Given the ever-increasing integration density and design complexity of computing systems, security and robustness become one of the first-priority citizens that need to be considered while designing a system. Though various solutions have been proposed and implemented in real systems for the known attacks, different systems and workloads have unique security holes and need different defenses. We would like to explore unique vulnerabilities of various systems and workloads and research effective countermeasures. [NSF 2114514]
Most of emerging workloads need massive data- and thread-level parallelism to handle big data inputs. Various throughput processors (e.g., GPU) are equpped with hundreds of cores and several mega-bytes of on-chip memories. These abundant resources are a double-edged sword that are inevitable for increasing execution concurrency but at the same time require high power consumption. In this project, we would like to optimize or revisit throughput processors to achieve higher throughput per energy consumption. [NSF 2341039]
In the post-Moore era, we can't simply rely on more transistors per unit area to produce better throughput. Domain-specific accelerators may be able to satisfy ever-increasing computing power demands of emerging workloads with given transistor and power budget. However, here comes another challenging questions, 'what types of workloads should we support with dedicated accelerators?' and 'how can the existing computing systems smoothly support the accelerators?'. In this project, we would like to answer these questions such that the new computing era can be smoothly and cost effectively phased into.
For an agile support for quickly evolving computing fields, it is essential to have a thorough undestanding of new workloads. To enable fair evaluations of various accelerators, it is important to have balanced and good-quality benchmark suites of emerging workloads. In this project, we aim to design various cutting-edge applications and explore optimization potentials. The workloads will be compiled into benchmark suites so that the community can use the suites for their research.Â
GPU Architecture (ISBN: 978-981-15-6401-7)
Hyeran Jeon
In: Chattopadhyay, A. (eds) Handbook of Computer Architecture. Springer, 2023
Co-authored by Hyeran Jeon
IEEE 1924.1, Nov 2022
Current status, needs, and challenges in Heterogeneous and Composable Memory from the HCM workshop (HPCA’23)
Hyeran Jeon, Dong Li, and Jie Ren
ACM SigArch Blog, May 2023
Performing logical operations in a memory
Hyeran Jeon and Gabriel H. Loh
US20150199150 A1
Hyeran Jeon, Woohyong Lee, Mingyu Lee, Woongee Kim, Jiseong Oh, Jagun Kwon, and Taekgyun Ko
US8423723 B2
* Students in MoCA Lab
Fang Chen, Gourav Datta, Mujahid Al Rafi*, Hyeran Jeon, Meng Tang
Transactions on Machine Learning Research (TMLR), 2025
Yuan Feng*, Yuke Li, Jiwon Lee, Won Woo Ro, and Hyeran Jeon
The 52nd International Symposium on Computer Architecture (ISCA), Tokyo, Japan, June 2025
Mao Lin*, Yuan Feng*, Guilherme Cox, and Hyeran Jeon
The 52nd International Symposium on Computer Architecture (ISCA), Tokyo, Japan, June 2025
Mao Lin*, and Hyeran Jeon
ACM Workshop on Machine Learning and Systems (EuroMLSys), Rotterdam, The Netherlands, Mar 2025
Mujahid Al Rafi*, Kevin Chau*, and Hyeran Jeon
ACM Workshop on General Purpose GPUs (GPGPU), Las Vegas, LV, Feb 2025
Dong Xu, Yuan Feng*, Kwangsik Shin, Daewoo Kim, Hyeran Jeon, and Dong Li
The 36th ACM/IEEE International Conference for High Performance Computing, Performance Measurement, Modeling and Tools (SC), Atlanta, GA, Nov 2024
Yuan Feng*, Seonjin Na, Hyesoon Kim, and Hyeran Jeon
The 51st International Symposium on Computer Architecture (ISCA), Buenos Aires, Argentina, June 2024
Mujahid Al Rafi*, Yuan Feng*, Fan Yao, Meng Tang, and Hyeran Jeon
IEEE International Symposium on Workload Characterization (IISWC), Ghent, Belgium, Oct 2023 (acceptance rate 30%)
Understanding System Resilience for Converged Computing of Cloud, Edge, and HPCÂ
Luanzheng Guo, Jay Lofstead, Jie Ren, Ignacio Laguna, Gokcen Kestor, Line Pouchard, Dossay Oryspayev, and Hyeran Jeon
Workshop on Converged Computing to be co-located with ISC'23 (WOCC), Hamburg, Germany, May 2023
Yuan Feng* and Hyeran Jeon
ACM Workshop on General Purpose GPUs (GPGPU), Montreal, Canada, Feb 2023
Accelerate Transformers with Efficient MemoizationÂ
Yuan Feng*, Dong Li, and Hyeran Jeon
Student Research Competition at IEEE/ACM International Symposium on Microarchitecture (MICRO), Chicago, Illinois, Oct 2022
Nigel Bernard*, Hoa Nguyen*, Aman Chandan*, Savyasachi Jagdeeshan*, Namdev Prabhugaonkar*, Rutuja Shah*, and Hyeran Jeon
arXiv Preprint, July 2022
Mujahid Al Rafi*, Yuan Feng,* and Hyeran Jeon
arXiv Preprint, July 2022
Characterization of Semantic Segmentation Models on Mobile Platforms for Self-Navigation in Disaster-Struck Zones
Ryan Zelek* and Hyeran Jeon
IEEE Access, vol 10, pp 73388--73402, July 2022, DOI 10.1109/ACCESS.2022.3190014 (impact factor 3.9)
Mujahid Al Rafi*, Yuan Feng*, and Hyeran Jeon
Workshop on Negative results, Opportunities, Perspectives, and Experiences In conjunction with ASPLOS-27 (NOPE), Feb 2022
A New Foe in GPUs: Power Side-Channel Attacks on Neural Network
Hyeran Jeon, Nima Karimian, and Tamara Lehman
IEEE 22nd International Symposium on Quality Electronic Design (ISQED), Apr 2021
Sentinel: Efficient Tensor Migration and Allocation on Heterogeneous Memory Systems for Deep Learning
Jie Ren, Jiaolin Luo, Kai Wu, Minjia Zhang, Hyeran Jeon and Dong Li
IEEE International Symposium on High Performance Computer Architecture (HPCA), Feb 2021
Two-Stage Sequence Model for Maximum Throughput in Cluster Tools
Taehee Jeong*, Kunj Parikh*, Raymond Chau, Chung Ho Huang, Henry Chan and Hyeran Jeon
IEEE 19th World Symposium on Applied Machine Intelligence and Informatics (SAMI), Jan 2021
Enabling Edge-based Self-Navigation in Earthquake-Struck Zones
Ryan Zelek*, Vignesh Kumar Venkateshwar*, Sai Kiran Duggineni*, Renu Dighe*, and Hyeran Jeon
International Conference on Hardware/Software Codesign and System Synthesis (CODES+ISSS) - ESWEEK, Sep 2020
Locality-aware GPU Register File
Hyeran Jeon, Hodjat Asghari Esfeden, Nael B. Abu-Ghazaleh, Daniel Wong, and Sindhuja Elango*
IEEE Computer Architecture Letter (IEEE CAL), Vol. 18, Issue 2, July-Dec. 1 2019 (impact factor 2.3)
Going Deeper or Wider : Throughput Prediction for Cluster Tools with Machine Learning
Taehee Jeong*, Deeksha Prakash Kankalale*, Raymond Chau, and Hyeran Jeon
IEEE/ACM International Conference on Big Data Computing, Applications and Technologies (BDCAT), Auckland University of Technology, New Zealand, Dec 2019
Understanding of GPU Architectural Vulnerability for Deep Learning Workloads
Danny Santoso* and Hyeran Jeon
The 32nd IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems (DFT), ESA-ESTEC & TU Delft, Netherlands, Oct 2019
Detailed Characterization of Deep Neural Networks on GPUs and FPGAs
Aajna Karki*, Chethan Palangotu Keshava*, Spoorthi Mysore Shivakumar*, Joshua Skow*, Goutam Madhukeshwar Hegde*, and Hyeran Jeon
ACM Workshop on General Purpose GPUs (GPGPU), Providence, RI, April 2019
Tango: A Deep Neural Network Benchmark Suite for Various Accelerators
Aajna Karki*, Chethan Palangotu Keshava*, Spoorthi Mysore Shivakumar*, Joshua Skow*, Goutam Madhukeshwar Hegde*, and Hyeran Jeon
IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS), Madison, WI, March 2019
CORF: Coalescing Operand Register File for GPUs
Hodjat Asghari Esfeden, Farzad Khorasani, Hyeran Jeon, Daniel Wong, and Nael Abu-Ghazaleh
The 24th International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS), Providence, RI, April 2019
CTA-Aware Prefetching and Scheduling for GPU
Gunjae Koo, Hyeran Jeon, Zhenhong Liu, Nam Sung Kim, and Murali Annavaram
The 32nd IEEE International Parallel and Distributed Processing Symposium (IPDPS), Vancouver, BC, May 2018
Parallelizing Deep Packet Inspection on GPU
Meera Ramesh* and Hyeran Jeon
IEEE International Conference on Big Data Computing Service and Applications (BigDataService), Bamberg, Germany, March 2018
Toward Machine Generated Passwords
Simon Woo, Wenzhe Li, Hyeran Jeon
Conference on Information Security and Cryptography (CISC-W), Seoul, Korea, December 2017 (Outstanding Paper Award)
The NVIDIA AI City Challenge
Milind Naphade, David C. Anastasiu, Anuj Sharma, Vamsi Jagrlamudi, Hyeran Jeon, Kaikai Liu, Ming-Ching Chang, Siwei Lyu, and Zeyu Gao
IEEE Smart World Congress, San Jose, CA, USA, August 2017
Edge-based street object detection
Sushma Nagaraj*, Bhushan Muthiyan*, Swetha Ravi*, Virginia Menezes*, Kalki Kapoor*, Hyeran Jeon
IEEE Smart World Congress, San Jose, CA, USA, August 2017
CNN-based Android Malware Detection
Meenu Ganesh*, Priyanka Pednekar*, Pooja Prabhuswamy*, Divyashri Sreedharan Nair*, Younghee Park, Hyeran Jeon
IEEE International Conference on Software Security and Assurance (ICSSA), Altoona, PA, Jul 2017
Smart Illegal Dumping Detection
Akshay Dabholkar*, Bhushan Muthiyan*, Shilpa Srinivasan*, Swetha Ravi*, Hyeran Jeon, Jerry Gao
IEEE International Conference on Big Data Computing Service and Applications (BigDataService), San Francisco, CA, Apr 2017
Pilot Register File: Energy Efficient Partitioned Register File for GPUs
Mohammad Abdel-Majeed, Hyeran Jeon, Alireza Shafaei, Massoud Pedram, and Murali Annavaram
The 23rd IEEE Symposium on High Performance Computer Architecture (HPCA), Austin, TX, Feb 2017
Improving Energy Efficiency of GPUs through Data Compression and Compressed Execution
Sangpil Lee, Keunsoo Kim, Gunjae Koo, Hyeran Jeon, Won Woo Ro, and Murali Annavaram
IEEE Transactions on Computers (TC), vol. 66, issue. 5, October 2016
Efficient Intra-SM Slicing through Dynamic Resource Partitioning for GPU Multiprogramming
Qiumin Xu, Hyeran Jeon, Keunsoo Kim, Won Woo Ro, and Murali Annavaram
The 43rd International Symposium on Computer Architecture (ISCA), Seoul, Korea, Jun 2016
GPGPU Register File Virtualization
Hyeran Jeon, Gokul Subramanian Ravi, Nam Sung Kim, and Murali Annavaram
The 48th IEEE/ACM International Symposium on Microarchitecture (MICRO), Waikiki, Hawaii, December 2015
Revealing Critical Loads and Hidden Data Locality in GPGPU applications
Gunjae Koo, Hyeran Jeon, and Murali Annavaram
IEEE International Symposium on Workload Characterization (IISWC), Atlanta, GA, Oct 2015
Warped-Compression: Enabling Power Efficient GPUs through Register Compression
Sangpil Lee, Keunsoo Kim, Gunjae Koo, Hyeran Jeon, Won Woo Ro, and Murali Annavaram
The 42nd Internaltional Symposium on Computer Architecture (ISCA), Portland, OR, Jun 2015
Warped-RE: Low-Cost Error Detection and Correction in GPUs
Mohammad Abdel-Majeed, Waleed Dweik, Hyeran Jeon, and Murali Annavaram
IEEE/IFIP International Conference on Dependable Systems and Networks (DSN), Rio De Janeiro, Brazil, Jun 2015
Graph processing on GPUs: Where are the bottlenecks?
Qiumin Xu, Hyeran Jeon and Murali Annavaram
IEEE International Symposium on Workload Characterization (IISWC), Raleigh, NC, Oct 2014
Efficient RAS support for Die-stacked DRAM
Hyeran Jeon, Gabriel H. Loh and Murali Annavaram
IEEE International Test Conference (ITC), Seattle, WA, Oct 2014
Investigating Hybrid SSD FTL Schemes for Hadoop Workloads
Hyeran Jeon, Kaoutar El Maghraoui and Gokul Kandiraju
ACM International Conference on Computing Frontiers (CF), Ischia, Italy, May 2013
Architectural Vulnerability Modeling and Analysis of Integrated Graphics Processors
Hyeran Jeon, Mark Wilkening, Vilas Sridharan, Sudhanva Gurumurthi and Gabriel H. Loh
The 9th IEEE Workshop on Silicon Errors in Logic - System Effect (SELSE), Stanford, CA, March 2013
Warped-DMR: Light-weight Error Detection for GPGPU
Hyeran Jeon and Murali Annavaram
The 45th IEEE/ACM International Symposium on Microarchitecture (MICRO), Vancouver, BC, December 2012
Load Unbalancing Strategy for Multi-Core Embedded Processors
Hyeran Jeon, Woo Hyong Lee and Sung Woo Chung
IEEE Transactions on Computers (TC), vol. 59, no. 10, pp. 1434-1440, October 2010
Parallel Exact Inference on a CPU-GPGPU Heterogenous System
Hyeran Jeon, Yinglong Xia and Viktor K. Prasanna
The 39th International Conference on Parallel Processing (ICPP), San Diego, CA, September 2010
Node Level Primitives for Exact Inference on GPGPU
Hyeran Jeon, Yinglong Xia and Viktor K. Prasanna
The 17th International Conference on Systems, Signals and Image Processing (IWSSIP), Rio de Janeiro, Brazil, Jun 2010