Zongwu Wang

According to our database, Zongwu Wang authored at least 46 papers between 2021 and 2025.

Collaborative distances:

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

2025

FlexQuant: A Flexible and Efficient Dynamic Precision Switching Framework for LLM Quantization.

Fangxin Liu, Zongwu Wang, JinHong Xia, Junping Zhao, Jian Liu, Haibing Guan, Li Jiang

CoRR, June, 2025

MILLION: Mastering Long-Context LLM Inference Via Outlier-Immunized KV Product Quantization.

Zongwu Wang, Peng Xu, Fangxin Liu, Yiwei Hu, Qingxiao Sun, Gezi Li, Cheng Li, Xuan Wang, Li Jiang, Haibing Guan

CoRR, April, 2025

ALLMod: Exploring Area-Efficiency of LUT-based Large Number Modular Reduction via Hybrid Workloads.

Fangxin Liu, Haomin Li, Zongwu Wang, Bo Zhang, Mingzhe Zhang, Shoumeng Yan, Li Jiang, Haibing Guan

CoRR, March, 2025

SpMMPlu-Pro: An Enhanced Compiler Plug-In for Efficient SpMM and Sparsity Propagation Algorithm.

Shiyuan Huang, Fangxin Liu, Tao Yang, Zongwu Wang, Ning Yang, Li Jiang

IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., February, 2025

STCO: Enhancing Training Efficiency via Structured Sparse Tensor Compilation Optimization.

Shiyuan Huang, Fangxin Liu, Tian Li, Zongwu Wang, Ning Yang, Haomin Li, Li Jiang

ACM Trans. Design Autom. Electr. Syst., 2025

FATE: Boosting the Performance of Hyper-Dimensional Computing Intelligence with Flexible Numerical DAta TypE.

Haomin Li, Fangxin Liu, Yichi Chen, Zongwu Wang, Shiyuan Huang, Ning Yang, Dongxu Lyu, Li Jiang

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

CROSS: Compiler-Driven Optimization of Sparse DNNs Using Sparse/Dense Computation Kernels.

Fangxin Liu, Shiyuan Huang, Ning Yang, Zongwu Wang, Haomin Li, Li Jiang

Proceedings of the IEEE International Symposium on High Performance Computer Architecture, 2025

EVASION: Efficient KV CAche CompreSsion vIa PrOduct QuaNtization.

Zongwu Wang, Fangxin Liu, Peng Xu, Qingxiao Sun, Junping Zhao, Li Jiang

Proceedings of the Design, Automation & Test in Europe Conference, 2025

OPS: Outlier-Aware Precision-Slice Framework for LLM Acceleration.

Fangxin Liu, Ning Yang, Zongwu Wang, Xuanpeng Zhu, Haidong Yao, Xiankui Xiong, Qi Sun, Li Jiang

Proceedings of the Design, Automation & Test in Europe Conference, 2025

HyperDyn: Dynamic Dimensional Masking for Efficient Hyper-Dimensional Computing.

Fangxin Liu, Haomin Li, Zongwu Wang, Dongxu Lyu, Li Jiang

Proceedings of the Design, Automation & Test in Europe Conference, 2025

TAIL: Exploiting Temporal Asynchronous Execution for Efficient Spiking Neural Networks with Inter-Layer Parallelism.

Haomin Li, Fangxin Liu, Zongwu Wang, Dongxu Lyu, Shiyuan Huang, Ning Yang, Qi Sun, Zhuoran Song, Li Jiang

Proceedings of the Design, Automation & Test in Europe Conference, 2025

Exploiting Differential-Based Data Encoding for Enhanced Query Efficiency.

Fangxin Liu, Zongwu Wang, Peng Xu, Shiyuan Huang, Li Jiang

Proceedings of the 30th Asia and South Pacific Design Automation Conference, 2025

NeuronQuant: Accurate and Efficient Post-Training Quantization for Spiking Neural Networks.

Haomin Li, Fangxin Liu, Zewen Sun, Zongwu Wang, Shiyuan Huang, Ning Yang, Li Jiang

Proceedings of the 30th Asia and South Pacific Design Automation Conference, 2025

2024

ERA-BS: Boosting the Efficiency of ReRAM-Based PIM Accelerator With Fine-Grained Bit-Level Sparsity.

Fangxin Liu, Wenbo Zhao, Zongwu Wang, Yongbiao Chen, Xiaoyao Liang, Li Jiang

IEEE Trans. Computers, September, 2024

TokenRing: An Efficient Parallelism Framework for Infinite-Context LLMs via Bidirectional Communication.

Zongwu Wang, Fangxin Liu, Mingshuai Li, Li Jiang

CoRR, 2024

COMPASS: SRAM-Based Computing-in-Memory SNN Accelerator with Adaptive Spike Speculation.

Zongwu Wang, Fangxin Liu, Ning Yang, Shiyuan Huang, Haomin Li, Li Jiang

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

LowPASS: A Low power PIM-based accelerator with Speculative Scheme for SNNs.

Fangxin Liu, Shiyuan Huang, Longyu Zhao, Li Jiang, Zongwu Wang

Proceedings of the 29th ACM/IEEE International Symposium on Low Power Electronics and Design, 2024

UM-PIM: DRAM-based PIM with Uniform & Shared Memory Space.

Yilong Zhao, Mingyu Gao, Fangxin Liu, Yiwei Hu, Zongwu Wang, Han Lin, Jin Li, He Xian, Hanlin Dong, Tao Yang, Naifeng Jing, Xiaoyao Liang, Li Jiang

Proceedings of the 51st ACM/IEEE Annual International Symposium on Computer Architecture, 2024

Ninja: A Hardware Assisted System for Accelerating Nested Address Translation.

Longyu Zhao, Zongwu Wang, Fangxin Liu, Li Jiang

Proceedings of the 42nd IEEE International Conference on Computer Design, 2024

T-BUS: Taming Bipartite Unstructured Sparsity for Energy-Efficient DNN Acceleration.

Ning Yang, Fangxin Liu, Zongwu Wang, Zhiyan Song, Tao Yang, Li Jiang

Proceedings of the 42nd IEEE International Conference on Computer Design, 2024

PS4: A Low Power SNN Accelerator with Spike Speculative Scheme.

Zongwu Wang, Fangxin Liu, Xin Tang, Li Jiang

Proceedings of the 42nd IEEE International Conference on Computer Design, 2024

HOLES: Boosting Large Language Models Efficiency with Hardware-Friendly Lossless Encoding.

Fangxin Liu, Ning Yang, Zhiyan Song, Zongwu Wang, Li Jiang

Proceedings of the 42nd IEEE International Conference on Computer Design, 2024

SPARK: Scalable and Precision-Aware Acceleration of Neural Networks via Efficient Encoding.

Fangxin Liu, Ning Yang, Haomin Li, Zongwu Wang, Zhuoran Song, Songwen Pei, Li Jiang

Proceedings of the IEEE International Symposium on High-Performance Computer Architecture, 2024

EOS: An Energy-Oriented Attack Framework for Spiking Neural Networks.

Ning Yang, Fangxin Liu, Zongwu Wang, Haomin Li, Zhuoran Song, Songwen Pei, Li Jiang

Proceedings of the 61st ACM/IEEE Design Automation Conference, 2024

INSPIRE: Accelerating Deep Neural Networks via Hardware-friendly Index-Pair Encoding.

Fangxin Liu, Ning Yang, Zhiyan Song, Zongwu Wang, Haomin Li, Shiyuan Huang, Zhuoran Song, Songwen Pei, Li Jiang

Proceedings of the 61st ACM/IEEE Design Automation Conference, 2024

TEAS: Exploiting Spiking Activity for Temporal-wise Adaptive Spiking Neural Networks.

Fangxin Liu, Haomin Li, Ning Yang, Zongwu Wang, Tao Yang, Li Jiang

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

PAAP-HD: PIM-Assisted Approximation for Efficient Hyper-Dimensional Computing.

Fangxin Liu, Haomin Li, Ning Yang, Yichi Chen, Zongwu Wang, Tao Yang, Li Jiang

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

TSTC: Enabling Efficient Training via Structured Sparse Tensor Compilation.

Shiyuan Huang, Fangxin Liu, Tian Li, Zongwu Wang, Haomin Li, Li Jiang

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

2023

SoBS-X: Squeeze-Out Bit Sparsity for ReRAM-Crossbar-Based Neural Network Accelerator.

Fangxin Liu, Zongwu Wang, Yongbiao Chen, Zhezhi He, Tao Yang, Xiaoyao Liang, Li Jiang

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

SIMSnn: A Weight-Agnostic ReRAM-based Search-In-Memory Engine for SNN Acceleration.

Fangxin Liu, Wenbo Zhao, Zongwu Wang, Xiaokang Yang, Li Jiang

Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2023

2022

IVQ: In-Memory Acceleration of DNN Inference Exploiting Varied Quantization.

Fangxin Liu, Wenbo Zhao, Zongwu Wang, Yilong Zhao, Tao Yang, Yiran Chen, Li Jiang

IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2022

Cross-layer Designs against Non-ideal Effects in ReRAM-based Processing-in-Memory System.

Chen Nie, Zongwu Wang, Qidong Tang, Chenyang Lv, Li Jiang, Zhezhi He

Proceedings of the 23rd International Symposium on Quality Electronic Design, 2022

Randomize and Match: Exploiting Irregular Sparsity for Energy Efficient Processing in SNNs.

Fangxin Liu, Zongwu Wang, Wenbo Zhao, Yongbiao Chen, Tao Yang, Xiaokang Yang, Li Jiang

Proceedings of the IEEE 40th International Conference on Computer Design, 2022

DynSNN: A Dynamic Approach to Reduce Redundancy in Spiking Neural Networks.

Fangxin Liu, Wenbo Zhao, Yongbiao Chen, Zongwu Wang, Fei Dai

Proceedings of the IEEE International Conference on Acoustics, 2022

DTQAtten: Leveraging Dynamic Token-based Quantization for Efficient Attention Architecture.

Tao Yang, Dongyue Li, Zhuoran Song, Yilong Zhao, Fangxin Liu, Zongwu Wang, Zhezhi He, Li Jiang

Proceedings of the 2022 Design, Automation & Test in Europe Conference & Exhibition, 2022

Self-Terminating Write of Multi-Level Cell ReRAM for Efficient Neuromorphic Computing.

Zongwu Wang, Zhezhi He, Rui Yang, Shiquan Fan, Jie Lin, Fangxin Liu, Yueyang Jia, Chenxi Yuan, Qidong Tang, Li Jiang

Proceedings of the 2022 Design, Automation & Test in Europe Conference & Exhibition, 2022

SATO: spiking neural network acceleration via temporal-oriented dataflow and architecture.

Fangxin Liu, Wenbo Zhao, Zongwu Wang, Yongbiao Chen, Tao Yang, Zhezhi He, Xiaokang Yang, Li Jiang

Proceedings of the DAC '22: 59th ACM/IEEE Design Automation Conference, San Francisco, California, USA, July 10, 2022

EBSP: evolving bit sparsity patterns for hardware-friendly inference of quantized deep neural networks.

Fangxin Liu, Wenbo Zhao, Zongwu Wang, Yongbiao Chen, Zhezhi He, Naifeng Jing, Xiaoyao Liang, Li Jiang

Proceedings of the DAC '22: 59th ACM/IEEE Design Automation Conference, San Francisco, California, USA, July 10, 2022

PIM-DH: ReRAM-based processing-in-memory architecture for deep hashing acceleration.

Fangxin Liu, Wenbo Zhao, Yongbiao Chen, Zongwu Wang, Zhezhi He, Rui Yang, Qidong Tang, Tao Yang, Cheng Zhuo, Li Jiang

Proceedings of the DAC '22: 59th ACM/IEEE Design Automation Conference, San Francisco, California, USA, July 10, 2022

HAWIS: Hardware-Aware Automated WIdth Search for Accurate, Energy-Efficient and Robust Binary Neural Network on ReRAM Dot-Product Engine.

Qidong Tang, Zhezhi He, Fangxin Liu, Zongwu Wang, Yiyuan Zhou, Yinghuan Zhang, Li Jiang

Proceedings of the 27th Asia and South Pacific Design Automation Conference, 2022

SpikeConverter: An Efficient Conversion Framework Zipping the Gap between Artificial Neural Networks and Spiking Neural Networks.

Fangxin Liu, Wenbo Zhao, Yongbiao Chen, Zongwu Wang, Li Jiang

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

SME: ReRAM-based Sparse-Multiplication-Engine to Squeeze-Out Bit Sparsity of Neural Network.

Fangxin Liu, Wenbo Zhao, Yilong Zhao, Zongwu Wang, Tao Yang, Zhezhi He, Naifeng Jing, Xiaoyao Liang, Li Jiang

CoRR, 2021

Improving Neural Network Efficiency via Post-training Quantization with Adaptive Floating-Point.

Fangxin Liu, Wenbo Zhao, Zhezhi He, Yanzhi Wang, Zongwu Wang, Changzhi Dai, Xiaoyao Liang, Li Jiang

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

SME: ReRAM-based Sparse-Multiplication-Engine to Squeeze-Out Bit Sparsity of Neural Network.

Fangxin Liu, Wenbo Zhao, Zhezhi He, Zongwu Wang, Yilong Zhao, Tao Yang, Jingnai Feng, Xiaoyao Liang, Li Jiang

Proceedings of the 39th IEEE International Conference on Computer Design, 2021

Bit-Transformer: Transforming Bit-level Sparsity into Higher Preformance in ReRAM-based Accelerator.

Fangxin Liu, Wenbo Zhao, Zhezhi He, Zongwu Wang, Yilong Zhao, Yongbiao Chen, Li Jiang

Proceedings of the IEEE/ACM International Conference On Computer Aided Design, 2021

IM3A: Boosting Deep Neural Network Efficiency via In-Memory Addressing-Assisted Acceleration.

Fangxin Liu, Wenbo Zhao, Zongwu Wang, Tao Yang, Li Jiang

Proceedings of the GLSVLSI '21: Great Lakes Symposium on VLSI 2021, 2021