| 2026 | HPCA | PASCAL: A Phase-Aware Scheduling Algorithm for Serving Reasoning-based Large Language Models. | Eunyeong Cho, Jehyeon Bang, Ranggi Hwang, Minsoo Rhu |
| 2025 | ISCA | 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, Minsoo Rhu |
| 2024 | ASPLOS | 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 |
| 2024 | ISCA | Pre-gated MoE: An Algorithm-System Co-Design for Fast and Scalable Mixture-of-Expert Inference. | Ranggi Hwang, Jianyu Wei, Shijie Cao, Changho Hwang, Xiaohu Tang, Ting Cao, Mao Yang |
| 2023 | HPCA | 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 |
| 2022 | MICRO | DiVa: An Accelerator for Differentially Private Machine Learning. | Beomsik Park, Ranggi Hwang, Dongho Yoon, Yoonhyuk Choi, Minsoo Rhu |
| 2020 | ISCA | Centaur: A Chiplet-based, Hybrid Sparse-Dense Accelerator for Personalized Recommendations. | Ranggi Hwang, Taehun Kim, Youngeun Kwon, Minsoo Rhu |