Ruokai Yin

According to our database, Ruokai Yin authored at least 24 papers between 2020 and 2025.

Collaborative distances:

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

2025

Learning to Shard: RL for Co-optimizing the Parallelism Degrees and Per-operator Sharding Dimensions in Distributed LLM Inference.

Ruokai Yin, Sattwik Deb Mishra, Xuan Zuo, Hokchhay Tann, Preyas Shah, Apala Guha

CoRR, September, 2025

DiffAxE: Diffusion-driven Hardware Accelerator Generation and Design Space Exploration.

Arkapravo Ghosh, Abhishek Moitra, Abhiroop Bhattacharjee, Ruokai Yin, Priyadarshini Panda

CoRR, August, 2025

DuoGPT: Training-free Dual Sparsity through Activation-aware Pruning in LLMs.

Ruokai Yin, Yuhang Li, Donghyun Lee, Priyadarshini Panda

CoRR, June, 2025

Memba: Membrane-driven Parameter-Efficient Fine-Tuning for Mamba.

Donghyun Lee, Yuhang Li, Ruokai Yin, Shiting Xiao, Priyadarshini Panda

CoRR, June, 2025

GPTQv2: Efficient Finetuning-Free Quantization for Asymmetric Calibration.

Yuhang Li, Ruokai Yin, Donghyun Lee, Shiting Xiao, Priyadarshini Panda

CoRR, April, 2025

PacQ: A SIMT Microarchitecture for Efficient Dataflow in Hyper-asymmetric GEMMs.

Ruokai Yin, Yuhang Li, Priyadarshini Panda

Proceedings of the 62nd ACM/IEEE Design Automation Conference, 2025

2024

Workload-Balanced Pruning for Sparse Spiking Neural Networks.

Ruokai Yin, Youngeun Kim, Yuhang Li, Abhishek Moitra, Nitin Satpute, Anna Hambitzer, Priyadarshini Panda

IEEE Trans. Emerg. Top. Comput. Intell., August, 2024

Do we really need a large number of visual prompts?

Youngeun Kim, Yuhang Li, Abhishek Moitra, Ruokai Yin, Priyadarshini Panda

Neural Networks, 2024

LoAS: Fully Temporal-Parallel Datatflow for Dual-Sparse Spiking Neural Networks.

Ruokai Yin, Youngeun Kim, Di Wu, Priyadarshini Panda

CoRR, 2024

LoAS: Fully Temporal-Parallel Dataflow for Dual-Sparse Spiking Neural Networks.

Ruokai Yin, Youngeun Kim, Di Wu, Priyadarshini Panda

Proceedings of the 57th IEEE/ACM International Symposium on Microarchitecture, 2024

Are SNNs Truly Energy-efficient? - A Hardware Perspective.

Abhiroop Bhattacharjee, Ruokai Yin, Abhishek Moitra, Priyadarshini Panda

Proceedings of the IEEE International Conference on Acoustics, 2024

TT-SNN: Tensor Train Decomposition for Efficient Spiking Neural Network Training.

Donghyun Lee, Ruokai Yin, Youngeun Kim, Abhishek Moitra, Yuhang Li, Priyadarshini Panda

Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2024

MINT: Multiplier-less INTeger Quantization for Energy Efficient Spiking Neural Networks.

Ruokai Yin, Yuhang Li, Abhishek Moitra, Priyadarshini Panda

Proceedings of the 29th Asia and South Pacific Design Automation Conference, 2024

2023

SATA: Sparsity-Aware Training Accelerator for Spiking Neural Networks.

Ruokai Yin, Abhishek Moitra, Abhiroop Bhattacharjee, Youngeun Kim, Priyadarshini Panda

IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., June, 2023

Sharing Leaky-Integrate-and-Fire Neurons for Memory-Efficient Spiking Neural Networks.

Youngeun Kim, Yuhang Li, Abhishek Moitra, Ruokai Yin, Priyadarshini Panda

CoRR, 2023

MINT: Multiplier-less Integer Quantization for Spiking Neural Networks.

Ruokai Yin, Yuhang Li, Abhishek Moitra, Priyadarshini Panda

CoRR, 2023

Hardware Accelerators for Spiking Neural Networks for Energy-Efficient Edge Computing.

Abhishek Moitra, Ruokai Yin, Priyadarshini Panda

Proceedings of the Great Lakes Symposium on VLSI 2023, 2023

Energy-efficient Hardware Design for Spiking Neural Networks (Extended Abstract).

Abhishek Moitra, Ruokai Yin, Priyadarshini Panda

Proceedings of the 57th Asilomar Conference on Signals, Systems, and Computers, ACSSC 2023, Pacific Grove, CA, USA, October 29, 2023

2022

Wearable-based Human Activity Recognition with Spatio-Temporal Spiking Neural Networks.

Yuhang Li, Ruokai Yin, Hyoungseob Park, Youngeun Kim, Priyadarshini Panda

CoRR, 2022

Exploring Lottery Ticket Hypothesis in Spiking Neural Networks.

Youngeun Kim, Yuhang Li, Hyoungseob Park, Yeshwanth Venkatesha, Ruokai Yin, Priyadarshini Panda

Proceedings of the Computer Vision - ECCV 2022, 2022

2021

uGEMM: Unary Computing for GEMM Applications.

Di Wu, Jingjie Li, Ruokai Yin, Hsuan Hsiao, Younghyun Kim, Joshua San Miguel

IEEE Micro, 2021

In-Stream Correlation-Based Division and Bit-Inserting Square Root in Stochastic Computing.

Di Wu, Ruokai Yin, Joshua San Miguel

IEEE Des. Test, 2021

Normalized Stability: A Cross-Level Design Metric for Early Termination in Stochastic Computing.

Di Wu, Ruokai Yin, Joshua San Miguel

Proceedings of the ASPDAC '21: 26th Asia and South Pacific Design Automation Conference, 2021

2020

UGEMM: Unary Computing Architecture for GEMM Applications.

Di Wu, Jingjie Li, Ruokai Yin, Hsuan Hsiao, Younghyun Kim, Joshua San Miguel

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