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Abstract : |
Memory cost is responsible for a large amount of the chip and/or board area of customized video and image processing system realizations. In this paper, we present a novel technique--founded on data-flow analysis-- which allows to address the problem of background memory size evaluation for a given non-procedural algorithm specification, operating on multi-dimensional signals with affine indices. Most of the target applications are characterized by a huge number of signals, so a new polyhedral data-flow model operating on groups of scalar signals is proposed. These groups are obtained by a novel analytical partitioning technique, allowing to select a desired granularity, depending on the application complexity. The method incorporates a way to trade-off memory size with computational and controller complexity. 1, |
