一、課程說明(Course Desc<x>ription)
<br>熟悉平行程式語言及平行程式設計
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<br> 二、指定用書(Text Books)
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<br>1. Parallel Programming – Techniques and applications Using Networked  
<br>Workstations and 
<br>Parallel Computers, Barry Wilkinson and Michael Allen, Prentice Hall, 1999.
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<br>2. Parallel Programming in C with MPI and OpenMP, Michael J. Quinn, McGraw-
<br>Hill, 2003.
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<br>3. Intel Multi-Core Programming
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<br> 三、參考書籍(References)
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<br>1. Documentation (PVM, MPI, Cilk, Pthread, TreadMark, SAM).
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<br>2. Designing and Building Parallel Programs, Ian Foster, Addison Wesley, 1995.
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<br> 四、教學方式(Teaching Method)
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<br>上課
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<br> 五、教學進度(Syllabus)
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<br>Lectures:
<br>Part I: Introduction
<br>- Introduction to Parallel Computers
<br>- Introduction to Parallel Computing
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<br>Part II: Parallel Programming
<br>- Message-Passing Programming (MPI)
<br>- Shared Memory Programming (Pthread and OpenMP)
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<br>Part III: Parallel Computing Techniques
<br>- Embarrassingly Parallel Computations
<br>- Partitioning and Divide-and-Conquer Strategies
<br>- Pipelined Computations
<br>- Synchronous Computations
<br>- Load Balancing and Termination Detection
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<br>Part IV: GPU Programming
<br>- Heterogeneous computing
<br>- CUDA programming model
<br>- GPU Architecture & Multi-GPU
<br>- Advanced CUDA Programming & Optimization
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<br>Part V: Distributed Programming
<br>- Big Data fr<x>ameworks: MapReduce, Spark
<br>- Distributed Deep Learning
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<br> 六、成績考核(Evaluation)
<br>Course partipation - 10%
<br>Programming assignment - 90%
<br>(1) MPI: basic parallel programming
<br>(2) OpenMP + MPI: load balancing
<br>(3) Pthread & MPI: synchronous computing
<br>(4) CUDA: GPU Programming
<br>(5) Final Project