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課程名稱 |
系統效能評估
Performance Modeling |
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開課學期 |
111-2 |
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授課對象 |
電機資訊學院 資訊網路與多媒體研究所 |
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授課教師 |
周承復 |
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課號 |
CSIE5023 |
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課程識別碼 |
922 U0240 |
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班次 |
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學分 |
3.0 |
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全/半年 |
半年 |
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必/選修 |
選修 |
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上課時間 |
星期三7,8,9(14:20~17:20) |
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上課地點 |
資111 |
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備註 |
總人數上限：40人 |
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課程簡介影片 |
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核心能力關聯 |
核心能力與課程規劃關聯圖 |
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課程大綱
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為確保您我的權利,請尊重智慧財產權及不得非法影印
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課程概述 |
An intro. to techniques and tools
Construct and analyze a model (or by simulations) for computer and communication systems designs.
Model-based, AI-based (DNN, data-driven) Or Both?
Example
Internet, wireless communication, operating system, parallel and distributed system, database system, programming languages, big data analytics, cloud computing….
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課程目標 |
An intro. to techniques and tools
Construct and analyze a model (or by simulations) for computer and communication systems or applications designs.
Model-based, AI-based (DNN, data-driven) Or Both? |
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課程要求 |
Basic ML and Programming knowledge
Math/Statistics knowledge
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預期每週課後學習時數 |
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Office Hours |
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指定閱讀 |
papers and slides |
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參考書目 |
Queueing systems (vol. I & II); Kleinrock
Analytical Performance Modeling for Computer Systems; Y.C. Tay
Prob., Stochastic process., and Queueing Theory; Randy Nelson.
Combinatorial Optimization: Algorithms and Complexity; Christos. H. Papadimitriou and Kenneth Steiglitz |
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評量方式
(僅供參考) |
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週次 |
日期 |
單元主題 |
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第1週 |
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Introduction |
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第2週 |
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Probability review
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第3週 |
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Discrete Time Event Simulator
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第4週 |
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Stochastic Processes
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第5週 |
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Stochastic Processes
Poisson Process
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第6週 |
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Elementary queueing theory
M/M/1, M/M/1 variants
M/G/1, M/G/1 variants, and Priority Queue
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第7週 |
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Elementary queueing theory
M/M/1, M/M/1 variants
M/G/1, M/G/1 variants, and Priority Queue
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第8週 |
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sample of mid-term exam
paper list
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第9週 |
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Intermediate queueing theory
Bounding techniques
Matrix Geometric solutions: high-dimensional MC
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第10週 |
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Intermediate queueing theory
Bounding techniques
Matrix Geometric solutions: high-dimensional MC
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第11週 |
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Average Value and Fluid approximation |
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第12週 |
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Open and close system
equilibrium decomposition
bottleneck analysis
flow equivalence
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第13週 |
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Markov Decision Process and Reinforcement Learning |
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第14週 |
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Diffusion Model
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第15週 |
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Paper Presentation
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第16週 |
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Final Project Presentation
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