In recent years, growing system complexity and shrink-ing time-to-market requirements have resulted in a strong need for new design methods and tools. In order to keep pace with the increased system complexity, designers must work at a higher level of abstraction [1]. Depending on the abstraction level (namely, the number of details used to model the system) different concerns can be addressed and solved. At each step of the design process, the key to cope with complexity is to model the systems, only with the minimum number of details needed. Abstraction hides complexity and accelerates design process. Tools support is needed throughout all steps of the design flow, from the formal specification of the system to its physical implementation.
Traditionally, the design of embedded systems has been carried out by decomposing and allocating the system to hardware and software, then allowing separate hardware and software design teams to design their respective parts, and finally integrating hardware and software. This separation of design tasks leads to the potential for initial design mistakes to be carried until the integration phase, where they are much more difficult and costly to correct. This issue has been widely addressed by development of high level languages, that describe both hardware and software, thus keeping their design flow tightly coupled.
Given system functionality the goal is to find the best architecture and the best partitioning of functionality into the architectural components. Here, the term architecture is used to mean not only the set of hardware and software components forming the system but also their topology. Starting from the same specification, many different architectures and functionality-architecture mapping may be produced. The exploration of all theses alternatives requires the ability to rapidly estimate the performance resulting from a particular partitioning. In order to evaluate performance, we cannot afford to synthesize and simulate at the cycle level, every possible design alternative. The use of a C/C++ based methodology simplifies the system modeling task and maintains computation time within feasible ranges [3]. As a result: 1) design assessment can be done much earlier in the design cycle, and 2) execution time to explore different design tradeoffs is much shorter. In this project, we have used C based methodology to model our system.
Contents
1. Introduction
2. Design Flow
3. Digital Camera as System under Design
3.1. System Description of Digital Camera
4. Specification Model of Digital Camera
5. Profiling
6. C/C++ Based Design Methodologies
7. Results and Conclusion
8. Appendix
