Runhua Zhang

According to our database, Runhua Zhang authored at least 13 papers between 2019 and 2026.

Collaborative distances:

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

2026

LSAF: A load-balancing SpGEMM acceleration framework with dynamic package and static partition for multi-core systolic arrays.

Yongxiang Cao, Hongxu Jiang, Guocheng Zhao, Dongcheng Shi, Runhua Zhang, Wei Wang

Parallel Comput., 2026

2025

FlexPie: Accelerate Distributed Inference on Edge Devices with Flexible Combinatorial Optimization[Technical Report].

Runhua Zhang, Hongxu Jiang, Jinkun Geng, Yuhang Ma, Chenhui Zhu, Haojie Wang

CoRR, February, 2025

JOVS: Joint Optimization of Vectorization and Scheduling for DNN on AI DSPs.

Yaochen Han, Hongxu Jiang, Runhua Zhang, Rui She

Proceedings of the 37th ACM Symposium on Parallelism in Algorithms and Architectures, 2025

SAM-Lightning: Segment Anything Model for Efficient Inference and Reduced Memory Footprint.

Yanfei Song, Hongxu Jiang, Bangzheng Pu, Peng Wang, Dong Dong, Yongxiang Cao, Runhua Zhang, Yiqing Shen

Proceedings of the PRICAI 2025: Trends in Artificial Intelligence, 2025

SparDR: Accelerating Unstructured Sparse DNN Inference via Dataflow Optimization.

Wei Wang, Hongxu Jiang, Runhua Zhang, Yongxiang Cao, Yaochen Han

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

2024

A high-performance dataflow-centric optimization framework for deep learning inference on the edge.

Runhua Zhang, Hongxu Jiang, Jinkun Geng, Fangzheng Tian, Yuhang Ma, Haojie Wang

J. Syst. Archit., 2024

2023

LOCP: Latency-optimized channel pruning for CNN inference acceleration on GPUs.

Yonghua Zhang, Hongxu Jiang, Yuting Zhu, Runhua Zhang, Yongxiang Cao, Chenhui Zhu, Wei Wang, Dong Dong, Xiaobin Li

J. Supercomput., September, 2023

Xenos : Dataflow-Centric Optimization to Accelerate Model Inference on Edge Devices.

Runhua Zhang, Hongxu Jiang, Fangzheng Tian, Jinkun Geng, Xiaobin Li, Yuhang Ma, Chenhui Zhu, Dong Dong, Xin Li, Haojie Wang

Proceedings of the Database Systems for Advanced Applications, 2023

2022

CNNBooster: Accelerating CNN Inference with Latency-aware Channel Pruning for GPU.

Yuting Zhu, Hongxu Jiang, Runhua Zhang, Yonghua Zhang, Dong Dong

Proceedings of the IEEE Intl Conf on Parallel & Distributed Processing with Applications, 2022

2021

Robustness-aware 2-bit quantization with real-time performance for neural network.

Xiaobin Li, Hongxu Jiang, Runhua Zhang, Fangzheng Tian, Shuangxi Huang, Donghuan Xu

Neurocomputing, 2021

SRQ: Self-Reference quantization scheme for lightweight neural network.

Xiaobin Li, Hongxu Jiang, Shuangxi Huang, Fangzheng Tian, Runhua Zhang, Dong Dong

Proceedings of the 31st Data Compression Conference, 2021

2020

DSANA: A distributed machine learning acceleration solution based on dynamic scheduling and network acceleration.

Runhua Zhang, Guowei Shen, Liangyi Gong, Chun Guo

Proceedings of the 22nd IEEE International Conference on High Performance Computing and Communications; 18th IEEE International Conference on Smart City; 6th IEEE International Conference on Data Science and Systems, 2020

2019

HiPower: A High-Performance RDMA Acceleration Solution for Distributed Transaction Processing.

Runhua Zhang, Yang Cheng, Jinkun Geng, Shuai Wang, Kaihui Gao, Guowei Shen

Proceedings of the Network and Parallel Computing, 2019