
ASP-DAC’21 Bridging the Frequency Gap in Heterogeneous 3D SoCs through Technology-Specific NoC Router Architectures
Jan Moritz Joseph, Lennart Bamberg, Geonhwa Jeong, Ruei-Ting Chien, Rainer Leupers, Alberto Garcia-Ortiz, Tushar Krishna, Thilo Pionteck
In Proc. of the 26th Asia and South Pacific Design Automation Conference (ASP-DAC)
Jan 2021 (Best Paper Candidate)
[Paper]
MICRO’20 ConfuciuX: Autonomous Hardware Resource Assignment for DNN Accelerators Using Reinforcement Learning
Sheng-Chun Kao, Geonhwa Jeong, Tushar Krishna
In Proc. of the 53rd Annual IEEE/ACM International Symposium on Microarchitecture (MICRO)
Oct 2020
[Paper]