Ranggi Hwang

Publication Activity (10 Years)

Years Active: 2020-2024
Publications (10 Years): 11

Top Topics

Machine Learning

Convolutional Neural Networks

Motion Field Estimation

Top Venues

Publications

Juntaek Lim, Youngeun Kwon, Ranggi Hwang, Kiwan Maeng, G. Edward Suh, Minsoo Rhu
LazyDP: Co-Designing Algorithm-Software for Scalable Training of Differentially Private Recommendation Models. ASPLOS (2) (2024)
Ranggi Hwang, Jianyu Wei, Shijie Cao, Changho Hwang, Xiaohu Tang, Ting Cao, Mao Yang
Pre-gated MoE: An Algorithm-System Co-Design for Fast and Scalable Mixture-of-Expert Inference. ISCA (2024)
Juntaek Lim, Youngeun Kwon, Ranggi Hwang, Kiwan Maeng, G. Edward Suh, Minsoo Rhu
LazyDP: Co-Designing Algorithm-Software for Scalable Training of Differentially Private Recommendation Models. CoRR (2024)
Seonho Lee, Ranggi Hwang, Jongse Park, Minsoo Rhu
HAMMER: Hardware-Friendly Approximate Computing for Self-Attention With Mean-Redistribution And Linearization. IEEE Comput. Archit. Lett. 22 (1) (2023)
Ranggi Hwang, Minhoo Kang, Jiwon Lee, Dongyun Kam, Youngjoo Lee, Minsoo Rhu
GROW: A Row-Stationary Sparse-Dense GEMM Accelerator for Memory-Efficient Graph Convolutional Neural Networks. HPCA (2023)
Ranggi Hwang, Jianyu Wei, Shijie Cao, Changho Hwang, Xiaohu Tang, Ting Cao, Mao Yang, Minsoo Rhu
Pre-gated MoE: An Algorithm-System Co-Design for Fast and Scalable Mixture-of-Expert Inference. CoRR (2023)
Beomsik Park, Ranggi Hwang, Dongho Yoon, Yoonhyuk Choi, Minsoo Rhu
DiVa: An Accelerator for Differentially Private Machine Learning. MICRO (2022)
Minhoo Kang, Ranggi Hwang, Jiwon Lee, Dongyun Kam, Youngjoo Lee, Minsoo Rhu
GROW: A Row-Stationary Sparse-Dense GEMM Accelerator for Memory-Efficient Graph Convolutional Neural Networks. CoRR (2022)
Beomsik Park, Ranggi Hwang, Dongho Yoon, Yoonhyuk Choi, Minsoo Rhu
DiVa: An Accelerator for Differentially Private Machine Learning. CoRR (2022)
Ranggi Hwang, Taehun Kim, Youngeun Kwon, Minsoo Rhu
Centaur: A Chiplet-based, Hybrid Sparse-Dense Accelerator for Personalized Recommendations. ISCA (2020)
Ranggi Hwang, Taehun Kim, Youngeun Kwon, Minsoo Rhu
Centaur: A Chiplet-based, Hybrid Sparse-Dense Accelerator for Personalized Recommendations. CoRR (2020)