About me

Hi, I am currently an assistant profosser at Beijing Normal University, working on high performance computing and efficient machine learning system. Prior to this, I earned my Ph.D. from the Guangzhou Supercomputing Center at Sun Yat-sen University, July 2024. I also have industry experience working as an R&D Engineer and Senior R&D Engineer at companies such as Baidu and NetEase Games. You can find with my email address: jiangjz@bnu.edu.cn .

🏫 Education

• Ph.D in Guangzhou National SuperComputer Center,Sun Yat-sen University
  Advised by Profossor Xiangke Liao, Yutong Lu.
• Visiting Scholar, Xtra Lab, National University of Singapore.
  Advised by Bingsheng He.
• M.Sc. Mayor in High Performance Computing, South China University of Technology.
  Advised by Hu Chen.
• B.Sc. Mayor in Software Engineering, South China University of Technology.

💻 Research Interest

My research interest focuses on ML System and HPC, including:

• Software-Hardware Co-Design for ML Operator.
• Efficient ML Inference/Training Systems.
• Task Scheduling for HPC-AI System.
• Resource Mananagement on Cloud/HPC Platfrom.

🔥 News

• [28/2/25] One Paper Accepted For SIGMOD 2025
• [15/12/24] One Paper Accepted For TPDS
• [01/11/24] Start working as an assistant professor at Beijing Normal University

🏆 Awards

• Chinese National Scholarship in Sun Yat-sen University
• Chinese National Scholarship in South China University of Technology

💻 Selected Publications

(#equal contribution, *corresponding author)

Journal Publications

• [TPDS 2025] Jiangsu Du, Yuanxin Wei, Shengyuan Ye, Jiazhi Jiang, Dan Huang, Xu Chen, Yutong Lu “Co-designing Transformer Architectures for Distributed Inference with Low Communication”
• [TPDS 2024] Rui Tian#, Jiazhi Jiang#, Jiangsu Du, Dan Huang, Yutong Lu “Sophisticated Orchestrating Concurrent DLRM Training on CPU/GPU Platform”
• [TPDS 2023] Jiazhi Jiang, Jiangsu Du, Dan Huang, Zhiguang Chen, Yutong Lu, Xiangke Liao, “Full Stack Optimizing Transformer Inference on ARM Many-core CPU”
• [TACO 2023] Jiazhi Jiang, Zijian Huang, Dan Huang, Jiangsu Du, Lin Chen, Zhiguang Chen, Yutong Lu,”Hierarchical Model Parallelism for Optimizing Inference on Many-core Processor Via Decoupled 3D-CNN Structure”
• [TACO 2023] Jiangsu Du, Jiazhi Jiang, Jiang Zheng, Hongbin Zhang, Dan Huang, Yutong Lu “Improving Computation and Memory Efficiency for Real world Transformer Inference on GPUs”
• [PARCO 2023] Jiang Zheng#, Jiazhi Jiang#, Jiangsu Du, Dan Huang, Yutong Lu “Optimizing Massively Parallel Sparse Matrix Computing on ARM Many-core Processor”
• [SCIS 2023] Jiazhi Jiang, Dan Huang, Hu Chen, Yutong Lu, Xiangke Liao, “HTDcr: A Job Execution Framework for High Throughput Computing on Supercomputers”
• [JCST 2023] Jiangsu Du, Dongsheng Li, Yingpeng Wen, Jiazhi Jiang, Dan Huang, Xiangke Liao, and Yutong Lu,”SAIH: A Scalable Evaluation Methodology for Understanding AI Performance Trend on HPC Systems”
• [PARCO 2022] Jiazhi Jiang, Dan Huang, Jiangsu Du, Yutong Lu, Xiangke Liao, “Optimizing small channel 3D convolution on GPU with tensor core”

Conference Publications

• [EuroPar 2024] Jiazhi Jiang#, Hongbin Zhang#, Deyin Liu, Jiangsu Du, Jinhui Wei, Dan Huang, Yutong Lu “RTAI:Efficient Coupling Hybrid Workflow of Streaming AI and Ensemble Simulations on HPC Clusters”
• [PPoPP 2024] Jiangsu Du, Jinhui Wei, Jiazhi Jiang, Shenggan Cheng, Dan Huang, Zhiguang Chen, Yulong Lu, “Liger: Interleaving Intra- and Inter-Operator Parallelism for Distributed Large Model Inference”
• [SC 2024] Yuanxin Wei, Jiangsu Du, Jiazhi Jiang, Xiao Shi, Xianwei Zhang, Dan Huang, Nong Xiao, Yutong Lu. APTMoE: Affinity-aware Pipeline Tuning for MoE Models on Bandwidth-constrained GPU Nodes.
• [DATE 2024] Yuanxin Wei, Shengyuan Ye, Jiazhi Jiang, Xu Chen, Dan Huang, Jiangsu Du, Yutong Lu. Communication-Efficient Model Parallelism for Distributed In-situ Transformer Inference.
• [ICCD 2023] Jiazhi Jiang, Rui Tian, Jiangsu Du, Dan Huang, Yutong Lu “MixRec: Orchestrating Concurrent Recommendation Model Training on CPU-GPU platform”
• [DATE 2023] Jiazhi Jiang, Zijian Huang, Dan Huang, Jiangsu Du, Yutong Lu, “Accelerating Inference of 3D-CNN on ARM Many-core CPU via Hierarchical Model Partition”
• [ICPP 2022] Jiazhi Jiang, Jiangsu Du, Dan Huang, Dongsheng Li, Jiang Zheng, Yutong Lu, “Characterizing and Optimizing Transformer Inference on ARM Many-core Processor”
• [ICS 2022] Jiangsu Du, Jiazhi Jiang, Yang You, Dan Huang, Yutong Lu, “Handling Heavy-tailed Input of Transformer Inference on GPUs”