Speed binning aware design methodology to improve profit under parameter variations

Abstract

Designing high-performance systems with high yield under parameter variations has raised serious design challenges in nanometer technologies. In this paper, we propose a profit-aware yield model, based on which we present a statistical design methodology to improve profit of a design considering frequency binning and product price profile. A low-complexity sensitivity-based gate sizing algorithm is developed to improve the profitability of design over an initial yield-optimized design. We also propose an algorithm to determine optimal bin boundaries for maximizing profit with frequency binning. Finally, we present an integrated design methodology for simultaneous sizing and bin placement to enhance profit under an area constraint. Experiments on a set of ISCAS85 benchmarks show up to 26% (36%) improvement in profit for fixed bin (for simultaneous sizing and bin placement) with three frequency bins considering both leakage and delay bounds compared to a design optimized for 90% yield at iso-area