Embedded Computing Systems

This course is no longer offered

(3-0-3-4)

CMPE Degree: This course is Elective for the CMPE degree.

EE Degree: This course is Elective for the EE degree.

Lab Hours: 0 supervised lab hours and 3 unsupervised lab hours.

Technical Interest Groups / Course Categories: VLSI Systems and Digital Design

Course Coordinator:

Prerequisites: ECE 3056 [min C]

Catalog Description

Algorithms and methodologies for the design of real-time, low-power embedded computing systems.

Textbook(s)

Computers as Components: Principles of Embedded Computing System Design

Course Outcomes

  1. design and implement embedded computing systems, including software and hardware.
  2. develop verification/validation evaluation methods for these hardware and software components and analyze and interpret the resulting data.
  3. write laboratory reports and documentation conforming to technical writing standards, including widely used methodologies for design documentation.
  4. analyze the execution time of small sections of assembly language code.
  5. analyze and estimate the worst-case execution time of a program.
  6. analyze and estimate the worst-case power consumption of a program.
  7. describe CPU mechanisms that support context switching.
  8. describe the steps required to switch contexts in a CPU.
  9. compute the CPU utilization of a set of tasks.
  10. analyze the schedulability of a set of tasks using rate monotonic scheduling.
  11. design and implement software that performs a real-time task.
  12. describe an embedded computing system design using UML.
  13. decompose a set of requirements for an embedded computing system into a set of tasks.

Strategic Performance Indicators (SPIs)

Not Applicable

Topic List

* Challenges in embedded computing: real-time, low power. * Comparative computer organization and instruction sets. * Hardware and software for I/O. * Instruction-level performance analysis under the influence of pipelines, caches, and memory management. * Embedded computing platforms. * Models for computer programs. * Path-based performance analysis and optimization, worst-case execution time, average case analysis. * Software power analysis and optimization. * Processes and tasks. * Operating system structures for context switching. * Task graph models and CPU utilization. * Rate-monotonic and earliest deadline first scheduling. * Embedded multiprocessors. * Applications: automotive, multimedia, etc.