Course Name (Chinese):并行程序设计
(English): Parallel Programming
Course Name: Parallel Programming |
Course Code: S2298046 |
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Semester: 4 |
Credit: 3 |
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Program: Computer Science |
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Course Module: Specialized Optional |
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Responsible:Ce Yu |
E-mail: yuce@tju.edu.cn |
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Department: College of Intelligence and Computing, Tianjin University |
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Time Allocation (1 credit hour = 45 minutes) |
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Exercise |
Lecture |
Lab-study |
Project |
Internship (days) |
Personal Work |
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12 |
12 |
24 |
8 |
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Course Description The course is designed for Engineering Master of TIEI. Parallel computing is the main way to achieve high-performance, high-availability computer systems. Courses, in parallel computing theme, focuses on contemporary parallel computer system and structure models, design principles and methods of parallel algorithm design and parallel programs, integrate the structure of parallel machines, parallel algorithms and parallel programming, trying to reflect the latest of the discipline achievements and trends. Besides, some experimental projects will be combined to cultivate students to develop simple parallel programming. Students will have a preliminary and extensive understanding about parallel programming, which enables students to become more effective Programs. |
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Prerequisite Ÿ Computer architecture: understand the basic components of the computer architecture, Ÿ Operating system: understand basic elements of operating system, and to Compiler theory: understand the process of translating a source program to target language. |
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Course Objectives This course discusses basic concepts of computer system to help students understand the program better and enhance their professional skills. After this course, students should be able to: Ÿ Understand the basic concepts of parallel processing and a variety of academic and technical issues involved, as well as cloud computing and distributed parallel programming technology, cloud computing applications design and development of technology. Ÿ Grasp the parallel processing technology, the latest achievements and trends, in order to be able to move in this direction deeply in the future deep. |
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Course Syllabus Ÿ Parallel computer architecture and model: understand the parallel computer system and its structure model, including parallel system interconnection, system structure model of parallel computers Ÿ Evaluation of parallel computing performance: introduction performance evaluation of parallel computing, including speedup, scalability, benchmarking and other issues Ÿ Fundamentals of designing parallel algorithms: introduction to the basics of parallel algorithms Ÿ Design methodology of parallel algorithms: introduce three general design method of parallel algorithms Parallel programming models: introduced a parallel programming model |
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Textbooks & References Ÿ Parallel Programming ModelsK Gilles.The semantics of a simple language for parallel programming.1974 Ÿ W Gropp,E Lusk,A Skjellum.Using MPI: portable parallel programming with the message-passing interface.1999 B Wilkinson, M Allen.Parallel programming.1999 |
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Capability Tasks CT1: To grasp the basic concepts of parallel processing technology. CT2: To grasp parallel computer system and its structural model, and how to evaluate the performance of parallel computing. CS1:To learn parallel programming methods and models. CS2: To understand MPI and PVM parallel programming. |
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Achievements Ÿ To understand the concept of parallel computing, including parallel system interconnection, system architecture model of parallel computers. - Level: N Ÿ To master the basics of parallel algorithm design, and understand the existing parallel computing model and parallel algorithm design methods, design techniques and design process. - Level: M Ÿ To master MPI and PVM parallel programming environment, including their architecture, libraries and specific programming. - Level: N |
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Students:Computer Science,Year 2, 3 |
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Assessment： |
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Exam |
Assignment |
Report |
Term Paper |
Presentation |
Others |
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√ |
√ |
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Language of assessment：Chinese Attendance： 10 % Homework: % Mid-term report/test： 30 % Final report/test： 60 % |
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