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2020 – today
- 2025
[c10]Ruokai Yin, Yuhang Li, Priyadarshini Panda:
PacQ: A SIMT Microarchitecture for Efficient Dataflow in Hyper-asymmetric GEMMs. DAC 2025: 1-7- [i15]Ruokai Yin, Yuhang Li, Priyadarshini Panda:
PacQ: A SIMT Microarchitecture for Efficient Dataflow in Hyper-asymmetric GEMMs. CoRR abs/2502.18627 (2025) - [i14]Yuhang Li, Ruokai Yin, Donghyun Lee, Shiting Xiao, Priyadarshini Panda:
GPTQv2: Efficient Finetuning-Free Quantization for Asymmetric Calibration. CoRR abs/2504.02692 (2025) - [i13]Donghyun Lee, Yuhang Li, Ruokai Yin, Shiting Xiao, Priyadarshini Panda:
Memba: Membrane-driven Parameter-Efficient Fine-Tuning for Mamba. CoRR abs/2506.18184 (2025) - [i12]Ruokai Yin, Yuhang Li, Donghyun Lee, Priyadarshini Panda:
DuoGPT: Training-free Dual Sparsity through Activation-aware Pruning in LLMs. CoRR abs/2506.20194 (2025) - [i11]Arkapravo Ghosh, Abhishek Moitra, Abhiroop Bhattacharjee, Ruokai Yin, Priyadarshini Panda:
DiffAxE: Diffusion-driven Hardware Accelerator Generation and Design Space Exploration. CoRR abs/2508.10303 (2025) - [i10]Ruokai Yin, Sattwik Deb Mishra, Xuan Zuo, Hokchhay Tann, Preyas Shah, Apala Guha:
Learning to Shard: RL for Co-optimizing the Parallelism Degrees and Per-operator Sharding Dimensions in Distributed LLM Inference. CoRR abs/2509.00217 (2025) - 2024
- [j5]Youngeun Kim, Yuhang Li, Abhishek Moitra, Ruokai Yin, Priyadarshini Panda:
Do we really need a large number of visual prompts? Neural Networks 177: 106390 (2024) - [j4]Ruokai Yin
, Youngeun Kim, Yuhang Li, Abhishek Moitra, Nitin Satpute, Anna Hambitzer, Priyadarshini Panda:
Workload-Balanced Pruning for Sparse Spiking Neural Networks. IEEE Trans. Emerg. Top. Comput. Intell. 8(4): 2897-2907 (2024) - [c9]Ruokai Yin, Yuhang Li, Abhishek Moitra, Priyadarshini Panda:
MINT: Multiplier-less INTeger Quantization for Energy Efficient Spiking Neural Networks. ASPDAC 2024: 830-835 - [c8]Donghyun Lee, Ruokai Yin, Youngeun Kim, Abhishek Moitra, Yuhang Li, Priyadarshini Panda:
TT-SNN: Tensor Train Decomposition for Efficient Spiking Neural Network Training. DATE 2024: 1-6 - [c7]Abhiroop Bhattacharjee, Ruokai Yin, Abhishek Moitra, Priyadarshini Panda:
Are SNNs Truly Energy-efficient? - A Hardware Perspective. ICASSP 2024: 13311-13315 - [c6]Ruokai Yin, Youngeun Kim, Di Wu, Priyadarshini Panda:
LoAS: Fully Temporal-Parallel Dataflow for Dual-Sparse Spiking Neural Networks. MICRO 2024: 1107-1121 - [i9]Donghyun Lee, Ruokai Yin, Youngeun Kim, Abhishek Moitra, Yuhang Li, Priyadarshini Panda:
TT-SNN: Tensor Train Decomposition for Efficient Spiking Neural Network Training. CoRR abs/2401.08001 (2024) - [i8]Ruokai Yin, Youngeun Kim, Di Wu, Priyadarshini Panda:
LoAS: Fully Temporal-Parallel Datatflow for Dual-Sparse Spiking Neural Networks. CoRR abs/2407.14073 (2024) - 2023
- [j3]Ruokai Yin, Abhishek Moitra, Abhiroop Bhattacharjee, Youngeun Kim, Priyadarshini Panda:
SATA: Sparsity-Aware Training Accelerator for Spiking Neural Networks. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 42(6): 1926-1938 (2023) - [c5]Abhishek Moitra, Ruokai Yin, Priyadarshini Panda:
Energy-efficient Hardware Design for Spiking Neural Networks (Extended Abstract). ACSSC 2023: 543-544 - [c4]Abhishek Moitra, Ruokai Yin, Priyadarshini Panda:
Hardware Accelerators for Spiking Neural Networks for Energy-Efficient Edge Computing. ACM Great Lakes Symposium on VLSI 2023: 137-138 - [i7]Ruokai Yin, Youngeun Kim, Yuhang Li, Abhishek Moitra, Nitin Satpute, Anna Hambitzer, Priyadarshini Panda:
Workload-Balanced Pruning for Sparse Spiking Neural Networks. CoRR abs/2302.06746 (2023) - [i6]Ruokai Yin, Yuhang Li, Abhishek Moitra, Priyadarshini Panda:
MINT: Multiplier-less Integer Quantization for Spiking Neural Networks. CoRR abs/2305.09850 (2023) - [i5]Youngeun Kim, Yuhang Li, Abhishek Moitra, Ruokai Yin, Priyadarshini Panda:
Sharing Leaky-Integrate-and-Fire Neurons for Memory-Efficient Spiking Neural Networks. CoRR abs/2305.18360 (2023) - [i4]Abhiroop Bhattacharjee, Ruokai Yin, Abhishek Moitra, Priyadarshini Panda:
Are SNNs Truly Energy-efficient? - A Hardware Perspective. CoRR abs/2309.03388 (2023) - 2022
- [c3]Youngeun Kim, Yuhang Li, Hyoungseob Park, Yeshwanth Venkatesha, Ruokai Yin, Priyadarshini Panda:
Exploring Lottery Ticket Hypothesis in Spiking Neural Networks. ECCV (12) 2022: 102-120 - [i3]Ruokai Yin, Abhishek Moitra, Abhiroop Bhattacharjee, Youngeun Kim, Priyadarshini Panda:
SATA: Sparsity-Aware Training Accelerator for Spiking Neural Networks. CoRR abs/2204.05422 (2022) - [i2]Youngeun Kim, Yuhang Li, Hyoungseob Park, Yeshwanth Venkatesha, Ruokai Yin, Priyadarshini Panda:
Exploring Lottery Ticket Hypothesis in Spiking Neural Networks. CoRR abs/2207.01382 (2022) - [i1]Yuhang Li, Ruokai Yin, Hyoungseob Park, Youngeun Kim, Priyadarshini Panda:
Wearable-based Human Activity Recognition with Spatio-Temporal Spiking Neural Networks. CoRR abs/2212.02233 (2022) - 2021
- [j2]Di Wu, Ruokai Yin, Joshua San Miguel:
In-Stream Correlation-Based Division and Bit-Inserting Square Root in Stochastic Computing. IEEE Des. Test 38(6): 53-59 (2021) - [j1]Di Wu, Jingjie Li, Ruokai Yin, Hsuan Hsiao, Younghyun Kim, Joshua San Miguel:
uGEMM: Unary Computing for GEMM Applications. IEEE Micro 41(3): 50-56 (2021) - [c2]Di Wu, Ruokai Yin, Joshua San Miguel:
Normalized Stability: A Cross-Level Design Metric for Early Termination in Stochastic Computing. ASP-DAC 2021: 254-259 - 2020
- [c1]Di Wu, Jingjie Li, Ruokai Yin, Hsuan Hsiao, Younghyun Kim, Joshua San Miguel:
UGEMM: Unary Computing Architecture for GEMM Applications. ISCA 2020: 377-390
Coauthor Index
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