Embedded Parallel Computing
The course is intended to provide knowledge of how parallel computing can be used as a way to meet application demands in embedded systems, such as performance and power efficiency. Further, it is intended to give a general insight into current research and development in regard to parallel architectures and computation models. Parallelism of various types exists in all modern computer architectures, and knowledge about how to apply parallelism is necessary, in particular, when designing embedded computer systems.
Level:
Advanced level
Application code:
X3434
Entry requirements:
Courses in computer science, computer engineering and electrical engineering of at least 90 credits. Courses in mathematics of at least 30 credits or courses including calculus, linear algebra and transform methods. The courses Artificial Intelligence 7.5 credits, Engineering Mathematics 7.5 credits and Algorithms, Data Structures and Problem Solving 7.5 credits or Real-Time Embedded Systems 7.5 credits. English 6.
Selection rules:
Available for exchange students. Limited numbers of seats.
Start week:
week: 12
Instructional time:
Daytime
Language of instruction:
Teaching is in English.
Level:
Advanced level
Application code:
X3434
Entry requirements:
Courses in computer science, computer engineering and electrical engineering of at least 90 credits. Courses in mathematics of at least 30 credits or courses including calculus, linear algebra and transform methods. The courses Artificial Intelligence 7.5 credits, Engineering Mathematics 7.5 credits and Algorithms, Data Structures and Problem Solving 7.5 credits or Real-Time Embedded Systems 7.5 credits. English 6.
Selection rules:
Available for exchange students. Limited numbers of seats.
Start week:
week: 14
Instructional time:
Daytime
Language of instruction:
Teaching is in English.
