Hiroshima University Syllabus

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Academic Year 2022Year School/Graduate School School of Informatics and Data Science
Lecture Code KA211001 Subject Classification Specialized Education
Subject Name 並列分散処理
Subject Name
Subject Name in
Parallel and Distributed Processing
カサギ アキヒコ,イトウ ヤスアキ
Campus Higashi-Hiroshima Semester/Term 3rd-Year,  Second Semester,  Intensive
Days, Periods, and Classrooms (Int) Inte
Lesson Style Lecture Lesson Style
(More Details)
Lecture and exercise 
Credits 2.0 Class Hours/Week   Language of Instruction B : Japanese/English
Course Level 3 : Undergraduate High-Intermediate
Course Area(Area) 25 : Science and Technology
Course Area(Discipline) 02 : Information Science
Eligible Students 3nd-year (School of Informatics and Data Science)
Keywords UNIX, process parallel, thread parallel, SIMD, GPU, CUDA  
Special Subject for Teacher Education   Special Subject  
Class Status
within Educational
Using the content learned in the basic subjects, deepen knowledge and understanding of the technical expertise. 
Criterion referenced
Informatics and Data Science Program
(Abilities and Skills)
・I3. Knowledge related to hardware and software, and the programming skills required for efficiently processing data.
Class Objectives
/Class Outline
The actual situation of recent multi-core processors and the necessity of parallel processing is introduced, and the processing model and operation method of parallel computing using CPU and GPU are explained respectively. To develop an operation and understanding of parallel processing programming using a large number of cores, and to acquire programming skills for parallel processing through practical exercises. 
Class Schedule lesson1: Thread parallel processing
lesson2: Thread parallel programming using OpenMP
lesson3: Thread parallel programming exercise
lesson4: Thread parallel programming exercise
lesson5: Process parallel processing
lesson6: Process parallel programming using MPI
lesson7: Process parallel programming exercise
lesson8: Process parallel programming exercise
lesson9: Basis of GPU
lesson10: Basis of CUDA programming
lesson11: Basic CUDA programming exercise
lesson12: Basic CUDA programming exercise
lesson13: Parallel computing technique for GPUs
lesson14: Librarization for GPU programs
lesson15: CUDA programming exercise

PC or AV used in
(More Details)  
Learning techniques to be incorporated  
Suggestions on
Preparation and
Please review C language programing 
Grading Method Exercise and reports 
Practical Experience  
Summary of Practical Experience and Class Contents based on it  
Message Details will be posted on Momiji as soon as the schedule is confirmed. 
Please fill in the class improvement questionnaire which is carried out on all classes.
Instructors will reflect on your feedback and utilize the information for improving their teaching. 
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