Architecture design of a high-performance dual-symbol binary arithmetic coder for JPEG2000. - Minsoo Rhu; In-Cheol Park (ICIP, 2009)

Memory-less bit-plane coder architecture for JPEG2000 with concurrent column-stripe coding. - Minsoo Rhu; In-Cheol Park (ICIP, 2009)

A novel trace-pipelined binary arithmetic coder architecture for JPEG2000. - Minsoo Rhu; In-Cheol Park (SiPS, 2009)

Optimization of Arithmetic Coding for JPEG2000. - Minsoo Rhu; In-Cheol Park (IEEE Trans. Circuits Syst. Video Technol., 2010)

CAPRI: Prediction of compaction-adequacy for handling control-divergence in GPGPU architectures. - Minsoo Rhu; Mattan Erez (ISCA, 2012)

The dual-path execution model for efficient GPU control flow. - Minsoo Rhu; Mattan Erez (HPCA, 2013)

Maximizing SIMD resource utilization in GPGPUs with SIMD lane permutation. - Minsoo Rhu; Mattan Erez (ISCA, 2013)

A locality-aware memory hierarchy for energy-efficient GPU architectures. - Minsoo Rhu; Michael B. Sullivan 001; Jingwen Leng; Mattan Erez (MICRO, 2013)

GPUVolt: modeling and characterizing voltage noise in GPU architectures. - Jingwen Leng; Yazhou Zu; Minsoo Rhu; Meeta Sharma Gupta; Vijay Janapa Reddi (ISLPED, 2014)

Priority-based cache allocation in throughput processors. - Dong Li; Minsoo Rhu; Daniel R. Johnson; Mike O'Connor; Mattan Erez; Doug Burger; Donald S. Fussell; Stephen W. Redder (HPCA, 2015)

CLEAN-ECC: high reliability ECC for adaptive granularity memory system. - Seong-Lyong Gong; Minsoo Rhu; Jungrae Kim; Jinsuk Chung; Mattan Erez (MICRO, 2015)

vDNN: Virtualized deep neural networks for scalable, memory-efficient neural network design. - Minsoo Rhu; Natalia Gimelshein; Jason Clemons; Arslan Zulfiqar; Stephen W. Keckler (MICRO, 2016)

Virtualizing Deep Neural Networks for Memory-Efficient Neural Network Design. - Minsoo Rhu; Natalia Gimelshein; Jason Clemons; Arslan Zulfiqar; Stephen W. Keckler (CoRR, 2016)

Architecting an Energy-Efficient DRAM System for GPUs. - Niladrish Chatterjee; Mike O'Connor; Donghyuk Lee; Daniel R. Johnson; Stephen W. Keckler; Minsoo Rhu; William J. Dally (HPCA, 2017)

SCNN: An Accelerator for Compressed-sparse Convolutional Neural Networks. - Angshuman Parashar; Minsoo Rhu; Anurag Mukkara; Antonio Puglielli; Rangharajan Venkatesan; Brucek Khailany; Joel S. Emer; Stephen W. Keckler; William J. Dally (ISCA, 2017)

GPUpd: a fast and scalable multi-GPU architecture using cooperative projection and distribution. - Youngsok Kim; Jae-Eon Jo; Hanhwi Jang; Minsoo Rhu; Hanjun Kim 001; Jangwoo Kim (MICRO, 2017)

Compressing DMA Engine: Leveraging Activation Sparsity for Training Deep Neural Networks. - Minsoo Rhu; Mike O'Connor; Niladrish Chatterjee; Jeff Pool; Stephen W. Keckler (CoRR, 2017)

Accelerator-centric deep learning systems for enhanced scalability, energy-efficiency, and programmability. - Minsoo Rhu (ASP-DAC, 2018)

Compressing DMA Engine: Leveraging Activation Sparsity for Training Deep Neural Networks. - Minsoo Rhu; Mike O'Connor; Niladrish Chatterjee; Jeff Pool; Youngeun Kwon; Stephen W. Keckler (HPCA, 2018)

Beyond the Memory Wall: A Case for Memory-Centric HPC System for Deep Learning. - Youngeun Kwon; Minsoo Rhu (MICRO, 2018)

A Case for Memory-Centric HPC System Architecture for Training Deep Neural Networks. - Youngeun Kwon; Minsoo Rhu (IEEE Comput. Archit. Lett., 2018)

Structurally Sparsified Backward Propagation for Faster Long Short-Term Memory Training. - Maohua Zhu; Jason Clemons; Jeff Pool; Minsoo Rhu; Stephen W. Keckler; Yuan Xie 001 (CoRR, 2018)

TensorDIMM: A Practical Near-Memory Processing Architecture for Embeddings and Tensor Operations in Deep Learning. - Youngeun Kwon; Yunjae Lee; Minsoo Rhu (MICRO, 2019)

A Disaggregated Memory System for Deep Learning. - Youngeun Kwon; Minsoo Rhu (IEEE Micro, 2019)

Bandwidth Bottleneck in Network-on-Chip for High-Throughput Processors. - Jiho Kim; Sanghun Cho; Minsoo Rhu; Ali Bakhoda; Tor M. Aamodt; John Kim 001 (PACT, 2020)

NeuMMU: Architectural Support for Efficient Address Translations in Neural Processing Units. - Bongjoon Hyun; Youngeun Kwon; Yujeong Choi; John Kim 001; Minsoo Rhu (ASPLOS, 2020)

PREMA: A Predictive Multi-Task Scheduling Algorithm For Preemptible Neural Processing Units. - Yujeong Choi; Minsoo Rhu (HPCA, 2020)

Centaur: A Chiplet-based, Hybrid Sparse-Dense Accelerator for Personalized Recommendations. - Ranggi Hwang; Taehun Kim; Youngeun Kwon; Minsoo Rhu (ISCA, 2020)

LazyBatching: An SLA-aware Batching System for Cloud Machine Learning Inference. - Yujeong Choi; Yunseong Kim; Minsoo Rhu (CoRR, 2020)

Trident: A Hybrid Correlation-Collision GPU Cache Timing Attack for AES Key Recovery. - Jaeguk Ahn; Cheolgyu Jin; Jiho Kim; Minsoo Rhu; Yunsi Fei; David R. Kaeli; John Kim 001 (HPCA, 2021)

Lazy Batching: An SLA-aware Batching System for Cloud Machine Learning Inference. - Yujeong Choi; Yunseong Kim; Minsoo Rhu (HPCA, 2021)

Tensor Casting: Co-Designing Algorithm-Architecture for Personalized Recommendation Training. - Youngeun Kwon; Yunjae Lee; Minsoo Rhu (HPCA, 2021)

TRiM: Enhancing Processor-Memory Interfaces with Scalable Tensor Reduction in Memory. - Jaehyun Park 006; Byeongho Kim; Sungmin Yun 001; Eojin Lee; Minsoo Rhu; Jung Ho Ahn (MICRO, 2021)

Characterization and Analysis of Deep Learning for 3D Point Cloud Analytics. - Bongjoon Hyun; Jiwon Lee; Minsoo Rhu (IEEE Comput. Archit. Lett., 2021)

TRiM: Tensor Reduction in Memory. - Byeongho Kim; Jaehyun Park 006; Eojin Lee; Minsoo Rhu; Jung Ho Ahn (IEEE Comput. Archit. Lett., 2021)

Understanding the Implication of Non-Volatile Memory for Large-Scale Graph Neural Network Training. - Yunjae Lee; Youngeun Kwon; Minsoo Rhu (IEEE Comput. Archit. Lett., 2021)

PARIS and ELSA: an elastic scheduling algorithm for reconfigurable multi-GPU inference servers. - Yunseong Kim; Yujeong Choi; Minsoo Rhu (DAC, 2022)

BTS: an accelerator for bootstrappable fully homomorphic encryption. - Sangpyo Kim; Jongmin Kim 007; Michael Jaemin Kim; Wonkyung Jung; John Kim 001; Minsoo Rhu; Jung Ho Ahn (ISCA, 2022)

Training personalized recommendation systems from (GPU) scratch: look forward not backwards. - Youngeun Kwon; Minsoo Rhu (ISCA, 2022)

SmartSAGE: training large-scale graph neural networks using in-storage processing architectures. - Yunjae Lee; Jinha Chung; Minsoo Rhu (ISCA, 2022)

ARK: Fully Homomorphic Encryption Accelerator with Runtime Data Generation and Inter-Operation Key Reuse. - Jongmin Kim 007; Gwangho Lee; Sangpyo Kim; Gina Sohn; Minsoo Rhu; John Kim 001; Jung Ho Ahn (MICRO, 2022)

DiVa: An Accelerator for Differentially Private Machine Learning. - Beomsik Park; Ranggi Hwang; Dongho Yoon; Yoonhyuk Choi; Minsoo Rhu (MICRO, 2022)

GROW: A Row-Stationary Sparse-Dense GEMM Accelerator for Memory-Efficient Graph Convolutional Neural Networks. - Ranggi Hwang; Minhoo Kang; Jiwon Lee; Dongyun Kam; Youngjoo Lee; Minsoo Rhu (HPCA, 2023)

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)

Hera: A Heterogeneity-Aware Multi-Tenant Inference Server for Personalized Recommendations. - Yujeong Choi; John Kim 001; Minsoo Rhu (CoRR, 2023)

GPU-based Private Information Retrieval for On-Device Machine Learning Inference. - Maximilian Lam; Jeff Johnson 004; Wenjie Xiong 001; Kiwan Maeng; Udit Gupta; Yang Li 183; Liangzhen Lai; Ilias Leontiadis; Minsoo Rhu; Hsien-Hsin S. Lee; Vijay Janapa Reddi; Gu-Yeon Wei; et al. (ASPLOS (1), 2024)

LazyDP: Co-Designing Algorithm-Software for Scalable Training of Differentially Private Recommendation Models. - Juntaek Lim; Youngeun Kwon; Ranggi Hwang; Kiwan Maeng; G. Edward Suh; Minsoo Rhu (ASPLOS (2), 2024)

Pathfinding Future PIM Architectures by Demystifying a Commercial PIM Technology. - Bongjoon Hyun; Taehun Kim; Dongjae Lee; Minsoo Rhu (HPCA, 2024)

ElasticRec: A Microservice-based Model Serving Architecture Enabling Elastic Resource Scaling for Recommendation Models. - Yujeong Choi; Jiin Kim; Minsoo Rhu (ISCA, 2024)

PreSto: An In-Storage Data Preprocessing System for Training Recommendation Models. - Yunjae Lee; Hyeseong Kim; Minsoo Rhu (ISCA, 2024)

vTrain: A Simulation Framework for Evaluating Cost-Effective and Compute-Optimal Large Language Model Training. - Jehyeon Bang; Yujeong Choi; Myeongwoo Kim; Yongdeok Kim; Minsoo Rhu (MICRO, 2024)

Uncovering Real GPU NoC Characteristics: Implications on Interconnect Architecture. - Zhixian Jin; Christopher Rocca; Jiho Kim; Hans Kasan; Minsoo Rhu; Ali Bakhoda; Tor M. Aamodt; John Kim 001 (MICRO, 2024)

PIM-MMU: A Memory Management Unit for Accelerating Data Transfers in Commercial PIM Systems. - Dongjae Lee; Bongjoon Hyun; Taehun Kim; Minsoo Rhu (MICRO, 2024)

Characterization and Analysis of Text-to-Image Diffusion Models. - Eunyeong Cho; Jehyeon Bang; Minsoo Rhu (IEEE Comput. Archit. Lett., 2024)

FPGA-Accelerated Data Preprocessing for Personalized Recommendation Systems. - Hyeseong Kim; Yunjae Lee; Minsoo Rhu (IEEE Comput. Archit. Lett., 2024)

Analysis of Data Transfer Bottlenecks in Commercial PIM Systems: A Study With UPMEM-PIM. - Dongjae Lee; Bongjoon Hyun; Taehun Kim; Minsoo Rhu (IEEE Comput. Archit. Lett., 2024)

A Quantitative Analysis of State Space Model-Based Large Language Model: Study of Hungry Hungry Hippos. - Dongho Yoon; Taehun Kim; Jae W. Lee; Minsoo Rhu (IEEE Comput. Archit. Lett., 2024)

PREBA: A Hardware/Software Co-Design for Multi-Instance GPU based AI Inference Servers. - Gwangoo Yeo; Jiin Kim; Yujeong Choi; Minsoo Rhu (CoRR, 2024)

Debunking the CUDA Myth Towards GPU-based AI Systems: Evaluation of the Performance and Programmability of Intel's Gaudi NPU for AI Model Serving. - Yunjae Lee; Juntaek Lim; Jehyeon Bang; Eunyeong Cho; Huijong Jeong; Taesu Kim; Hyungjun Kim; Joonhyung Lee; Jinseop Im; Ranggi Hwang; Se Jung Kwon; Dongsoo Lee; et al. (ISCA, 2025)

A Characterization of Generative Recommendation Models: Study of Hierarchical Sequential Transduction Unit. - Taehun Kim; Yunjae Lee; Juntaek Lim; Minsoo Rhu (IEEE Comput. Archit. Lett., 2025)

Characterization and Analysis of the 3D Gaussian Splatting Rendering Pipeline. - Jiwon Lee; Yunjae Lee; Youngeun Kwon; Minsoo Rhu (IEEE Comput. Archit. Lett., 2025)

Debunking the CUDA Myth Towards GPU-based AI Systems. - Yunjae Lee; Juntaek Lim; Jehyeon Bang; Eunyeong Cho; Huijong Jeong; Taesu Kim; Hyungjun Kim; Joonhyung Lee; Jinseop Im; Ranggi Hwang; Se Jung Kwon; Dongsoo Lee; et al. (CoRR, 2025)

PIM-malloc: A Fast and Scalable Dynamic Memory Allocator for Processing-In-Memory (PIM) Architectures. - Dongjae Lee; Bongjoon Hyun; Youngjin Kwon; Minsoo Rhu (CoRR, 2025)

The Cost of Dynamic Reasoning: Demystifying AI Agents and Test-Time Scaling from an AI Infrastructure Perspective. - Jiin Kim; Byeongjun Shin; Jinha Chung; Minsoo Rhu (CoRR, 2025)

Mamba-X: An End-to-End Vision Mamba Accelerator for Edge Computing Devices. - Dongho Yoon; Gungyu Lee; Jaewon Chang; Yunjae Lee; Dongjae Lee; Minsoo Rhu (CoRR, 2025)