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Many of today's DSP applications are subject to real-time constraints. Many applications will eventually grow to a point where they are stressing the available CPU and memory resources. Understanding the workings of the DSP architecture, compiler, and the application algorithms can speed up applications, sometimes by an order of magnitude. This article will summarize some of the techniques that can improve the performance of your code in terms of cycle count, memory use, and power consumption. Embedded real-time applications are an exercise in optimization. There are three main optimization strategies that the embedded DSP developer needs to consider: 1. DSP architecture optimization; 2. DSPs are optimized microprocessors that perform signal processing functions very efficiently by providing hardware support for common DSP functions; 3. DSP algorithm optimization; choosing the right implementation technique for standard and often used DSP algorithms can have a significant impact on system performance; 4. DSP complier optimization; DSP compilers are tools that help the embedded programmer exploit the DSP architecture by mapping code onto the resources in such as way as to utilize as much of the processing resources as possible, gaining the highest level of architecture entitlement as possible