Variation-Aware Topology Synthesis and Knowledge Extraction

Abstract

This chapter aims to simultaneously address problems which previous chapters attacked separately. In Chap. 3, SANGRIA did variation-aware design (sizing). In Chaps. 6–7, MOJITO did topology synthesis (nominally). This chapter does both: variation-aware topology synthesis. By combining the two features at once, we bias the MOJITO search towards topologies that are robust, resulting in the MOJITO-R tool [Mcc2009d]. It also does knowledge extraction on the variation-aware synthesis results, using tools from Chap. 8.

The rest of this chapter is organized as follows. Section 9.2 gives the problem specification. Section 9.3 gives background on variation-aware topology synthesis. Section 9.5 describes MOJITO-R, the proposed approach. Section 9.6 gives experimental results which include knowledge extraction. Finally, Sect. 9.7 concludes.

Divide each difficulty into as many parts as is feasible and necessary to resolve it.

– Rene Descartes