Hardware-Software Codesign for Embedded Numerical Acceleration

Abstract

In this work we aim to strike a balance between performance, power consumption and design effort for complex digital signal processing within the power and size constraints of embedded systems. Looking across the design stack, from algorithm formulation down to accelerator microarchitecture, we show that a high degree of flexibility and design reuse can be achieved without much performance sacrifice. The foundation of our design is a numerical accelerator template. Extensively parameterized, it allows us to develop the design while postponing microarchitectural decisions until program is known. Statically scheduling compiler provides a link between the algorithm and template instantiation parameters. Results show that the derived design can significantly outperform embedded processors for similar power cost and also approach the high-performance processor performance for a fraction of the power cost.