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Jongse Park
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Other persons with a similar name
- Jong-Seo Park (aka: Jong Seo Park)
- Jong-Seon Park
- Jong-Seung Park
- JongSeung Park
- Jong Seok Park (aka: Jong-Seok Park, Jongseok Park) — disambiguation page
- Jongsei Park
- Jongseo Park
- Jongseon Park
- Jongseung Park
- Jong Seok Park 0001 (aka: Jongseok Park 0001) — Apple, San Diego, CA, USA (and 2 more)
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2020 – today
- 2024
- [j9]Minsu Kim, Jinwoo Hwang, Guseul Heo, Seiyeon Cho, Divya Mahajan, Jongse Park:
Accelerating String-key Learned Index Structures via Memoization-based Incremental Training. Proc. VLDB Endow. 17(8): 1802-1815 (2024) - [j8]Joongun Park, Seunghyo Kang, Sanghyeon Lee, Taehoon Kim, Jongse Park, Youngjin Kwon, Jaehyuk Huh:
Hardware-hardened Sandbox Enclaves for Trusted Serverless Computing. ACM Trans. Archit. Code Optim. 21(1): 13:1-13:25 (2024) - [j7]Soojin Hwang, Daehyeon Baek, Jongse Park, Jaehyuk Huh:
Cerberus: Triple Mode Acceleration of Sparse Matrix and Vector Multiplication. ACM Trans. Archit. Code Optim. 21(2): 38 (2024) - [c26]Guseul Heo, Sangyeop Lee, Jaehong Cho, Hyunmin Choi, Sanghyeon Lee, Hyungkyu Ham, Gwangsun Kim, Divya Mahajan, Jongse Park:
NeuPIMs: NPU-PIM Heterogeneous Acceleration for Batched LLM Inferencing. ASPLOS (3) 2024: 722-737 - [c25]Soroush Ghodrati, Sean Kinzer, Hanyang Xu, Rohan Mahapatra, Yoonsung Kim, Byung Hoon Ahn, Dong Kai Wang, Lavanya Karthikeyan, Amir Yazdanbakhsh, Jongse Park, Nam Sung Kim, Hadi Esmaeilzadeh:
Tandem Processor: Grappling with Emerging Operators in Neural Networks. ASPLOS (2) 2024: 1165-1182 - [c24]Yunghee Lee, Jongse Park:
LVS: A Learned Video Storage for Fast and Efficient Video Understanding. CVPR Workshops 2024: 8085-8093 - [c23]Yoonsung Kim, Changhun Oh, Jinwoo Hwang, Wonung Kim, Seongryong Oh, Yubin Lee, Hardik Sharma, Amir Yazdanbakhsh, Jongse Park:
DACAPO: Accelerating Continuous Learning in Autonomous Systems for Video Analytics. ISCA 2024: 1246-1261 - [i11]Guseul Heo, Sangyeop Lee, Jaehong Cho, Hyunmin Choi, Sanghyeon Lee, Hyungkyu Ham, Gwangsun Kim, Divya Mahajan, Jongse Park:
NeuPIMs: NPU-PIM Heterogeneous Acceleration for Batched LLM Inferencing. CoRR abs/2403.00579 (2024) - [i10]Minsu Kim, Jinwoo Hwang, Guseul Heo, Seiyeon Cho, Divya Mahajan, Jongse Park:
Accelerating String-Key Learned Index Structures via Memoization-based Incremental Training. CoRR abs/2403.11472 (2024) - [i9]Yoonsung Kim, Changhun Oh, Jinwoo Hwang, Wonung Kim, Seongryong Oh, Yubin Lee, Hardik Sharma, Amir Yazdanbakhsh, Jongse Park:
DaCapo: Accelerating Continuous Learning in Autonomous Systems for Video Analytics. CoRR abs/2403.14353 (2024) - [i8]Hyungkyu Ham, Wonhyuk Yang, Yunseon Shin, Okkyun Woo, Guseul Heo, Sangyeop Lee, Jongse Park, Gwangsun Kim:
ONNXim: A Fast, Cycle-level Multi-core NPU Simulator. CoRR abs/2406.08051 (2024) - [i7]Jaehong Cho, Minsu Kim, Hyunmin Choi, Guseul Heo, Jongse Park:
LLMServingSim: A HW/SW Co-Simulation Infrastructure for LLM Inference Serving at Scale. CoRR abs/2408.05499 (2024) - [i6]Seungjae Moon, Jung-Hoon Kim, Junsoo Kim, Seongmin Hong, Junseo Cha, Minsu Kim, Sukbin Lim, Gyubin Choi, Dongjin Seo, Jongho Kim, Hunjong Lee, Hyunjun Park, Ryeowook Ko, Soongyu Choi, Jongse Park, Jinwon Lee, Joo-Young Kim:
LPU: A Latency-Optimized and Highly Scalable Processor for Large Language Model Inference. CoRR abs/2408.07326 (2024) - 2023
- [j6]Seonho Lee, Ranggi Hwang, Jongse Park, Minsoo Rhu:
HAMMER: Hardware-Friendly Approximate Computing for Self-Attention With Mean-Redistribution And Linearization. IEEE Comput. Archit. Lett. 22(1): 13-16 (2023) - [j5]Seock-Hwan Noh, Jahyun Koo, Seunghyun Lee, Jongse Park, Jaeha Kung:
FlexBlock: A Flexible DNN Training Accelerator With Multi-Mode Block Floating Point Support. IEEE Trans. Computers 72(9): 2522-2535 (2023) - 2022
- [j4]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, Jongse Park, Hadi Esmaeilzadeh:
Yin-Yang: Programming Abstractions for Cross-Domain Multi-Acceleration. IEEE Micro 42(5): 89-98 (2022) - [c22]Sunho Lee, Jungwoo Kim, Seonjin Na, Jongse Park, Jaehyuk Huh:
TNPU: Supporting Trusted Execution with Tree-less Integrity Protection for Neural Processing Unit. HPCA 2022: 229-243 - [c21]Bokyeong Kim, Soojin Hwang, Sanghoon Cha, Chang Hyun Park, Jongse Park, Jaehyuk Huh:
Supporting Dynamic Translation Granularity for Hybrid Memory Systems. ICCD 2022: 25-32 - [c20]Sunho Lee, Seonjin Na, Jungwoo Kim, Jongse Park, Jaehyuk Huh:
Tunable Memory Protection for Secure Neural Processing Units. ICCD 2022: 105-108 - [c19]Seungbeom Choi, Sunho Lee, Yeonjae Kim, Jongse Park, Youngjin Kwon, Jaehyuk Huh:
Serving Heterogeneous Machine Learning Models on Multi-GPU Servers with Spatio-Temporal Sharing. USENIX ATC 2022: 199-216 - [c18]Jinwoo Hwang, Minsu Kim, Daeun Kim, Seungho Nam, Yoonsung Kim, Dohee Kim, Hardik Sharma, Jongse Park:
CoVA: Exploiting Compressed-Domain Analysis to Accelerate Video Analytics. USENIX ATC 2022: 707-722 - [i5]Seock-Hwan Noh, Jahyun Koo, Seunghyun Lee, Jongse Park, Jaeha Kung:
FlexBlock: A Flexible DNN Training Accelerator with Multi-Mode Block Floating Point Support. CoRR abs/2203.06673 (2022) - [i4]Jinwoo Hwang, Minsu Kim, Daeun Kim, Seungho Nam, Yoonsung Kim, Dohee Kim, Hardik Sharma, Jongse Park:
CoVA: Exploiting Compressed-Domain Analysis to Accelerate Video Analytics. CoRR abs/2207.00588 (2022) - 2021
- [j3]Wonik Seo, Sanghoon Cha, Yeonjae Kim, Jaehyuk Huh, Jongse Park:
SLO-Aware Inference Scheduler for Heterogeneous Processors in Edge Platforms. ACM Trans. Archit. Code Optim. 18(4): 43:1-43:26 (2021) - [c17]Seonjin Na, Sunho Lee, Yeonjae Kim, Jongse Park, Jaehyuk Huh:
Common Counters: Compressed Encryption Counters for Secure GPU Memory. HPCA 2021: 1-13 - [i3]Joongun Park, Seunghyo Kang, Sanghyeon Lee, Taehoon Kim, Jongse Park, Youngjin Kwon, Jaehyuk Huh:
Stockade: Hardware Hardening for Distributed Trusted Sandboxes. CoRR abs/2108.13922 (2021) - [i2]Seungbeom Choi, Sunho Lee, Yeonjae Kim, Jongse Park, Youngjin Kwon, Jaehyuk Huh:
Multi-model Machine Learning Inference Serving with GPU Spatial Partitioning. CoRR abs/2109.01611 (2021) - 2020
- [c16]Bokyeong Kim, Soojin Hwang, Sanghoon Cha, Chang Hyun Park, Jongse Park, Jaehyuk Huh:
Decoupled Address Translation for Heterogeneous Memory Systems. PACT 2020: 155-156 - [c15]Soroush Ghodrati, Hardik Sharma, Sean Kinzer, Amir Yazdanbakhsh, Jongse Park, Nam Sung Kim, Doug Burger, Hadi Esmaeilzadeh:
Mixed-Signal Charge-Domain Acceleration of Deep Neural Networks through Interleaved Bit-Partitioned Arithmetic. PACT 2020: 399-411
2010 – 2019
- 2019
- [j2]Hadi Esmaeilzadeh, Jongse Park:
Machine Learning Acceleration. IEEE Micro 39(5): 6-7 (2019) - 2018
- [c14]Hardik Sharma, Jongse Park, Naveen Suda, Liangzhen Lai, Benson Chau, Vikas Chandra, Hadi Esmaeilzadeh:
Bit Fusion: Bit-Level Dynamically Composable Architecture for Accelerating Deep Neural Network. ISCA 2018: 764-775 - [c13]Youjie Li, Jongse Park, Mohammad Alian, Yifan Yuan, Zheng Qu, Peitian Pan, Ren Wang, Alexander G. Schwing, Hadi Esmaeilzadeh, Nam Sung Kim:
A Network-Centric Hardware/Algorithm Co-Design to Accelerate Distributed Training of Deep Neural Networks. MICRO 2018: 175-188 - 2017
- [c12]Jongse Park, Hardik Sharma, Divya Mahajan, Joon Kyung Kim, Preston Olds, Hadi Esmaeilzadeh:
Scale-out acceleration for machine learning. MICRO 2017: 367-381 - [i1]Hardik Sharma, Jongse Park, Naveen Suda, Liangzhen Lai, Benson Chau, Joon Kyung Kim, Vikas Chandra, Hadi Esmaeilzadeh:
Bit Fusion: Bit-Level Dynamically Composable Architecture for Accelerating Deep Neural Networks. CoRR abs/1712.01507 (2017) - 2016
- [c11]Jongse Park, Emmanuel Amaro, Divya Mahajan, Bradley Thwaites, Hadi Esmaeilzadeh:
AxGames: Towards Crowdsourcing Quality Target Determination in Approximate Computing. ASPLOS 2016: 623-636 - [c10]Divya Mahajan, Jongse Park, Emmanuel Amaro, Hardik Sharma, Amir Yazdanbakhsh, Joon Kyung Kim, Hadi Esmaeilzadeh:
TABLA: A unified template-based framework for accelerating statistical machine learning. HPCA 2016: 14-26 - [c9]Divya Mahajan, Amir Yazdanbakhsh, Jongse Park, Bradley Thwaites, Hadi Esmaeilzadeh:
Towards Statistical Guarantees in Controlling Quality Tradeoffs for Approximate Acceleration. ISCA 2016: 66-77 - [c8]Hardik Sharma, Jongse Park, Divya Mahajan, Emmanuel Amaro, Joon Kyung Kim, Chenkai Shao, Asit Mishra, Hadi Esmaeilzadeh:
From high-level deep neural models to FPGAs. MICRO 2016: 17:1-17:12 - 2015
- [j1]Divya Mahajan, Kartik Ramkrishnan, Rudra Jariwala, Amir Yazdanbakhsh, Jongse Park, Bradley Thwaites, Anandhavel Nagendrakumar, Abbas Rahimi, Hadi Esmaeilzadeh, Kia Bazargan:
Axilog: Abstractions for Approximate Hardware Design and Reuse. IEEE Micro 35(5): 16-30 (2015) - [c7]Amir Yazdanbakhsh, Divya Mahajan, Bradley Thwaites, Jongse Park, Anandhavel Nagendrakumar, Sindhuja Sethuraman, Kartik Ramkrishnan, Nishanthi Ravindran, Rudra Jariwala, Abbas Rahimi, Hadi Esmaeilzadeh, Kia Bazargan:
Axilog: language support for approximate hardware design. DATE 2015: 812-817 - [c6]Amir Yazdanbakhsh, Jongse Park, Hardik Sharma, Pejman Lotfi-Kamran, Hadi Esmaeilzadeh:
Neural acceleration for GPU throughput processors. MICRO 2015: 482-493 - [c5]Jongse Park, Hadi Esmaeilzadeh, Xin Zhang, Mayur Naik, William Harris:
FlexJava: language support for safe and modular approximate programming. ESEC/SIGSOFT FSE 2015: 745-757 - 2014
- [c4]Bradley Thwaites, Gennady Pekhimenko, Hadi Esmaeilzadeh, Amir Yazdanbakhsh, Onur Mutlu, Jongse Park, Girish Mururu, Todd C. Mowry:
Rollback-free value prediction with approximate loads. PACT 2014: 493-494 - [c3]Renée St. Amant, Amir Yazdanbakhsh, Jongse Park, Bradley Thwaites, Hadi Esmaeilzadeh, Arjang Hassibi, Luis Ceze, Doug Burger:
General-purpose code acceleration with limited-precision analog computation. ISCA 2014: 505-516 - 2013
- [c2]Jaewon Choi, Jongse Park, Jinho Seol, Seungryoul Maeng:
Isolated Mini-domain for Trusted Cloud Computing. CCGRID 2013: 194-195 - 2012
- [c1]Jongse Park, DaeWoo Lee, Bokyeong Kim, Jaehyuk Huh, Seungryoul Maeng:
Locality-aware dynamic VM reconfiguration on MapReduce clouds. HPDC 2012: 27-36
Coauthor Index
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last updated on 2024-10-11 17:28 CEST by the dblp team
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