Zongwu Wang

68 papers A* 19A 11B 3C 6Misc 1Journal 17Unranked 11
YearRankTypeTitle / Venue / Authors
2026 — conf
BLADE: Boosting LLM Decoding's Communication Efficiency in DRAM-based PIM.
ASP-DAC
Yilong Zhao, Fangxin Liu, Zongwu Wang, Mingjian Li, Mingxing Zhang, Chixiao Chen, Li Jiang
2026 — conf
EARTH: An Efficient MoE Accelerator with Entropy-Aware Speculative Prefetch and Result Reuse.
ASPLOS (2)
Fangxin Liu, Ning Yang, Jingkui Yang, Zongwu Wang, Chenyang Guan, Yu Feng, Li Jiang, Haibing Guan
2026 A* conf
ORANGE: Exploring Ockham's Razor for Neural Rendering by Accelerating 3DGS on NPUs with GEMM-Friendly Blending and Balanced Workloads.
HPCA
Haomin Li, Yun Liang, Fangxin Liu, Bowen Zhu, Zongwu Wang, Yu Feng, Liqiang Lu, Li Jiang, Haibing Guan
2026 A* conf
SpecQuant: Spectral Decomposition and Adaptive Truncation for Ultra-Low-Bit LLMs Quantization.
AAAI
Zhixiong Zhao, Fangxin Liu, Junjie Wang, Chenyang Guan, Zongwu Wang, Li Jiang, Haibing Guan
2026 — conf
TFLOP: Towards Energy-Efficient LLM Inference An FPGA-Affinity Accelerator with Unified LUT-based OPtimization.
ASP-DAC
Zongwu Wang, Zhongyi Tang, Fangxin Liu, Chenyang Guan, Li Jiang, Haibing Guan
2025 A* conf
ALLMod: Exploring Area-Efficiency of LUT-based Large Number Modular Reduction via Hybrid Workloads.
DAC
Fangxin Liu, Haomin Li, Zongwu Wang, Bo Zhang, Mingzhe Zhang, Shoumeng Yan, Li Jiang, Haibing Guan
2025 J jnl
ALLMod: Exploring Area-Efficiency of LUT-based Large Number Modular Reduction via Hybrid Workloads.
CoRR
Fangxin Liu, Haomin Li, Zongwu Wang, Bo Zhang, Mingzhe Zhang, Shoumeng Yan, Li Jiang, Haibing Guan
2025 — conf
ASDR: Exploiting Adaptive Sampling and Data Reuse for CIM-based Instant Neural Rendering.
ASPLOS (3)
Fangxin Liu, Haomin Li, Bowen Zhu, Zongwu Wang, Zhuoran Song, Haibing Guan, Li Jiang
2025 J jnl
ASDR: Exploiting Adaptive Sampling and Data Reuse for CIM-based Instant Neural Rendering.
CoRR
Fangxin Liu, Haomin Li, Bowen Zhu, Zongwu Wang, Zhuoran Song, Habing Guan, Li Jiang
2025 A* conf
ASTER: Adaptive Dynamic Layer-Skipping for Efficient Transformer Inference via Markov Decision Process.
ACM Multimedia
Fangxin Liu, Junjie Wang, Ning Yang, Zongwu Wang, Junping Zhao, Li Jiang, Haibing Guan
2025 J jnl
Attack and Defense: Enhancing Robustness of Binary Hyper-Dimensional Computing.
ACM Trans. Archit. Code Optim.
Haomin Li, Fangxin Liu, Zongwu Wang, Ning Yang, Shiyuan Huang, Xiaoyao Liang, Haibing Guan, Li Jiang
2025 A* conf
BLOOM: Bit-Slice Framework for DNN Acceleration with Mixed-Precision.
DAC
Fangxin Liu, Ning Yang, Zongwu Wang, Xuanpeng Zhu, Haidong Yao, Xiankui Xiong, Li Jiang, Haibing Guan
2025 A* conf
CROSS: Compiler-Driven Optimization of Sparse DNNs Using Sparse/Dense Computation Kernels.
HPCA
Fangxin Liu, Shiyuan Huang, Ning Yang, Zongwu Wang, Haomin Li, Li Jiang
2025 A conf
EVASION: Efficient KV CAche CompreSsion vIa PrOduct QuaNtization.
DATE
Zongwu Wang, Fangxin Liu, Peng Xu, Qingxiao Sun, Junping Zhao, Li Jiang
2025 — conf
Exploiting Differential-Based Data Encoding for Enhanced Query Efficiency.
ASP-DAC
Fangxin Liu, Zongwu Wang, Peng Xu, Shiyuan Huang, Li Jiang
2025 A* conf
FATE: Boosting the Performance of Hyper-Dimensional Computing Intelligence with Flexible Numerical DAta TypE.
ISCA
Haomin Li, Fangxin Liu, Yichi Chen, Zongwu Wang, Shiyuan Huang, Ning Yang, Dongxu Lyu, Li Jiang
2025 — conf
FlexQuant: A Flexible and Efficient Dynamic Precision Switching Framework for LLM Quantization.
EMNLP (Findings)
Fangxin Liu, Zongwu Wang, JinHong Xia, Junping Zhao, Shouren Zhao, Jinjin Li, Jian Liu, Li Jiang, Haibing Guan
2025 J jnl
FlexQuant: A Flexible and Efficient Dynamic Precision Switching Framework for LLM Quantization.
CoRR
Fangxin Liu, Zongwu Wang, JinHong Xia, Junping Zhao, Jian Liu, Haibing Guan, Li Jiang
2025 A conf
HyperDyn: Dynamic Dimensional Masking for Efficient Hyper-Dimensional Computing.
DATE
Fangxin Liu, Haomin Li, Zongwu Wang, Dongxu Lyu, Li Jiang
2025 — conf
Irregular Sparsity-Enabled Search-in-Memory Engine for Accelerating Spiking Neural Networks.
APPT
Fangxin Liu, Zongwu Wang, Ning Yang, Haomin Li, Tao Yang, Haibing Guan, Li Jiang
2025 J jnl
LaMoS: Enabling Efficient Large Number Modular Multiplication through SRAM-based CiM Acceleration.
CoRR
Haomin Li, Fangxin Liu, Chenyang Guan, Zongwu Wang, Li Jiang, Haibing Guan
2025 A* conf
MILLION: MasterIng Long-Context LLM Inference Via Outlier-Immunized KV Product QuaNtization.
DAC
Zongwu Wang, Peng Xu, Fangxin Liu, Yiwei Hu, Qingxiao Sun, Gezi Li, Cheng Li, Xuan Wang, Li Jiang, Haibing Guan
2025 J jnl
MILLION: Mastering Long-Context LLM Inference Via Outlier-Immunized KV Product Quantization.
CoRR
Zongwu Wang, Peng Xu, Fangxin Liu, Yiwei Hu, Qingxiao Sun, Gezi Li, Cheng Li, Xuan Wang, Li Jiang, Haibing Guan
2025 — conf
NeuronQuant: Accurate and Efficient Post-Training Quantization for Spiking Neural Networks.
ASP-DAC
Haomin Li, Fangxin Liu, Zewen Sun, Zongwu Wang, Shiyuan Huang, Ning Yang, Li Jiang
2025 A conf
OPS: Outlier-Aware Precision-Slice Framework for LLM Acceleration.
DATE
Fangxin Liu, Ning Yang, Zongwu Wang, Xuanpeng Zhu, Haidong Yao, Xiankui Xiong, Qi Sun, Li Jiang
2025 A* conf
PISA: Efficient Precision-Slice Framework for LLMs with Adaptive Numerical Type.
DAC
Ning Yang, Zongwu Wang, Qingxiao Sun, Liqiang Lu, Fangxin Liu
2025 A conf
PLAIN: Leveraging High Internal Bandwidth in PIM for Accelerating Large Language Model Inference via Mixed-Precision Quantization.
ICCAD
Yiwei Hu, Fangxin Liu, Zongwu Wang, Yilong Zhao, Tao Yang, Li Jiang, Haibing Guan
2025 A conf
QUARK: Quantization-Enabled Circuit Sharing for Transformer Acceleration by Exploiting Common Patterns in Nonlinear Operations.
ICCAD
Zhixiong Zhao, Haomin Li, Fangxin Liu, Yuncheng Lu, Zongwu Wang, Tao Yang, Li Jiang, Haibing Guan
2025 J jnl
QUARK: Quantization-Enabled Circuit Sharing for Transformer Acceleration by Exploiting Common Patterns in Nonlinear Operations.
CoRR
Zhixiong Zhao, Haomin Li, Fangxin Liu, Yuncheng Lu, Zongwu Wang, Tao Yang, Li Jiang, Haibing Guan
2025 J jnl
STCO: Enhancing Training Efficiency via Structured Sparse Tensor Compilation Optimization.
ACM Trans. Design Autom. Electr. Syst.
Shiyuan Huang, Fangxin Liu, Tian Li, Zongwu Wang, Ning Yang, Haomin Li, Li Jiang
2025 J jnl
SpMMPlu-Pro: An Enhanced Compiler Plug-In for Efficient SpMM and Sparsity Propagation Algorithm.
IEEE Trans. Comput. Aided Des. Integr. Circuits Syst.
Shiyuan Huang, Fangxin Liu, Tao Yang, Zongwu Wang, Ning Yang, Li Jiang
2025 J jnl
SpecQuant: Spectral Decomposition and Adaptive Truncation for Ultra-Low-Bit LLMs Quantization.
CoRR
Zhixiong Zhao, Fangxin Liu, Junjie Wang, Chenyang Guan, Zongwu Wang, Li Jiang, Haibing Guan
2025 A conf
TAIL: Exploiting Temporal Asynchronous Execution for Efficient Spiking Neural Networks with Inter-Layer Parallelism.
DATE
Haomin Li, Fangxin Liu, Zongwu Wang, Dongxu Lyu, Shiyuan Huang, Ning Yang, Qi Sun, Zhuoran Song, Li Jiang
2024 A* conf
COMPASS: SRAM-Based Computing-in-Memory SNN Accelerator with Adaptive Spike Speculation.
MICRO
Zongwu Wang, Fangxin Liu, Ning Yang, Shiyuan Huang, Haomin Li, Li Jiang
2024 A* conf
EOS: An Energy-Oriented Attack Framework for Spiking Neural Networks.
DAC
Ning Yang, Fangxin Liu, Zongwu Wang, Haomin Li, Zhuoran Song, Songwen Pei, Li Jiang
2024 J jnl
ERA-BS: Boosting the Efficiency of ReRAM-Based PIM Accelerator With Fine-Grained Bit-Level Sparsity.
IEEE Trans. Computers
Fangxin Liu, Wenbo Zhao, Zongwu Wang, Yongbiao Chen, Xiaoyao Liang, Li Jiang
2024 J jnl
Exploiting Temporal-Unrolled Parallelism for Energy-Efficient SNN Acceleration.
IEEE Trans. Parallel Distributed Syst.
Fangxin Liu, Zongwu Wang, Wenbo Zhao, Ning Yang, Yongbiao Chen, Shiyuan Huang, Haomin Li, Tao Yang, Songwen Pei, Xiaoyao Liang, Li Jiang
2024 C conf
HOLES: Boosting Large Language Models Efficiency with Hardware-Friendly Lossless Encoding.
ICCD
Fangxin Liu, Ning Yang, Zhiyan Song, Zongwu Wang, Li Jiang
2024 A* conf
INSPIRE: Accelerating Deep Neural Networks via Hardware-friendly Index-Pair Encoding.
DAC
Fangxin Liu, Ning Yang, Zhiyan Song, Zongwu Wang, Haomin Li, Shiyuan Huang, Zhuoran Song, Songwen Pei, Li Jiang
2024 A conf
LowPASS: A Low power PIM-based accelerator with Speculative Scheme for SNNs.
ISLPED
Fangxin Liu, Shiyuan Huang, Longyu Zhao, Li Jiang, Zongwu Wang
2024 C conf
Ninja: A Hardware Assisted System for Accelerating Nested Address Translation.
ICCD
Longyu Zhao, Zongwu Wang, Fangxin Liu, Li Jiang
2024 B conf
PAAP-HD: PIM-Assisted Approximation for Efficient Hyper-Dimensional Computing.
ASPDAC
Fangxin Liu, Haomin Li, Ning Yang, Yichi Chen, Zongwu Wang, Tao Yang, Li Jiang
2024 C conf
PS4: A Low Power SNN Accelerator with Spike Speculative Scheme.
ICCD
Zongwu Wang, Fangxin Liu, Xin Tang, Li Jiang
2024 A* conf
SPARK: Scalable and Precision-Aware Acceleration of Neural Networks via Efficient Encoding.
HPCA
Fangxin Liu, Ning Yang, Haomin Li, Zongwu Wang, Zhuoran Song, Songwen Pei, Li Jiang
2024 J jnl
SearchQ: Search-Based Fine-Grained Quantization for Data-Free Model Compression.
IEEE Trans. Circuits Syst. Artif. Intell.
Ning Yang, Fangxin Liu, Zongwu Wang, Junping Zhao, Li Jiang
2024 C conf
T-BUS: Taming Bipartite Unstructured Sparsity for Energy-Efficient DNN Acceleration.
ICCD
Ning Yang, Fangxin Liu, Zongwu Wang, Zhiyan Song, Tao Yang, Li Jiang
2024 B conf
TEAS: Exploiting Spiking Activity for Temporal-wise Adaptive Spiking Neural Networks.
ASPDAC
Fangxin Liu, Haomin Li, Ning Yang, Zongwu Wang, Tao Yang, Li Jiang
2024 B conf
TSTC: Enabling Efficient Training via Structured Sparse Tensor Compilation.
ASPDAC
Shiyuan Huang, Fangxin Liu, Tian Li, Zongwu Wang, Haomin Li, Li Jiang
2024 J jnl
TokenRing: An Efficient Parallelism Framework for Infinite-Context LLMs via Bidirectional Communication.
CoRR
Zongwu Wang, Fangxin Liu, Mingshuai Li, Li Jiang
2024 A* conf
UM-PIM: DRAM-based PIM with Uniform & Shared Memory Space.
ISCA
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
2023 A conf
SIMSnn: A Weight-Agnostic ReRAM-based Search-In-Memory Engine for SNN Acceleration.
DATE
Fangxin Liu, Wenbo Zhao, Zongwu Wang, Xiaokang Yang, Li Jiang
2023 J jnl
SoBS-X: Squeeze-Out Bit Sparsity for ReRAM-Crossbar-Based Neural Network Accelerator.
IEEE Trans. Comput. Aided Des. Integr. Circuits Syst.
Fangxin Liu, Zongwu Wang, Yongbiao Chen, Zhezhi He, Tao Yang, Xiaoyao Liang, Li Jiang
2022 — conf
Cross-layer Designs against Non-ideal Effects in ReRAM-based Processing-in-Memory System.
ISQED
Chen Nie, Zongwu Wang, Qidong Tang, Chenyang Lv, Li Jiang, Zhezhi He
2022 A conf
DTQAtten: Leveraging Dynamic Token-based Quantization for Efficient Attention Architecture.
DATE
Tao Yang, Dongyue Li, Zhuoran Song, Yilong Zhao, Fangxin Liu, Zongwu Wang, Zhezhi He, Li Jiang
2022 Misc conf
DynSNN: A Dynamic Approach to Reduce Redundancy in Spiking Neural Networks.
ICASSP
Fangxin Liu, Wenbo Zhao, Yongbiao Chen, Zongwu Wang, Fei Dai
2022 A* conf
EBSP: evolving bit sparsity patterns for hardware-friendly inference of quantized deep neural networks.
DAC
Fangxin Liu, Wenbo Zhao, Zongwu Wang, Yongbiao Chen, Zhezhi He, Naifeng Jing, Xiaoyao Liang, Li Jiang
2022 — conf
HAWIS: Hardware-Aware Automated WIdth Search for Accurate, Energy-Efficient and Robust Binary Neural Network on ReRAM Dot-Product Engine.
ASP-DAC
Qidong Tang, Zhezhi He, Fangxin Liu, Zongwu Wang, Yiyuan Zhou, Yinghuan Zhang, Li Jiang
2022 J jnl
IVQ: In-Memory Acceleration of DNN Inference Exploiting Varied Quantization.
IEEE Trans. Comput. Aided Des. Integr. Circuits Syst.
Fangxin Liu, Wenbo Zhao, Zongwu Wang, Yilong Zhao, Tao Yang, Yiran Chen, Li Jiang
2022 A* conf
PIM-DH: ReRAM-based processing-in-memory architecture for deep hashing acceleration.
DAC
Fangxin Liu, Wenbo Zhao, Yongbiao Chen, Zongwu Wang, Zhezhi He, Rui Yang, Qidong Tang, Tao Yang, Cheng Zhuo, Li Jiang
2022 C conf
Randomize and Match: Exploiting Irregular Sparsity for Energy Efficient Processing in SNNs.
ICCD
Fangxin Liu, Zongwu Wang, Wenbo Zhao, Yongbiao Chen, Tao Yang, Xiaokang Yang, Li Jiang
2022 A* conf
SATO: spiking neural network acceleration via temporal-oriented dataflow and architecture.
DAC
Fangxin Liu, Wenbo Zhao, Zongwu Wang, Yongbiao Chen, Tao Yang, Zhezhi He, Xiaokang Yang, Li Jiang
2022 A conf
Self-Terminating Write of Multi-Level Cell ReRAM for Efficient Neuromorphic Computing.
DATE
Zongwu Wang, Zhezhi He, Rui Yang, Shiquan Fan, Jie Lin, Fangxin Liu, Yueyang Jia, Chenxi Yuan, Qidong Tang, Li Jiang
2022 A* conf
SpikeConverter: An Efficient Conversion Framework Zipping the Gap between Artificial Neural Networks and Spiking Neural Networks.
AAAI
Fangxin Liu, Wenbo Zhao, Yongbiao Chen, Zongwu Wang, Li Jiang
2021 A conf
Bit-Transformer: Transforming Bit-level Sparsity into Higher Preformance in ReRAM-based Accelerator.
ICCAD
Fangxin Liu, Wenbo Zhao, Zhezhi He, Zongwu Wang, Yilong Zhao, Yongbiao Chen, Li Jiang
2021 — conf
IM3A: Boosting Deep Neural Network Efficiency via In-Memory Addressing-Assisted Acceleration.
ACM Great Lakes Symposium on VLSI
Fangxin Liu, Wenbo Zhao, Zongwu Wang, Tao Yang, Li Jiang
2021 A* conf
Improving Neural Network Efficiency via Post-training Quantization with Adaptive Floating-Point.
ICCV
Fangxin Liu, Wenbo Zhao, Zhezhi He, Yanzhi Wang, Zongwu Wang, Changzhi Dai, Xiaoyao Liang, Li Jiang
2021 C conf
SME: ReRAM-based Sparse-Multiplication-Engine to Squeeze-Out Bit Sparsity of Neural Network.
ICCD
Fangxin Liu, Wenbo Zhao, Zhezhi He, Zongwu Wang, Yilong Zhao, Tao Yang, Jingnai Feng, Xiaoyao Liang, Li Jiang
2021 J jnl
SME: ReRAM-based Sparse-Multiplication-Engine to Squeeze-Out Bit Sparsity of Neural Network.
CoRR
Fangxin Liu, Wenbo Zhao, Yilong Zhao, Zongwu Wang, Tao Yang, Zhezhi He, Naifeng Jing, Xiaoyao Liang, Li Jiang