Publications
Computer Architecture and Systems
Dongho Yoon*, Taehun Kim*, Jae W. Lee, and Minsoo Rhu, "A Quantitative Analysis of State Space Model-based Large Language Model: Study of Hungry Hungry Hippos" IEEE Computer Architecture Letters, 2024
Dongho Yoon and Taehun Kim are co-first authors of this work*
[Paper]
Dongjae Lee, Bongjoon Hyun, Taehun Kim and Minsoo Rhu, "Analysis of Data Transfer Bottlenecks in Commercial PIM Systems: A Study with UPMEM-PIM," IEEE Computer Architecture Letters, 2024
[Paper]
Ranggi Hwang*, Jianyu Wei*, Shijie Cao, Changho Hwang, Xiaohu Tang, Ting Cao, and Mao Yang, "Pre-gated MoE: An Algorithm-System Co-Design for Fast and Scalable Mixture-of-Expert Inference," The 51st IEEE/ACM International Symposium on Computer Architecture (ISCA-51), Buenos Aires, Argentina, June 2024
Ranggi Hwang and Jianyu Wei are co-first authors of this work*
Acceptance Rate: 19% (83 among 423)
[Paper]
Yunjae Lee*, Hyeseong Kim*, and Minsoo Rhu, "PreSto: An In-Storage Data Preprocessing System for Training Recommendation Models," The 51st IEEE/ACM International Symposium on Computer Architecture (ISCA-51), Buenos Aires, Argentina, June 2024
Yunjae Lee and Hyeseong Kim are co-first authors of this work*
Acceptance Rate: 19% (83 among 423)
[Paper]
Yujeong Choi, Jiin Kim, and Minsoo Rhu, "ElasticRec: A Microservice-based Model Serving Architecture Enabling Elastic Resource Scaling for Recommendation Models," The 51st IEEE/ACM International Symposium on Computer Architecture (ISCA-51), Buenos Aires, Argentina, June 2024
Acceptance Rate: 19% (83 among 423)
[Paper]
Juntaek Lim, Youngeun Kwon, Ranggi Hwang, Kiwan Maeng, Edward Suh, and Minsoo Rhu, "LazyDP: Co-Designing Algorithm-Software for Scalable Training of Differentially Private Recommendation Models," The 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS-29), San Diego, CA, Apr. 2024
Acceptance Rate: 20% (193 among 921)
Maximilian Lam, Jeff Johnson, Wenjie Xiong, Kiwan Maeng, Udit Gupta, Yang Li, Liangzhen Lai, Minsoo Rhu, Hsien-Hsin S. Lee, Vijay Janapa Reddi, Gu-Yeon Wei, David Brooks, Edward Suh, "GPU-based Private Information Retrieval for On-Device Machine Learning Inference," The 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS-29), San Diego, CA, Mar. 2024
Acceptance Rate: 20% (193 among 921)
[Paper]
Bongjoon Hyun, Taehun Kim, Dongjae Lee, and Minsoo Rhu, "Pathfinding Future PIM Architectures by Demystifying a Commercial PIM Technology," The 30th IEEE International Symposium on High-Performance Computer Architecture (HPCA-30), Edinburgh, UK, Feb. 2024
Best Paper Award
Acceptance Rate: 18% (75 among 410)
[Paper] [Code] [Slides] [Presentation]
Hyeseong Kim*, Yunjae Lee*, and Minsoo Rhu, "FPGA-Accelerated Data Preprocessing for Personalized Recommendation Systems," IEEE Computer Architecture Letters, Jan. 2024
Hyeseong Kim and Yunjae Lee are co-first authors of this work*
Ranggi Hwang*, Minhoo Kang*, Jiwon Lee, Dongyun Kam, Youngjoo Lee, and Minsoo Rhu, "GROW: A Row-Stationary Sparse-Dense GEMM Accelerator for Memory-Efficient Graph Convolutional Neural Networks," The 29th IEEE International Symposium on High-Performance Computer Architecture (HPCA-29), Montreal, Canada, Feb. 2023
Ranggi Hwang and Minhoo Kang are co-first authors of this work*
Acceptance Rate: 25% (91 among 364)
[Paper]
Seonho Lee, Ranggi Hwang, Jongse Park, and Minsoo Rhu, "HAMMER: Hardware-friendly Approximate Computing for Self-attention with Mean-redistribution and Linearization," IEEE Computer Architecture Letters, Jan. 2023
[Paper]
Beomsik Park*, Ranggi Hwang*, Dongho Yoon, Yoonhyuk Choi, and Minsoo Rhu, "DiVa: An Accelerator for Differentially Private Machine Learning," The 55th IEEE/ACM International Symposium on Microarchitecture (MICRO-55), Chicago, IL, Oct. 2022
Beomsik Park and Ranggi Hwang are co-first authors of this work*
Acceptance Rate: 22% (83 among 369)
[Paper]
Jongmin Kim, Gwangho Lee, Sangpyo Kim, Gina Sohn, John Kim, Minsoo Rhu, and Jung Ho Ahn, "ARK: Fully Homomorphic Encryption Accelerator with Runtime Data Generation and Inter-Operation Key Reuse," The 55th IEEE/ACM International Symposium on Microarchitecture (MICRO-55), Chicago, IL, Oct. 2022
Acceptance Rate: 22% (83 among 369)
[Paper]
Yunseong Kim, Yujeong Choi, and Minsoo Rhu, "PARIS and ELSA: An Elastic Scheduling Algorithm for Reconfigurable Multi-GPU Inference Servers," The 59th ACM/ESDA/IEEE Design Automation Conference (DAC), San Francisco, CA, Jul. 2022
Acceptance Rate: 23%
[Paper] [Extended version] [Slide] [Presentation]
Yunjae Lee, Jinha Chung, and Minsoo Rhu, "SmartSAGE: Training Large-scale Graph Neural Networks using In-Storage Processing Architectures," The 49th IEEE/ACM International Symposium on Computer Architecture (ISCA-49), New York, NY, June 2022
Acceptance Rate: 16% (67 among 400)
[Paper]
Youngeun Kwon and Minsoo Rhu, " Training Personalized Recommendation Systems from (GPU) Scratch: Look Forward not Backwards," The 49th IEEE/ACM International Symposium on Computer Architecture (ISCA-49), New York, NY, June 2022
Acceptance Rate: 16% (67 among 400)
[Paper]
Sangpyo Kim, Jongmin Kim, Michael Jaemin Kim, Wonkyung Jung, John Kim, Minsoo Rhu, and Jung Ho Ahn, "BTS: An Accelerator for Bootstrappable Fully Homomorphic Encryption," The 49th IEEE/ACM International Symposium on Computer Architecture (ISCA-49), New York, NY, June 2022
Acceptance Rate: 16% (67 among 400)
[Paper]
Jaehyun Park, Byeongho Kim, Sungmin Yun, Eojin Lee, Minsoo Rhu, and Jung Ho Ahn, "TRiM: Enhancing Processor-Memory Interfaces with Scalable Tensor Reduction in Memory," The 54th IEEE/ACM International Symposium on Microarchitecture (MICRO-54), Athens, Greece, Oct. 2021
Acceptance Rate: 22% (94 among 430)
[Paper]
Bongjoon Hyun, Jiwon Lee, and Minsoo Rhu, "Characterization and Analysis of Deep Learning for 3D Point Cloud Analytics," IEEE Computer Architecture Letters, Jul. 2021
[Paper]
Yunjae Lee, Youngeun Kwon, and Minsoo Rhu, "Understanding the Implication of Non-Volatile Memory for Large-Scale Graph Neural Network Training," IEEE Computer Architecture Letters, Jul. 2021
[Paper]
Youngeun Kwon, Yunjae Lee, and Minsoo Rhu, "Tensor Casting: Co-Designing Algorithm-Architecture for Personalized Recommendation Training," The 27th IEEE International Symposium on High-Performance Computer Architecture (HPCA-27), Seoul, South Korea, Feb. 2021
Acceptance Rate: 24% (63 among 258)
[Paper] [Presentation]
Yujeong Choi, Yunseong Kim, and Minsoo Rhu, "LazyBatching: An SLA-aware Batching System for Cloud Machine Learning Inference," The 27th IEEE International Symposium on High-Performance Computer Architecture (HPCA-27), Seoul, South Korea, Feb. 2021
Acceptance Rate: 24% (63 among 258)
[Paper] [Presentation]
Jaeguk Ahn, Cheolgyu Jin, Jiho Kim, Minsoo Rhu, Yunsi Fei, David Kaeli, and John Kim, "Trident: A Hybrid Correlation-Collision GPU Cache Timing Attack for AES Key Recovery," The 27th IEEE International Symposium on High-Performance Computer Architecture (HPCA-27), Seoul, South Korea, Feb. 2021
Acceptance Rate: 24% (63 among 258)
[Paper]
Byeongho Kim, Jaehyun Park, Eojin Lee, Minsoo Rhu, and Jung Ho Ahn, "TRiM: Tensor Reduction in Memory," IEEE Computer Architecture Letters, Dec. 2020
[Paper]
Ranggi Hwang, Taehun Kim, Youngeun Kwon, and Minsoo Rhu, "Centaur: A Chiplet-based, Hybrid Sparse-Dense Accelerator for Personalized Recommendations," The 47th IEEE/ACM International Symposium on Computer Architecture (ISCA-47), Valencia, Spain, June 2020
Acceptance Rate: 18% (77 among 421)
[Paper] [Presentation]
Bongjoon Hyun, Youngeun Kwon, Yujeong Choi, John Kim, and Minsoo Rhu, "NeuMMU: Architectural Support for Efficient Address Translations in NPUs," The 25th ACM International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS-25), Lausanne, Switzerland, Mar. 2020
Selected for IEEE Micro Top Picks - Honorable Mention ("IEEE Micro - Special Issue on Top Picks from the 2020 Computer Architecture Conferences")
Acceptance Rate: 18% (86 among 476)
[Paper] [Presentation]
Yujeong Choi and Minsoo Rhu, "PREMA: A Predictive Multi-task Scheduling Algorithm For Preemptible Neural Processing Units," The 26th IEEE International Symposium on High-Performance Computer Architecture (HPCA-26), San Diego, CA, Feb. 2020
Acceptance Rate: 19% (48 among 248)
[Paper]
Youngeun Kwon, Yunjae Lee, and Minsoo Rhu, "TensorDIMM: A Practical Near-Memory Processing Architecture for Embeddings and Tensor Operations in Deep Learning," The 52nd IEEE/ACM International Symposium on Microarchitecture (MICRO-52), Columbus, OH, Oct. 2019
Selected for IEEE Micro Top Picks - Honorable Mention ("IEEE Micro - Special Issue on Top Picks from the 2019 Computer Architecture Conferences")
Acceptance Rate: 22% (79 among 344)
[Paper]
Youngeun Kwon and Minsoo Rhu, "A Disaggregated Memory System for Deep Learning," IEEE Micro, Special Issue on Machine Learning Acceleration, Volume 39, Issue 5, Sep/Oct., 2019
[Paper]
Youngeun Kwon and Minsoo Rhu, "Beyond the Memory Wall: A Case for Memory-centric HPC System for Deep Learning," The 51st IEEE/ACM International Symposium on Microarchitecture (MICRO-51), Fukuoka, Japan, Oct. 2018
Acceptance Rate: 21% (74 among 351)
[Paper] [Presentation]
Youngeun Kwon and Minsoo Rhu, "A Case for Memory-Centric HPC System Architecture for Training Deep Neural Networks," IEEE Computer Architecture Letters, Jul. 2018
[Paper]
Maohua Zhu, Jason Clemons, Jeff Pool, Minsoo Rhu, Stephen W. Keckler, and Yuan Xie, "Structurally Sparsified Backward Propagation for Faster Long Short-Term Memory Training," arXiv.org
Minsoo Rhu, Mike O'Connor, Niladrish Chatterjee, Jeff Pool, Youngeun Kwon, and Stephen W. Keckler, "Compressing DMA Engine: Leveraging Activation Sparsity for Training Deep Neural Networks," The 24th IEEE International Symposium on High-Performance Computer Architecture (HPCA-24), Vienna, Austria, Feb. 2018
Minsoo Rhu, "Accelerator-centric Deep Learning Systems for Enhanced Scalability, Energy-Efficiency, and Programmability", (Invited Paper) The 23rd Asia and South Pacific Design Automation Conference (ASP-DAC), Jeju, South Korea, Feb. 2018
Youngsok Kim, Jae-Eon Jo, Hanhwi Jang, Minsoo Rhu, Hanjun Kim, and Jangwoo Kim, "GPUpd: A Fast and Scalable Multi-GPU Architecture Using Cooperative Projection and Distribution," The 50th IEEE/ACM International Symposium on Microarchitecture (MICRO-50), Boston, MA, Oct. 2017
Acceptance Rate: 19% (61 among 327)
[Paper]
Angshuman Parashar, Minsoo Rhu, Anurag Mukkara, Antonio Puglielli, Rangharajan Venkatesan, Brucek Khailany, Joel Emer, Stephen W. Keckler, and William J. Dally, "SCNN: An Accelerator for Compressed-sparse Convolutional Neural Networks," The 44th IEEE/ACM International Symposium on Computer Architecture (ISCA-44), Toronto, ON, Canada, June 2017
Niladrish Chatterjee, Mike O'Connor, Donghyuk Lee, Daniel R. Johnson, Stephen W. Keckler, Minsoo Rhu, and William J. Dally, "Architecting an Energy-Efficient DRAM System For GPUs," The 23rd IEEE International Symposium on High-Performance Computer Architecture (HPCA-23), Austin, TX, Feb. 2017
Acceptance Rate:
Minsoo Rhu, Natalia Gimelshein, Jason Clemons, Arslan Zulfiqar, and Stephen W. Keckler, "vDNN: Virtualized Deep Neural Networks for Scalable, Memory-Efficient Neural Network Design," The 49th IEEE/ACM International Symposium on Microarchitecture (MICRO-49), Taipei, Taiwan, Oct. 2016
Seong-Lyong Gong, Minsoo Rhu, Jungrae Kim, Jinsuk Chung, and Mattan Erez, "CLEAN-ECC: High Reliability ECC for Adaptive Granularity Memory System," The 48th IEEE/ACM International Symposium on Microarchitecture (MICRO-48), Waikiki, HI, Dec. 2015
Acceptance Rate: 22% (61 among 283)
Dong Li*, Minsoo Rhu, Daniel R. Johnson, Mike O'Connor, Mattan Erez, Doug Burger, Donald S. Fussell, and Stephen W. Keckler, "Priority-Based Cache Allocation for Throughput Processors," The 21st IEEE International Symposium on High-Performance Computer Architecture (HPCA-21), San Francisco, CA, Feb. 2015
Jingwen Leng, Yazhou Zu, Minsoo Rhu, Meeta Sharma Gupta, and Vijay Janapa Reddi, "GPUVolt: Characterizing and Mitigating Voltage Noise in GPUs," The IEEE/ACM International Symposium on Low Power Electronics and Design (ISLPED-2014), La Jolla, CA, Aug. 2014
Acceptance Rate: 23%
Minsoo Rhu, Michael Sullivan, Jingwen Leng and Mattan Erez, "A Locality-Aware Memory Hierarchy for Energy-Efficient GPU Architectures," The 46th IEEE/ACM International Symposium on Microarchitecture (MICRO-46), Davis, CA, Dec. 2013
Minsoo Rhu and Mattan Erez, "Maximizing SIMD Resource Utilization in GPGPUs with SIMD Lane Permutation," The 40th IEEE/ACM International Symposium on Computer Architecture (ISCA-40), Tel-Aviv, Israel, Jun. 2013
Minsoo Rhu and Mattan Erez, "The Dual-Path Execution Model for Efficient GPU Control Flow," The 19th IEEE International Symposium on High-Performance Computer Architecture (HPCA-19), Shenzhen, China, Feb. 2013
Minsoo Rhu and Mattan Erez, "CAPRI: Prediction of Compaction-Adequacy for Handling Control-Divergence in GPGPU Architectures," The 39th IEEE/ACM International Symposium on Computer Architecture (ISCA-39), Portland, OR, Jun. 2012
ASIC Design
Minsoo Rhu and In-Cheol Park, "Optimization of Arithmetic Coding for JPEG2000," IEEE Transactions on Circuits and System for Video Technology, Vol.20, No.3, pp.446-451, Mar. 2010
Minsoo Rhu and In-Cheol Park, "Memory-less Bit-Plane Coder Architecture for JPEG2000 with Concurrent Column-Stripe Coding", IEEE International Conference on Image Processing 2009 (ICIP 2009), Cairo, Egypt, p.2673-2676, Nov. 2009
Minsoo Rhu and In-Cheol Park, "Architecture Design of a High-Performance Dual-Symbol Binary Arithmetic Coder for JPEG2000", IEEE International Conference on Image Processing 2009 (ICIP 2009), Cairo, Egypt, p.2665-2668, Nov. 2009
Minsoo Rhu and In-Cheol Park, "A Novel Trace-Pipelined Binary Arithmetic Coder Architecture for JPEG2000", IEEE Workshop on Signal Processing Systems 2009 (SiPS 2009), Tampere, Finland, p.243-248, Oct. 2009