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This course introduces various parallel programming paradigms, algorithms, and architectures, including some hands-on parallel programming on shared-memory and message-passing parallel architectures. The course aims to help students understand conceptually what parallel computing systems are, what they do, and how they are designed and constructed. Students who registered the course will learn different parallel languages and an ability to parallelize a sequential application using MPI and OpenMP.
The prerequisites for this course are data structure and algorithms, programming language, computer architecture, and operating systems. Students are expected to have strong programming background before taking this course.
Lecture time: Wednesday 6:00 PM - 8:20 PM
Weeks: 2nd week to 12th week
Location: Lecture Room, 2nd Floor at Big Data Center
|Minyi Guo||guo-my AT cs.sjtu.edu.cn||Room 415 SEIEE Building #3||(021) 3420 4438||By appointment|
|Chentao Wu||wuct AT cs.sjtu.edu.cn||Room 513 SEIEE Building #3||(021) 3420 8230||By appointment|
|Pu Pangemail@example.com||Just drop by|
|Wenyi Zhaofirstname.lastname@example.org||Room 118 SEIEE Building #3||Just drop by|
Students are encouraged to talk to each other, to the course staff, or to anyone else about any of the assignments. Assistance must be limited to discussion of the problem and sketching general approaches to a solution. Each student (or team) must write out his or her own solutions to the homework. Any forms of copying code is strictly prohibited.
The deadline for any assignment can be extended with a 10% penalty per day.
No deadline can be extended by more than three days. Assignments will NOT be accepted 72 hours after the due date.
If you are ill: Contact the instructor and get a medical note.
Cheating is NOT tolerated! Please read the SJTU's Academic Code of Conduct if you are not familiar with the definition of cheating. If you are caught cheating on an assignment, you will get a zero for that assignment. Other repercussions are also possible.
homework to download: https://pan.baidu.com/s/1VhZ2CSCx7D2aShxhGshUpQ
uploads for teachers: https://pan.baidu.com/s/1c8fe6MQCiCiOUBI8wh-14Q password: 8rgz