Ranggi Hwang

According to our database, Ranggi Hwang authored at least 11 papers between 2020 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

SpecMoE: A Fast and Efficient Mixture-of-Experts Inference via Self-Assisted Speculative Decoding.

Jehyeon Bang, Eunyeong Cho, Ranggi Hwang, Jinha Chung, Minsoo Rhu

CoRR, April, 2026

Exploring KV Cache Quantization in Multimodal Large Language Model Inference.

Hyesung Ahn, Ranggi Hwang, Minsoo Rhu

IEEE Comput. Archit. Lett., 2026

PASCAL: A Phase-Aware Scheduling Algorithm for Serving Reasoning-based Large Language Models.

Eunyeong Cho, Jehyeon Bang, Ranggi Hwang, Minsoo Rhu

Proceedings of the IEEE International Symposium on High Performance Computer Architecture, 2026

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, Minsoo Rhu

CoRR, January, 2025

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

Proceedings of the 52nd Annual International Symposium on Computer Architecture, 2025

2024

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

Proceedings of the 51st ACM/IEEE Annual International Symposium on Computer Architecture, 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

Proceedings of the 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2024

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

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

Proceedings of the IEEE International Symposium on High-Performance Computer Architecture, 2023

2022

DiVa: An Accelerator for Differentially Private Machine Learning.

Beomsik Park, Ranggi Hwang, Dongho Yoon, Yoonhyuk Choi, Minsoo Rhu

Proceedings of the 55th IEEE/ACM International Symposium on Microarchitecture, 2022

2020

Centaur: A Chiplet-based, Hybrid Sparse-Dense Accelerator for Personalized Recommendations.

Ranggi Hwang, Taehun Kim, Youngeun Kwon, Minsoo Rhu

Proceedings of the 47th ACM/IEEE Annual International Symposium on Computer Architecture, 2020