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Redundancy-free and load-balanced TGNN training with hierarchical pipeline parallelism Journal article
Xia, Yaqi, Zhang, Zheng, Yang, Donglin, Hu, Chuang, Zhou, Xiaobo, Chen, Hongyang, Sang, Qianlong, Cheng, Dazhao. Redundancy-free and load-balanced TGNN training with hierarchical pipeline parallelism[J]. IEEE Transactions on Parallel and Distributed Systems, 2024, 35(11), 1904-1919.
Authors:  Xia, Yaqi;  Zhang, Zheng;  Yang, Donglin;  Hu, Chuang;  Zhou, Xiaobo; et al.
Favorite | TC[WOS]:0 TC[Scopus]:1  IF:5.6/4.5 | Submit date：2024/08/05
Communication Balance  Distributed Training  Dynamic Gnn  Pipeline Parallelism  Redundancy-free  
QUART: Latency-Aware FaaS System for Pipelining Large Model Inference Conference paper
Lin, Yanying, Li, Yanbo, Peng, Shijie, Tang, Yingfei, Luo, Shutian, Shen, Haiying, Xu, Chengzhong, Ye, Kejiang. QUART: Latency-Aware FaaS System for Pipelining Large Model Inference[C]:Institute of Electrical and Electronics Engineers Inc., 2024.
Authors:  Lin, Yanying;  Li, Yanbo;  Peng, Shijie;  Tang, Yingfei;  Luo, Shutian; et al.
Favorite | TC[WOS]:0 TC[Scopus]:0 | Submit date：2024/10/10
Processor Scheduling  Computational Modeling  Tail  Position Measurement  Resource Management  Low Latency Communication  Distributed Computing  Pipeline Inference  Large Model  Serverless  Latency Aware  
Frustum: Achieving High Throughput in Blockchain Systems Through Hierarchical and Pipelined Sharding Journal article
Yukun Xu, Wenhan Wu, Yili Gong, WANG YE. Frustum: Achieving High Throughput in Blockchain Systems Through Hierarchical and Pipelined Sharding[J]. Blockchain, 2024, 2(1).
Authors:  Yukun Xu;  Wenhan Wu;  Yili Gong;  WANG YE
Favorite |  | Submit date：2025/01/17
Blockchain Sharding  Complete Pipeline  Frustum  
MPMoE: Memory Efficient MoE for Pre-Trained Models With Adaptive Pipeline Parallelism Journal article
Zhang, Zheng, Xia, Yaqi, Wang, Hulin, Yang, Donglin, Hu, Chuang, Zhou, Xiaobo, Cheng, Dazhao. MPMoE: Memory Efficient MoE for Pre-Trained Models With Adaptive Pipeline Parallelism[J]. IEEE Transactions on Parallel and Distributed Systems, 2024, 35(6), 843-856.
Authors:  Zhang, Zheng;  Xia, Yaqi;  Wang, Hulin;  Yang, Donglin;  Hu, Chuang; et al.
Favorite | TC[WOS]:0 TC[Scopus]:4  IF:5.6/4.5 | Submit date：2024/05/16
Distributed Training  Memory Redundancy  Mixture Of Experts  Performance Model  Pipeline Parallelism  
A 160-MHz BW 68-dB SNDR 36.2 mW Continuous-Time Pipelined ΔΣ ADC With DAC Image Prefiltering Journal article
Li, Ke, Gong, Haoyu, Xianyu, Congzhou, Li, Zhensheng, Qi, Liang, Guo, Mingqiang, Martins, Rui P., Sin, Sai Weng. A 160-MHz BW 68-dB SNDR 36.2 mW Continuous-Time Pipelined ΔΣ ADC With DAC Image Prefiltering[J]. IEEE Journal of Solid-State Circuits, 2024.
Authors:  ; et al.
Favorite | TC[WOS]:0 TC[Scopus]:0  IF:4.6/5.6 | Submit date：2025/01/13
Analog-to-digital Converter (Adc)  Cascade Of Integrators With Feedforward (Ciff)  Continuous Time (Ct)  Ct Pipeline (Ctp)  Excess Loop Delay (Eld)  Low-pass Filter (Lpf)  Multistage Noise-shaping (Mash)  Offset Calibration  Signal Transfer Function (Stf) Peaking  
Planck: Optimizing LLM Inference Performance in Pipeline Parallelism with Fine-Grained SLO Constraint Conference paper
Lin, Yanying, Peng, Shijie, Wu, Shuaipeng, Li, Yanbo, Lu, Chengzhi, Xu, Chengzhong, Ye, Kejiang. Planck: Optimizing LLM Inference Performance in Pipeline Parallelism with Fine-Grained SLO Constraint[C]:Institute of Electrical and Electronics Engineers Inc., 2024, 1306-1313.
Authors:  ; et al.
Favorite | TC[WOS]:0 TC[Scopus]:1 | Submit date：2024/12/05
Llm Serving  Pipeline Bubble  Pipeline Parallelism  Slo Constraint  
On Security-Constrained Bidding of Shared Transportation Hubs for Renewable Fuels and Refined Oil Participating Within Energy, Regulation and Pipeline Logistics Markets Conference paper
Wang, Shengshi, Li, Hongyi, Huang, Danji, Li, Kun, Cui, Shichang, Ai, Xiaomeng, Fang, Jiakun, Wen, Jinyu. On Security-Constrained Bidding of Shared Transportation Hubs for Renewable Fuels and Refined Oil Participating Within Energy, Regulation and Pipeline Logistics Markets[C]:Institute of Electrical and Electronics Engineers, 2024, 204483.
Authors:  Wang, Shengshi;  Li, Hongyi;  Huang, Danji;  Li, Kun;  Cui, Shichang; et al.
Favorite | TC[Scopus]:0 | Submit date：2024/12/26
Frequency Regulation  Multi-product Pipeline Logistics  Renewable Energy  Security-constrained  Shared Transportation Hubs For Renewable Fuels And Refined Oil  
Planck: Optimizing LLM Inference Performance in Pipeline Parallelism with Fine-Grained SLO Constraint Journal article
Lin, Yanying, Peng, Shijie, Wu, Shuaipeng, Li, Yanbo, Lu, Chengzhi, Xu, Chengzhong, Ye, Kejiang. Planck: Optimizing LLM Inference Performance in Pipeline Parallelism with Fine-Grained SLO Constraint[J]. Proceedings of the IEEE International Conference on Web Services, ICWS, 2024, 1306-1313.
Authors:  Lin, Yanying;  Peng, Shijie;  Wu, Shuaipeng;  Li, Yanbo;  Lu, Chengzhi; et al.
Favorite | TC[WOS]:0 TC[Scopus]:1 | Submit date：2024/12/26
LLM Serving  Pipeline Bubble  Pipeline Parallelism  SLO Constraint  
MPipeMoE: Memory Efficient MoE for Pre-trained Models with Adaptive Pipeline Parallelism Conference paper
Zhang, Zheng, Yang, Donglin, Xia, Yaqi, Ding, Liang, Tao, Dacheng, Zhou, Xiaobo, Cheng, Dazhao. MPipeMoE: Memory Efficient MoE for Pre-trained Models with Adaptive Pipeline Parallelism[C], USA:Institute of Electrical and Electronics Engineers Inc., 2023, 167-177.
Authors:  Zhang, Zheng;  Yang, Donglin;  Xia, Yaqi;  Ding, Liang;  Tao, Dacheng; et al.
Favorite | TC[WOS]:2 TC[Scopus]:6 | Submit date：2023/08/08
Mixture Of Experts  Pipeline Parallelism  Distributed Training  Memory Efficiency  
Low-Power Nyquist ADCs Book chapter
出自: Analog Circuits and Signal Processing, Switzerland:Springer, 2023, 页码:131-180
Authors:  Minglei Zhang;  Chi-Hang Chan;  Yan Zhu;  Rui P. Martins
Favorite | TC[Scopus]:1 | Submit date：2023/08/03
Analog-to-digital Converter (Adc)  Calibration  Low Supply Voltage  Pipeline  Successive Approximation Register (Sar)  Time-domain Converter (Tdc)