Abstract

It is pointed out that by establishing a relationship between the basic properties of linear computations and several optimizing transformations, it is possible to optimally speed up linear computations with respect to those transformations while keeping the latency fixed. Furthermore, arbitrarily fast, asymptotically optimal implementations can be obtained by adding retiming and loop unrolling to the transformations set and trading latency for throughput. The proposed techniques have yielded results superior to the best published previously on all benchmark examples. The presented approach is also applicable to general (nonlinear) computations. >

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