Content, progress and pedagogy of the module

Learning objectives

Knowledge

• Representation of Digital Signal Processing (DSP) algorithms
• Cost functions, models of computation and complexity
• Iteration bounds
• Pipelining and retiming
• Folding and unfolding
• Scheduling and allocation
• Data path, control path, Finite State Machine with Data path (FSMD)
• Functional unit arithmetic
• Low power design methods

Skills

• Must be able to apply advanced terms, concepts, and methods, in the context of time-, area-, or energy optimal/constrained mapping of DSP algorithms onto real-time HW/SW architectures.

Competences

• The student must be able to apply the proper terminology in oral and written communication and documentation within the scientific domains of DSP algorithms, and application specific HW/SW architectures.

Type of instruction

As described in § 17.

Exam

Exams