Abstract
This paper presents a new approach to the problem caused by the exploding needs of computing resources in function calculation. The proposal argues for increasing the computing power at the primitive processing level in order to reduce the number of computing levels required to carry out the calculations. This trade-off is developed within the limits of function evaluation by substituting the usual primitives, namely sum and multiplication, by a unique weighted primitive that can be tuned for different values of the weighting parameters. All function points are carried out by successive iterations of the primitive. A parametric architecture implements the design. The case of combined trigonometric functions involved in the calculation of the Hough transform (HT) is analyzed under this scope. It provides memory and hardware resource saving as well as speed improvements, according to the experiments carried out with the HT.
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Signes Pont, M.T., García Chamizo, J.M., Mora Mora, H., de Miguel Casado, G. (2007). Parametric Architecture for Function Calculation Improvement. In: Lukowicz, P., Thiele, L., Tröster, G. (eds) Architecture of Computing Systems - ARCS 2007. ARCS 2007. Lecture Notes in Computer Science, vol 4415. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71270-1_18
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DOI: https://doi.org/10.1007/978-3-540-71270-1_18
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