Taking as a starting point a collection of algebraic primitives that captures the SIMD computational model, we show in this paper our methodology for designing, mapping and implementing algorithms for SIMD-vector signal processors with scalable level of parallelism. Taking as an example the LMS, we show how an algorithm, which has been designed to exhibit a suitable level of data parallelism can be described by these algebraic primitives. In turn, these algebraic primitives are programmed in a matrix oriented language. A suitable compiler generates object code for SIMD processors with a scalable number of processing elements.
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