Joongun Park

According to our database, Joongun Park authored at least 13 papers between 2018 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

MLCommons Chakra: Advancing Performance Benchmarking and Co-design using Standardized Execution Traces.

Srinivas Sridharan, Theodor-Adrian Badea, Andy Balogh, Bradford M. Beckmann, Brian Coutinho, Louis Feng, Sheng Fu, Sanshan Gao, Mehryar Garakani, Taekyung Heo, David Kanter, Josh Ladd, Ziwei Li, Winston Liu, Changhai Man, Dan Mihailescu, Spandan More, Joongun Park, Ashwin Ramachandran, Vinay Ramakrishnaiah, Saeed Rashidi, Vijay Janapa Reddi, Puneet Sharma, Phio Tian, William Won, Hanjiang Wu, Huan Xu, Jinsun Yoo, Tushar Krishna

CoRR, May, 2026

SCALE: Tackling Communication Bottlenecks in Confidential Distributed Machine Learning.

Joongun Park, Yongqin Wang, Huan Xu, Hanjiang Wu, Mengyuan Li, Tushar Krishna

Proceedings of the IEEE International Symposium on High Performance Computer Architecture, 2026

Compositional AI Beyond LLMs: System Implications of Neuro-Symbolic-Probabilistic Architectures.

Zishen Wan, Hanchen Yang, Jiayi Qian, Ritik Raj, Joongun Park, Chenyu Wang, Arijit Raychowdhury, Tushar Krishna

Proceedings of the 31st ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2026

2025

STAGE: A Symbolic Tensor grAph GEnerator for distributed AI system co-design.

Changhai Man, Joongun Park, Hanjiang Wu, Huan Xu, Srinivas Sridharan, Tushar Krishna

CoRR, November, 2025

Characterizing the Efficiency of Distributed Training: A Power, Performance, and Thermal Perspective.

Seokjin Go, Joongun Park, Spandan More, Hanjiang Wu, Irene Wang, Aaron Jezghani, Tushar Krishna, Divya Mahajan

Proceedings of the 58th IEEE/ACM International Symposium on Microarchitecture, 2025

NSFlow: An End-to-End FPGA Framework with Scalable Dataflow Architecture for Neuro-Symbolic AI.

Hanchen Yang, Zishen Wan, Ritik Raj, Joongun Park, Ziwei Li, Ananda Samajdar, Arijit Raychowdhury, Tushar Krishna

Proceedings of the 62nd ACM/IEEE Design Automation Conference, 2025

2024

Hardware-hardened Sandbox Enclaves for Trusted Serverless Computing.

Joongun Park, Seunghyo Kang, Sanghyeon Lee, Taehoon Kim, Jongse Park, Youngjin Kwon, Jaehyuk Huh

ACM Trans. Archit. Code Optim., March, 2024

Enhancing Scalability and Performance in Influence Maximization with Optimized Parallel Processing.

Hanjiang Wu, Huan Xu, Joongun Park, Jesmin Jahan Tithi, Fabio Checconi, Jordi Wolfson-Pou, Fabrizio Petrini, Tushar Krishna

Proceedings of the SC24-W: Workshops of the International Conference for High Performance Computing, 2024

Supporting Trusted Virtual Machines with Hardware-Based Secure Remote Memory.

Taekyung Heo, Seunghyo Kang, Sanghyeon Lee, Soojin Hwang, Joongun Park, Jaehyuk Huh

Proceedings of the 2024 ACM SIGPLAN International Symposium on Memory Management, 2024

2021

Stockade: Hardware Hardening for Distributed Trusted Sandboxes.

Joongun Park, Seunghyo Kang, Sanghyeon Lee, Taehoon Kim, Jongse Park, Youngjin Kwon, Jaehyuk Huh

CoRR, 2021

2020

Nested Enclave: Supporting Fine-grained Hierarchical Isolation with SGX.

Joongun Park, Naegyeong Kang, Taehoon Kim, Youngjin Kwon, Jaehyuk Huh

Proceedings of the 47th ACM/IEEE Annual International Symposium on Computer Architecture, 2020

2019

ShieldStore: Shielded In-memory Key-value Storage with SGX.

Taehoon Kim, Joongun Park, Jae-Woo Chang, Seungheun Jeon, Jaehyuk Huh

Proceedings of the Fourteenth EuroSys Conference 2019, Dresden, Germany, March 25-28, 2019, 2019

2018

Secure In-memory Key-Value Storage with SGX.

Taehoon Kim, Joongun Park, Jae-Woo Chang, Seungheun Jeon, Jaehyuk Huh

Proceedings of the ACM Symposium on Cloud Computing, 2018