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Cost functions for mapping DSP algorithms onto multiprocessors

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2 Author(s)
D. J. Rabideau ; Rome Lab., Griffiss AFB, NY, USA ; A. O. Steinhardt

In this correspondence, we examine several cost functions that have been proposed for automating the mapping of algorithms onto multiprocessors. Through a case study of the recursive least squares problem, we develop improved cost functions. One of these (the Min-Max+Idle cost function) performed better than the others and was applied to the related problem of full QR decomposition. Experiments on an iPSC/860 hypercube confirm that automated mapping can lead to lower execution times than published mappings

Published in:

IEEE Transactions on Signal Processing  (Volume:43 ,  Issue: 1 )