Modern advances in reconfigurable analog technologies are allowing field-programmable analog arrays (FPAAs) to dramatically grow in size, flexibility, and usefulness. With these advances, analog circuits and systems can be programmable, reconfigurable, adaptive, implemented on standard CMOS to take advantage of scaled CMOS technology, and at a density comparable to digital memories. Our goal in this paper is to develop the first physical design automation toolset for floating-gate based FPAA with focus on minimization of parasitic effects on FPAA interconnect. We provide graph-based analog circuit and FPAA device modeling suitable for efficient mapping. Our FPAA clustering algorithm constructs Computational Analog Blocks (CAB) from analog circuit elements while improving the utilization of the device and reducing its impact on the total number of routing switches used. Experimental results demonstrate the effectiveness of our approach.
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