Locality-aware dynamic VM reconfiguration on MapReduce clouds. - Jongse Park; DaeWoo Lee; Bokyeong Kim; Jaehyuk Huh 001; Seungryoul Maeng (HPDC, 2012)

Isolated Mini-domain for Trusted Cloud Computing. - Jaewon Choi; Jongse Park; Jinho Seol; Seungryoul Maeng (CCGRID, 2013)

Rollback-free value prediction with approximate loads. - Bradley Thwaites; Gennady Pekhimenko; Hadi Esmaeilzadeh; Amir Yazdanbakhsh; Onur Mutlu; Jongse Park; Girish Mururu; Todd C. Mowry (PACT, 2014)

General-purpose code acceleration with limited-precision analog computation. - Renée St. Amant; Amir Yazdanbakhsh; Jongse Park; Bradley Thwaites; Hadi Esmaeilzadeh; Arjang Hassibi; Luis Ceze; Doug Burger (ISCA, 2014)

Axilog: language support for approximate hardware design. - Amir Yazdanbakhsh; Divya Mahajan 001; Bradley Thwaites; Jongse Park; Anandhavel Nagendrakumar; Sindhuja Sethuraman; Kartik Ramkrishnan; Nishanthi Ravindran; Rudra Jariwala; Abbas Rahimi; Hadi Esmaeilzadeh; Kia Bazargan (DATE, 2015)

Neural acceleration for GPU throughput processors. - Amir Yazdanbakhsh; Jongse Park; Hardik Sharma; Pejman Lotfi-Kamran; Hadi Esmaeilzadeh (MICRO, 2015)

FlexJava: language support for safe and modular approximate programming. - Jongse Park; Hadi Esmaeilzadeh; Xin Zhang 035; Mayur Naik; William Harris (ESEC/SIGSOFT FSE, 2015)

Axilog: Abstractions for Approximate Hardware Design and Reuse. - Divya Mahajan 001; Kartik Ramkrishnan; Rudra Jariwala; Amir Yazdanbakhsh; Jongse Park; Bradley Thwaites; Anandhavel Nagendrakumar; Abbas Rahimi; Hadi Esmaeilzadeh; Kia Bazargan (IEEE Micro, 2015)

AxGames: Towards Crowdsourcing Quality Target Determination in Approximate Computing. - Jongse Park; Emmanuel Amaro; Divya Mahajan 001; Bradley Thwaites; Hadi Esmaeilzadeh (ASPLOS, 2016)

TABLA: A unified template-based framework for accelerating statistical machine learning. - Divya Mahajan 001; Jongse Park; Emmanuel Amaro; Hardik Sharma; Amir Yazdanbakhsh; Joon Kyung Kim; Hadi Esmaeilzadeh (HPCA, 2016)

Towards Statistical Guarantees in Controlling Quality Tradeoffs for Approximate Acceleration. - Divya Mahajan 001; Amir Yazdanbakhsh; Jongse Park; Bradley Thwaites; Hadi Esmaeilzadeh (ISCA, 2016)

From high-level deep neural models to FPGAs. - Hardik Sharma; Jongse Park; Divya Mahajan 001; Emmanuel Amaro; Joon Kyung Kim; Chenkai Shao; Asit Mishra; Hadi Esmaeilzadeh (MICRO, 2016)

Scale-out acceleration for machine learning. - Jongse Park; Hardik Sharma; Divya Mahajan 001; Joon Kyung Kim; Preston Olds; Hadi Esmaeilzadeh (MICRO, 2017)

Bit Fusion: Bit-Level Dynamically Composable Architecture for Accelerating Deep Neural Networks. - Hardik Sharma; Jongse Park; Naveen Suda; Liangzhen Lai; Benson Chau; Joon Kyung Kim; Vikas Chandra; Hadi Esmaeilzadeh (CoRR, 2017)

Bit Fusion: Bit-Level Dynamically Composable Architecture for Accelerating Deep Neural Network. - Hardik Sharma; Jongse Park; Naveen Suda; Liangzhen Lai; Benson Chau; Vikas Chandra; Hadi Esmaeilzadeh (ISCA, 2018)

A Network-Centric Hardware/Algorithm Co-Design to Accelerate Distributed Training of Deep Neural Networks. - Youjie Li; Jongse Park; Mohammad Alian; Yifan Yuan; Zheng Qu 002; Peitian Pan; Ren Wang 001; Alexander G. Schwing; Hadi Esmaeilzadeh; Nam Sung Kim (MICRO, 2018)

Machine Learning Acceleration. - Hadi Esmaeilzadeh; Jongse Park (IEEE Micro, 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)

Decoupled Address Translation for Heterogeneous Memory Systems. - Bokyeong Kim; Soojin Hwang; Sanghoon Cha; Chang Hyun Park 001; Jongse Park; Jaehyuk Huh 001 (PACT, 2020)

Common Counters: Compressed Encryption Counters for Secure GPU Memory. - Seonjin Na; Sunho Lee 002; Yeonjae Kim; Jongse Park; Jaehyuk Huh 001 (HPCA, 2021)

Stockade: Hardware Hardening for Distributed Trusted Sandboxes. - Joongun Park; Seunghyo Kang; Sanghyeon Lee; Taehoon Kim 003; Jongse Park; Youngjin Kwon; Jaehyuk Huh 001 (CoRR, 2021)

Multi-model Machine Learning Inference Serving with GPU Spatial Partitioning. - Seungbeom Choi; Sunho Lee 002; Yeonjae Kim; Jongse Park; Youngjin Kwon; Jaehyuk Huh 001 (CoRR, 2021)

SLO-Aware Inference Scheduler for Heterogeneous Processors in Edge Platforms. - Wonik Seo; Sanghoon Cha; Yeonjae Kim; Jaehyuk Huh 001; Jongse Park (ACM Trans. Archit. Code Optim., 2021)

TNPU: Supporting Trusted Execution with Tree-less Integrity Protection for Neural Processing Unit. - Sunho Lee 002; Jungwoo Kim 002; Seonjin Na; Jongse Park; Jaehyuk Huh 001 (HPCA, 2022)

Supporting Dynamic Translation Granularity for Hybrid Memory Systems. - Bokyeong Kim; Soojin Hwang; Sanghoon Cha; Chang Hyun Park 001; Jongse Park; Jaehyuk Huh 001 (ICCD, 2022)

Tunable Memory Protection for Secure Neural Processing Units. - Sunho Lee 002; Seonjin Na; Jungwoo Kim 002; Jongse Park; Jaehyuk Huh 001 (ICCD, 2022)

Serving Heterogeneous Machine Learning Models on Multi-GPU Servers with Spatio-Temporal Sharing. - Seungbeom Choi; Sunho Lee 002; Yeonjae Kim; Jongse Park; Youngjin Kwon; Jaehyuk Huh 001 (USENIX ATC, 2022)

CoVA: Exploiting Compressed-Domain Analysis to Accelerate Video Analytics. - Jinwoo Hwang; Minsu Kim 004; Daeun Kim; Seungho Nam; Yoonsung Kim; Dohee Kim; Hardik Sharma; Jongse Park (USENIX ATC, 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)

HAMMER: Hardware-Friendly Approximate Computing for Self-Attention With Mean-Redistribution And Linearization. - Seonho Lee; Ranggi Hwang; Jongse Park; Minsoo Rhu (IEEE Comput. Archit. Lett., 2023)

FlexBlock: A Flexible DNN Training Accelerator With Multi-Mode Block Floating Point Support. - Seock-Hwan Noh; Jahyun Koo 002; Seunghyun Lee; Jongse Park; Jaeha Kung (IEEE Trans. Computers, 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)

NeuPIMs: NPU-PIM Heterogeneous Acceleration for Batched LLM Inferencing. - Guseul Heo; Sangyeop Lee; Jaehong Cho; Hyunmin Choi; Sanghyeon Lee; Hyungkyu Ham; Gwangsun Kim; Divya Mahajan 001; Jongse Park (ASPLOS (3), 2024)

LVS: A Learned Video Storage for Fast and Efficient Video Understanding. - Yunghee Lee; Jongse Park (CVPR Workshops, 2024)

Interference-Aware DNN Serving on Heterogeneous Processors in Edge Systems. - Yeonjae Kim; Igjae Kim; Kwanghoon Choi 003; Jeongseob Ahn; Jongse Park; Jaehyuk Huh 001 (ICCD, 2024)

LLMServingSim: A HW/SW Co-Simulation Infrastructure for LLM Inference Serving at Scale. - Jaehong Cho; Minsu Kim 004; Hyunmin Choi; Guseul Heo; Jongse Park (IISWC, 2024)

DACAPO: Accelerating Continuous Learning in Autonomous Systems for Video Analytics. - Yoonsung Kim; Changhun Oh; Jinwoo Hwang; Wonung Kim; Seongryong Oh; Yubin Lee 002; Hardik Sharma; Amir Yazdanbakhsh; Jongse Park (ISCA, 2024)

ONNXim: A Fast, Cycle-Level Multi-Core NPU Simulator. - Hyungkyu Ham; Wonhyuk Yang; Yunseon Shin; Okkyun Woo; Guseul Heo; Sangyeop Lee; Jongse Park; Gwangsun Kim (IEEE Comput. Archit. Lett., 2024)

LPU: A Latency-Optimized and Highly Scalable Processor for Large Language Model Inference. - Seungjae Moon; Jung-Hoon Kim; Junsoo Kim 002; Seongmin Hong; Junseo Cha; Minsu Kim 004; Sukbin Lim; Gyubin Choi; Dongjin Seo; Jongho Kim; Hunjong Lee; Hyunjun Park; et al. (CoRR, 2024)

A Latency Processing Unit: A Latency-Optimized and Highly Scalable Processor for Large Language Model Inference. - Seungjae Moon; Jung-Hoon Kim; Junsoo Kim 002; Seongmin Hong; Junseo Cha; Minsu Kim 004; Sukbin Lim; Gyubin Choi; Dongjin Seo; Jongho Kim; Hunjong Lee; Hyunjun Park; et al. (IEEE Micro, 2024)

Hardware-hardened Sandbox Enclaves for Trusted Serverless Computing. - Joongun Park; Seunghyo Kang; Sanghyeon Lee; Taehoon Kim 001; Jongse Park; Youngjin Kwon; Jaehyuk Huh 001 (ACM Trans. Archit. Code Optim., 2024)

Accelerating String-key Learned Index Structures via Memoization-based Incremental Training. - Minsu Kim 004; Jinwoo Hwang; Guseul Heo; Seiyeon Cho; Divya Mahajan 001; Jongse Park (Proc. VLDB Endow., 2024)

Cerberus: Triple Mode Acceleration of Sparse Matrix and Vector Multiplication. - Soojin Hwang; Daehyeon Baek; Jongse Park; Jaehyuk Huh 001 (ACM Trans. Archit. Code Optim., 2024)

Oaken: Fast and Efficient LLM Serving with Online-Offline Hybrid KV Cache Quantization. - Minsu Kim 004; Seongmin Hong; Ryeowook Ko; Soongyu Choi; Hunjong Lee; Junsoo Kim 002; Joo-Young Kim 001; Jongse Park (ISCA, 2025)

MixDiT: Accelerating Image Diffusion Transformer Inference With Mixed-Precision MX Quantization. - Daeun Kim; Jinwoo Hwang; Changhun Oh; Jongse Park (IEEE Comput. Archit. Lett., 2025)

Oaken: Fast and Efficient LLM Serving with Online-Offline Hybrid KV Cache Quantization. - Minsu Kim 004; Seongmin Hong; Ryeowook Ko; Soongyu Choi; Hunjong Lee; Junsoo Kim 002; Joo-Young Kim 006; Jongse Park (CoRR, 2025)

Déjà Vu: Efficient Video-Language Query Engine with Learning-based Inter-Frame Computation Reuse. - Jinwoo Hwang; Daeun Kim; Sangyeop Lee; Yoonsung Kim; Guseul Heo; Hojoon Kim; Yunseok Jeong; Tadiwos Meaza; Eunhyeok Park; Jeongseob Ahn; Jongse Park (CoRR, 2025)

Characterizing Compute-Communication Overlap in GPU-Accelerated Distributed Deep Learning: Performance and Power Implications. - Seonho Lee; Jihwan Oh; Junkyum Kim; Seokjin Go; Jongse Park; Divya Mahajan 001 (CoRR, 2025)

Pimba: A Processing-in-Memory Acceleration for Post-Transformer Large Language Model Serving. - Wonung Kim; Yubin Lee 002; Yoonsung Kim; Jinwoo Hwang; Seongryong Oh; Jiyong Jung; Aziz Huseynov; Woong Gyu Park; Chang Hyun Park 001; Divya Mahajan 001; Jongse Park (CoRR, 2025)