Digital Signal Processing on MMXTM Technology

Algorithmic-level optimization and programming-level optimization are tightly coupled with each other. Many programmers can optimize the implementation of a specific algorithm using MMX™ technology. However, without algo-rithmic-level optimization, the speed-up of the optimization will be limited. On the other hand, many algorithm developers can optimize the DSP algorithm in terms of the numbers of operations (multiplications or additions). Nonetheless, without implementation details, the number of operations cannot be directly translated into the number of clock cycles spent in CPU. Moreover, many algorithms can accomplish the same task. For best performance of DSP/multimedia applications on personal computers, we should consider algorithm-MMX co-optimization. One way to increase performance of digital signal processing is to execute several computations in parallel. MMX is one of the techniques that speed up software performance by performing the same operation on multiple data elements in parallel using a single instruction. However, MMX programming and designing DSP algorithms for MMX are full of twists and turns. Implementation of digital signal processing using MMX technology is a mix of a science and an art. Matching the algorithms to MMX instruction capabilities is the key to extracting the best performance. This chapter is covering algorithm design and algorithmic-level optimization for MMX. In this chapter, besides showing you how to optimize your code and algorithm-from a science view, we will show you how we go about optimizing ours-from an art perspective.