Efficient scheduling and instruction selection for programmable digital signal processors

We present an efficient method for optimized instruction selection and scheduling for programmable digital signal processors. Our approach uses artificial intelligence techniques to yield code that is comparable to that of hand-written assembly codes by DSP experts. Several examples which demonstrate the feasibility of the approach, targeted to the TMS32020/50 architecture, are presented.<
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