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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]:
0
IF:
5.6
/
4.5
|
Submit date:2024/08/05
Communication Balance
Distributed Training
Dynamic Gnn
Pipeline Parallelism
Redundancy-free
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]:
1
IF:
5.6
/
4.5
|
Submit date:2024/05/16
Distributed Training
Memory Redundancy
Mixture Of Experts
Performance Model
Pipeline Parallelism
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, 1-12.
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
Large Model
Latency Aware
Pipeline Inference
Serverless
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]:
1
TC[Scopus]:
1
|
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)
High-Performance Oversampling ADCs
Book chapter
出自: Analog Circuits and Signal Processing, Switzerland:Springer, 2023, 页码:181-218
Authors:
Chi-Hang Chan
;
Yan Zhu
;
Liang Qi
;
Sai Weng Sin
;
Maurits Ortmanns
; et al.
Favorite
|
TC[Scopus]:
0
|
Submit date:2023/08/03
Analog-to-digital Converter (Adc)
Cmos
Continuous-time Dsm (Ct Dsm)
Delta-sigma Modulator (Dsm)
Noise Shaping (Ns)
Oversampling
Pipeline Sar Adc
Successive Approximation Register (Sar)
A 266-µW Bluetooth Low-Energy (BLE) Receiver Featuring an N-Path Passive Balun-LNA and a Pipeline Down-Mixing BB-Extraction Scheme Achieving 77dB SFDR and -3dBm OOB-B-1dB
Journal article
Shao, Haijun, Mak, Pui-In, Qi, Gengzhen, Martins, Rui P.. A 266-µW Bluetooth Low-Energy (BLE) Receiver Featuring an N-Path Passive Balun-LNA and a Pipeline Down-Mixing BB-Extraction Scheme Achieving 77dB SFDR and -3dBm OOB-B-1dB[J]. IEEE Journal of Solid-State Circuits, 2022, 57(12), 3669–3680.
Authors:
Shao, Haijun
;
Mak, Pui-In
;
Qi, Gengzhen
;
Martins, Rui P.
Adobe PDF
|
Favorite
|
TC[WOS]:
8
TC[Scopus]:
11
IF:
4.6
/
5.6
|
Submit date:2023/05/15
Balun-low-noise Amplifier (Balun-lna)
Bandpass Filtering
Baseband (Bb)
Bluetooth Low-energy (Ble)
Cmos
Hybrid Filter
Noise Figure (Nf)
Nonlinearity
N-path
Out-of-band (Oob)
Passive Gain
Pipeline
Spurious-free Dynamic Range (Sfdr)
Ultra-low-power (Ulp)
A 20 MHz Bandwidth 79 dB SNDR SAR-Assisted Noise-Shaping Pipeline ADC with Gain and Offset Calibrations
Journal article
Zhang, Yanbo, Zhang, Jin, Liu, Shubin, Ding, Ruixue, Zhu, Yan, Chan, Chi Hang, Martins, Rui P.. A 20 MHz Bandwidth 79 dB SNDR SAR-Assisted Noise-Shaping Pipeline ADC with Gain and Offset Calibrations[J]. IEEE Journal of Solid-State Circuits, 2022, 57(3), 745-756.
Authors:
Zhang, Yanbo
;
Zhang, Jin
;
Liu, Shubin
;
Ding, Ruixue
;
Zhu, Yan
; et al.
Favorite
|
TC[WOS]:
7
TC[Scopus]:
10
IF:
4.6
/
5.6
|
Submit date:2022/03/28
Analog-to-digital Converter (Adc)
Inter-stage Gain And Offset Calibrations
Noise-shaping (Ns)
Split Adc
Successive Approximation Register (Sar)-assisted Pipeline
A 40-MHz Bandwidth 75-dB SNDR Partial-Interleaving SAR-Assisted Noise-Shaping Pipeline ADC
Journal article
Song,Yan, Zhu,Yan, Chan,Chi Hang, Martins,Rui P.. A 40-MHz Bandwidth 75-dB SNDR Partial-Interleaving SAR-Assisted Noise-Shaping Pipeline ADC[J]. IEEE Journal of Solid-State Circuits, 2021, 56(6), 1772-1783.
Authors:
Song,Yan
;
Zhu,Yan
;
Chan,Chi Hang
;
Martins,Rui P.
Favorite
|
TC[WOS]:
14
TC[Scopus]:
17
IF:
4.6
/
5.6
|
Submit date:2021/03/09
Analog-to-digital Converter (Adc)
Noise-shaping (Ns)
Offset Calibration
Successive Approximation Register (Sar)-assisted Pipeline
Time Interleaving
A 3.3-GS/s 6-b Fully Dynamic Pipelined ADC With Linearized Dynamic Amplifier
Journal article
Zihao Zheng, Lai Wei, Jorge Lagos, Ewout Martens, Yan Zhu, Chi Hang Chan, Jan Craninckx, Rui P. Martins. A 3.3-GS/s 6-b Fully Dynamic Pipelined ADC With Linearized Dynamic Amplifier[J]. IEEE Journal of Solid-State Circuits, 2021.
Authors:
Zihao Zheng
;
Lai Wei
;
Jorge Lagos
;
Ewout Martens
;
Yan Zhu
; et al.
Favorite
|
TC[WOS]:
8
TC[Scopus]:
9
IF:
4.6
/
5.6
|
Submit date:2021/09/20
Analog-to-digital Conversion
Calibration
Calibration
Dynamic Amplifier (Da)
Hardware
Linearity
Linearization Technique
Pipeline Processing
Pipelined Analog-to-digital Converter (Adc).
Quantization (Signal)
Signal Resolution
System-on-chip