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Strategies and Principles of Distributed Machine Learning on Big Data Review
Eric P. Xing,Qirong Ho,Pengtao Xie,Dai Wei
Engineering 2016, Volume 2, Issue 2, Pages 179-195 doi: 10.1016/J.ENG.2016.02.008
The rise of big data has led to new demands for machine learning (ML) systems to learn complex models, with millions to billions of parameters, that promise adequate capacity to digest massive datasets and offer powerful predictive analytics (such as high-dimensional latent features, intermediate representations, and decision functions) thereupon. In order to run ML algorithms at such scales, on a distributed cluster with tens to thousands of machines, it is often the case that significant engineering efforts are required—and one might fairly ask whether such engineering truly falls within the domain of ML research. Taking the view that “big” ML systems can benefit greatly from ML-rooted statistical and algorithmic insights—and that ML researchers should therefore not shy away from such systems design—we discuss a series of principles and strategies distilled from our recent efforts on industrial-scale ML solutions. These principles and strategies span a continuum from application, to engineering, and to theoretical research and development of big ML systems and architectures, with the goal of understanding how to make them efficient, generally applicable, and supported with convergence and scaling guarantees. They concern four key questions that traditionally receive little attention in ML research: How can an ML program be distributed over a cluster? How can ML computation be bridged with inter-machine communication? How can such communication be performed? What should be communicated between machines? By exposing underlying statistical and algorithmic characteristics unique to ML programs but not typically seen in traditional computer programs, and by dissecting successful cases to reveal how we have harnessed these principles to design and develop both high-performance distributed ML software as well as general-purpose ML frameworks, we present opportunities for ML researchers and practitioners to further shape and enlarge the area that lies between ML and systems.
Keywords: Machine learning Artificial intelligence big data Big model Distributed systems Principles Theory Data-parallelism Model-parallelism
Avision of post-exascale programming None
Ji-dong ZHAI, Wen-guang CHEN
Frontiers of Information Technology & Electronic Engineering 2018, Volume 19, Issue 10, Pages 1261-1266 doi: 10.1631/FITEE.1800442
Keywords: Computing model Fault-tolerance Heterogeneous Parallelism Post-exascale
A survey on design and application of open-channel solid-state drives Review Article
Junchao CHEN, Guangyan ZHANG, Junyu WEI,gyzh@tsinghua.edu.cn
Frontiers of Information Technology & Electronic Engineering 2023, Volume 24, Issue 5, Pages 637-658 doi: 10.1631/FITEE.2200317
Keywords: Domain-specific storage Flash translation layer Garbage collection Internal parallelism Open-channel
Standard model of knowledge representation
Wensheng YIN
Frontiers of Mechanical Engineering 2016, Volume 11, Issue 3, Pages 275-288 doi: 10.1007/s11465-016-0372-3
Keywords: knowledge representation standard model ontology system theory control theory multidimensional representation
Zhang Zhengyan: Pre Training Language Model Integrating Knowledge (2020-4-3)
18 Apr 2022
Keywords: 工程管理
State of the Art of Compartment Fire Modeling
Zheng Xin,Yuan Hongyong
Strategic Study of CAE 2004, Volume 6, Issue 3, Pages 68-74
Keywords: compartment field model zone model network model FZN (field zone and network) model empirical model
Elevated temperature creep model of parallel wire strands
Frontiers of Structural and Civil Engineering Pages 1060-1071 doi: 10.1007/s11709-023-0981-y
Keywords: parallel wire strands experimental study elevated temperature creep model
Impact of crude distillation unit model accuracy on refinery production planning
Gang FU, Pedro A. Castillo CASTILLO, Vladimir MAHALEC
Frontiers of Engineering Management 2018, Volume 5, Issue 2, Pages 195-201 doi: 10.15302/J-FEM-2017052
Keywords: impact of model accuracy on production planning swing cut+ bias CDU model hybrid CDU model refinery feedstock
Test-driven verification/validation of model transformations
László LENGYEL,Hassan CHARAF
Frontiers of Information Technology & Electronic Engineering 2015, Volume 16, Issue 2, Pages 85-97 doi: 10.1631/FITEE.1400111
Keywords: Graph rewriting based model transformations Verification/validation Test-driven verification
Digital twin-assisted gearbox dynamic model updating toward fault diagnosis
Frontiers of Mechanical Engineering 2023, Volume 18, Issue 2, doi: 10.1007/s11465-023-0748-0
Keywords: digital twin gearbox model construction model updating physical–virtual interaction
Nitin Kumar SAXENA,Ashwani Kumar SHARMA
Frontiers in Energy 2015, Volume 9, Issue 4, Pages 472-485 doi: 10.1007/s11708-015-0373-7
Keywords: isolated hybrid power system (IHPS) composite load model static load dynamic load induction motor loadmodel aggregate load
Initiation of Setaria as a model plant
Xianmin DIAO,James SCHNABLE,Jeffrey L. BENNETZEN,Jiayang LI
Frontiers of Agricultural Science and Engineering 2014, Volume 1, Issue 1, Pages 16-20 doi: 10.15302/J-FASE-2014011
Keywords: Setaria foxtail millet C4 photosynthesis model organism
A time−space porosity computational model for concrete under sulfate attack
Frontiers of Structural and Civil Engineering doi: 10.1007/s11709-023-0985-7
Keywords: deformation porosity internal expansion stress external sulfate attack mechanical–chemical coupling model
The Construction of Tetrahedral Model of Engineering Ethical Evaluation
Jin Wang
Frontiers of Engineering Management 2014, Volume 1, Issue 1, Pages 62-70 doi: 10.15302/J-FEM-2014009
Keywords: tetrahedral model ethical evaluation engineering Lamps and Mirrors
Four-protein model for predicting prognostic risk of lung cancer
Frontiers of Medicine 2022, Volume 16, Issue 4, Pages 618-626 doi: 10.1007/s11684-021-0867-0
Keywords: lung cancer HSP90β decision tree model prognosis
Title Author Date Type Operation
Strategies and Principles of Distributed Machine Learning on Big Data
Eric P. Xing,Qirong Ho,Pengtao Xie,Dai Wei
Journal Article
A survey on design and application of open-channel solid-state drives
Junchao CHEN, Guangyan ZHANG, Junyu WEI,gyzh@tsinghua.edu.cn
Journal Article
Zhang Zhengyan: Pre Training Language Model Integrating Knowledge (2020-4-3)
18 Apr 2022
Conference Videos
Impact of crude distillation unit model accuracy on refinery production planning
Gang FU, Pedro A. Castillo CASTILLO, Vladimir MAHALEC
Journal Article
Test-driven verification/validation of model transformations
László LENGYEL,Hassan CHARAF
Journal Article
Estimation of composite load model with aggregate induction motor dynamic load for an isolated hybrid
Nitin Kumar SAXENA,Ashwani Kumar SHARMA
Journal Article
Initiation of Setaria as a model plant
Xianmin DIAO,James SCHNABLE,Jeffrey L. BENNETZEN,Jiayang LI
Journal Article