ISC18-poster-ABCI application JH r3 - 産業技術総合研究所 · 2019-12-27 · Title:...
Transcript of ISC18-poster-ABCI application JH r3 - 産業技術総合研究所 · 2019-12-27 · Title:...
Gather a variety of data sets using monitoring technologies
Apply optimization, simulation and deep learning techniques to the real world data
Collaborative research
CPS(Cyber Physical System) and Creating New Industrial Applications on ABCI
Information: https://unit.aist.go.jp/rwbc-oil/index-en.htmlContact: [email protected]
CPS(Cyber Physical System) and Mobility Optimization Engine
歩道
倉庫
EV
オフィスビル
高速道路
監視カメラ
入退館ゲートESC
商業複合ビル
空港
産地
農業
橋堤防
航空管制
住宅マンション
SA/PA
ゴミ処理場コンビニ 商店街
駅
農業用水路
病院
車道
市街地道路
河川
浄水場
トンネル
医療
Energy Consumption
FCV/EV
Traffic Movement
People Movement
GPS, GIS, Facility Information
Administrative Information,
Social InformationMedical & Finance
Wearable DevicePersonal Device
Digital Signage
Smart Phone, Navigation
Social System, ITS, EMS
Real World Real World
Modeling Real World Feedback/Control Real World
Cyber Space
Optimization / Simulation
Cyber-physical System and Industrial Applications of Mobility Optimization Engine
サブ 分け
サブ1
回路A
回路B
回路C
回路Aと 回路Bの関係性
回路Bと 回路Cの関係性
絶対条件( 共圧着) に該当する 枝 (赤) にはより 高い重みを 与える
グラ フ分割の結果は点の色で表現
(3) サブ分けの評価
(1) 枝生成ルールの決定
(2) グラフ 分割
Next Generation AI Optimizing the materials flow in the distribution center
Virtual Factory on CyberspaceOptimizing production planning and schedule &decreasing manufacturing costs
Mobility of Human, Object, Money and InformationAnalyzing web access data & estimating effectiveness of web advertisementGeneral Simulator of HV or PHV
Given a driving pattern, minimize the fuel consumption of HV or PHV system
Automatic Driving & Traffic Route PlanAnalyzing CAN data & constructing map matching system based on GPS data
Cyber Physical System(CPS) & Mobility Optimization Engine
Real World Cyber World Real World• Data acquisition
• Censoring, Sensing, …
• Optimization• Simulation• Analyzing
• Feedback• Realization• Display
…
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Human and objectsdetectionfrom cameras
Obtaining the most likely passage using optimization and graph analysis
Detection and visualization of congestions and its origins
High Dimensional Data
Low Dimensional Representation
Based on Manifold Theory
Extract nice low dimensional representation from high dimensional original data
多様体理論
With extremely large scale of access data gathered by[1]Clustering users under considering users’ interest each website by 3 optimization problem[2]Fitting user’s time on website to single weibull distribution every cluster and website
Proposing New Website Performance Metricby Obtaining How to Change User’s Interest
Fitting
Fitting
Clustering
Weibull distribution
①Nonnegative Matrix Factorization
②LP (Constrained Network flow Problem)
Pick up feature vector of
each webpage and user
Calculate the proportion ofclusters in each website
under given feature vector
Decide which cluster the user belongs
when the user visits certain website
③LP (Constrained Network flow Problem)
Analyzing Web access data & Estimating effectiveness of Web advertisement
Basic Requirements for AI Cloud System
PFSLu stre・
GPFS
Ba tch Job Sch ed u l er s
Loca l Fla sh + 3 D
Xp o in t Stor a g e
DFSHDFS
BD/AI U ser Ap p l ica tion s
RDBPostg reSQL
Py th on , Ju p yte r N o tebook , R etc. + I DL
SQLH ive/Pi g
Clo u d DB/N oSQLHbase/Mond oDB/Red is
Re so u rce Br oke rs
Mach in e Lea rn ing Lib rar ies
Nu m er ica l Lib ra r iesBLAS/Ma tla b
Fo rtra n ・ C・ C+ +Na tive Cod es
BD Alg o r ithm K e rn e ls ( so r t e tc. )
Pa ra l le l Deb u g g e rs a n d Pro f i le rs
W ork f low System s
Graph Com pu tin g Libra ries
Deep Lea rn in g
Fram ew orks
W eb Services
Lin u x Con ta in er s ・ Clou d Ser v ice s
M PI ・ Open M P/ACC・ CUDA/Op en CL
Lin u x OS
I B・ OPAH ig h Ca pa city
Lo w La ten cy N W
X8 6 ( Xeon , Ph i )+Acce l era to r s e . g . GPU,
FPGA, La ke Cr est
Ap p l ica tio n
ü Easy use of various ML/DL/Graph frameworks from Python, Jupyter Notebook, R, etc.
ü Web-based applications and services provision
System So f tw a re
ü HPC-oriented techniques for numerical libraries, BD Algorithm kernels, etc.
ü Supporting long running jobs / workflow for DL ü Accelerated I/O and secure data access to large data
setsü User-customized environment based on Linux
containers for easy deployment and reproducibility
OS
H a rd w a re
ü Modern supercomputing facilities based on commodity components
CPS Mobility Optimization Engine on ABCI•AI(Deep Learning), Graph Analysis, Mathematical Optimization (LP, MILP, SDP, etc.)⇒ Chainer(Chainermn), Caffe, Tensorflow, Keras, SDPARA etc.
4D Geospatial Information System + CPS Mobility Optimization Engine
Current System : Smartphone + Google Maps ⇒New Generation Personal Navigation System⇒ 4D Display + CPS Mobility (life, amusement, security) + Wearable Devices (AR + VR)
サイ バー空間
リ アルタ イ ム計算
オンデマンド 計算
ディ ープ計算
マク ロ解析層
中位解析層
ミ ク ロ解析層
動線データとグラフデータ化 建物や動線の設計
グラフデータと静的データ活用
最適化計算機械学習
ネットワークフロー計算
混雑度予測リアルタイム避難誘導
実世界 実世界実世界のデータ 化 最適化計算、 シミ ュ レーショ ン 実世界へ反映、 制御
⾧期
中期
短期
棚や商品の配置商品や場所等の価値判定
センシングなどの動的データ活用データセンシング
ボトルネック解析最適化計算
CPS Mobility Optimization Engine
4D (Position + time)Geospatial Information
+Wearable Devices
VR + ARData
(Imagery + Point)
Knowledge4D map =
position(3D) + time
Physical CyberData collection + Map renewal
Positioning +Optimized action based on
simulation and big data analysis
Real objects an events Dynamic 3D map
OPEN AI Infrastructure
+
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