理工学研究科Graduate School of Science and Engineering
COT500X3（計算基盤 / Computing technologies 500）計算機システム工学特論１Computer System Engineering (Ⅰ)
和田 幸一Koichi WADA
授業コードなどClass code etc
| 学部・研究科Faculty/Graduate school | 理工学研究科Graduate School of Science and Engineering |
| 添付ファイル名Attached documents | |
| 年度Year | 2022 |
| 授業コードClass code | YB004 |
| 旧授業コードPrevious Class code | |
| 旧科目名Previous Class title | |
| 開講時期Term | 春学期授業/Spring |
| 曜日・時限Day/Period | 火2/Tue.2 |
| 科目種別Class Type | |
| キャンパスCampus | 小金井 |
| 教室名称Classroom name | 各学部・研究科等の時間割等で確認 |
| 配当年次Grade | |
| 単位数Credit(s) | 2 |
| 備考（履修条件等）Notes | |
| 実務経験のある教員による授業科目Class taught by instructors with practical experience | |
| カテゴリーCategory | 応用情報工学専攻 |
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Outline (in English)
The course introduces the computing models and algorithms of distribution systems. The course also exposes students to an array of big data analysis theories, techniques and practices in different fields of study using distributed models. The topics include distributed computing models, massage-passing and shared memory systems, design and analysis of synchronous and asynchronous algorithms, fault tolerance, and data distribution, collection, processing and analysis in distributed systems. This is a project-based course that provides students with hands-on experience on distributed computing with different data types.
授業で使用する言語Default language used in class
英語 / English
授業の概要と目的（何を学ぶか）Outline and objectives
The course introduces the computing models and algorithms of distribution systems. The course also exposes students to an array of big data analysis theories, techniques and practices in different fields of study using distributed models. The topics include distributed computing models, massage-passing and shared memory systems, design and analysis of synchronous and asynchronous algorithms, fault tolerance, and data distribution, collection, processing and analysis in distributed systems. This is a project-based course that provides students with hands-on experience on distributed computing with different data types.
到達目標Goal
The course will expose students to fundamental concepts into the algorithms and theory of distributed computing and its applications to data analytics. It discusses the important issues such as computing/communication efficiency, resource allocation, synchronization, global/local clock, dead lock, fault tolerance, security, and etc. in HPC, networked computers, wireless/sensor networks, IoTs, etc. This is a project-based course centered on hands-on experiences with methods on different types of data and frameworks.
この授業を履修することで学部等のディプロマポリシーに示されたどの能力を習得することができるか（該当授業科目と学位授与方針に明示された学習成果との関連）Which item of the diploma policy will be obtained by taking this class?
ディプロマポリシーのうち、「DP1」「DP2」「DP3」に関連
授業で使用する言語Default language used in class
英語 / English
授業の進め方と方法Method(s)（学期の途中で変更になる場合には、別途提示します。 /If the Method(s) is changed, we will announce the details of any changes. ）
講義と演習とプロジェクト
アクティブラーニング（グループディスカッション、ディベート等）の実施Active learning in class (Group discussion, Debate.etc.)
あり / Yes
フィールドワーク（学外での実習等）の実施Fieldwork in class
なし / No
授業計画Schedule
授業形態/methods of teaching：対面/face to face
※各回の授業形態は予定です。教員の指示に従ってください。
1[対面/face to face]：Introduction to distributed/parallel computing systems I
Architectures, hared & distributed memory,
2[対面/face to face]：Introduction to distributed/parallel computing systems II
Computation & communication complexity, control/data/processes,
3[対面/face to face]：Parallel algorithm design I
PRAM model
4[対面/face to face]：Parallel algorithm design II
Algorithm design and analysis on PRAM
5[対面/face to face]：Computing platforms for shared memory I
OpenMP
6[対面/face to face]：Computing platforms for shared memory II
GPU
7[対面/face to face]：Computing platforms for distributed memory
MPI & PVM
8[対面/face to face]：Computing on synchronous computer networks I
Synchronous network model
9[対面/face to face]：Computing on synchronous computer networks II
Algorithms of synchronized networks: lead election
10[対面/face to face]：Computing on synchronous computer networks III
Algorithms of synchronized networks: shortest path, minimum spanning tree,etc.
11[対面/face to face]：Computing on asynchronous computer networks I
Asynchronous network model, algorithms of synchronized networks: leader election, spanning tree
12[対面/face to face]：Computing on asynchronous computer networks II
Algorithms of synchronized networks: , breadth-first search; local time and global snapshots, resource allocation, deadlock and dinner of philosophers problem
13[対面/face to face]：Applications in distributed computing systems I
Sensor fusion and sensor
networks
14[対面/face to face]：Applications in distributed computing systems II
IoTs, brock chains, etc.
授業時間外の学習（準備学習・復習・宿題等）Work to be done outside of class (preparation, etc.)
【本授業の準備・復習時間は、各4時間を標準とします。】
6 hours per week
テキスト（教科書）Textbooks
１．Title: Distributed Algorithms: An Intuitive Approach.
Authors: Wan Fokkink
Publisher: The MIT Press (2013)
ISBN: 9780262026772
2．Title: An Introduction to Parallel Programming
Author: Peter S. Pacheco
Publisher: MK
ISBN: 978012374260-5
参考書References
Title: Distributed Algorithms
Author: Nancy A. Lynch
Publisher: Morgan Kaufmann
ISBN: 9781558603486
成績評価の方法と基準Grading criteria
Assignments: 30%
Projects: 30%
Exams: 40%
学生の意見等からの気づきChanges following student comments
特になし
学生が準備すべき機器他Equipment student needs to prepare
Visual Studio 2010 以降
その他の重要事項Others
特になし