Floating-point bit-width optimization for low-power signal processing applications
To enable floating-point (FP) signal processing applications in low-power mobile devices, we propose a lightweight FP design flow that can optimize the bit-width configuration. The optimization considers both the hardware cost and the numerical precision. Variable grouping is used to reduce the complexity of optimization by connecting software description and hardware implementation. The optimization algorithm is able to avoid local optima, and multiple-phase optimization helps to reduce the cost further. We apply the proposed design flow to the design of inverse discrete cosine transform (IDCT), and show that the power consumption of our lightweight FP IDCT is comparable to an optimized fixed-point design. In addition, promising results on some real-world applications such as video coding and speech recognition demonstrate that lightweight FP signal processing will find more and more applications in low-power devices.