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Speeding up the design optimization process of Analog/Mixed-Signal circuits has been a subject of active research. Techniques such as metamodeling, artificial neural networks, and optimization over SPICE netlists have been used. While the results are accurate and promising, the effects of process variation on design space exploration still persist. Metamodels created by existing techniques are still...
The design of Analog Mixed-Signal Systems-on-Chip (AMS-SoCs) presents difficult challenges given the number of design specifications that must be met. This situation is more aggravating in the presence of process variation effects for nanoscale technologies. Existing statistical techniques heavily rely on Monte-Carlo analysis for design parameters in an effort to mitigate the effects of process variation...
With CMOS technologies progressing deeper into the nano-scale domain the design of analog and mixed-signal components is becoming very challenging. The presence of parasitics and the complexity of calculations involved create an enormous challenge for designers to keep their design within specifications when reaching the physical layout stage of the design process. This paper proposes a novel ultra-fast...
At the nanoscale domain, the simulation, design, and optimization time of the circuits have increased significantly due to high-integration density, increasing technology constraints, and complex device models. This necessitates fast design space exploration techniques to meet the shorter time to market driven by consumer electronics. This paper presents non-polynomial metamodels (surrogate models)...
The design and optimization complexity of analog/mixed-signal (AMS) components causes significant increase in the design cycle as the technology progresses towards deep nanoscale. This paper presents a two-tier approach to significantly reduce the design cycle time by combining accurate metamodeling and intelligent optimization. The paper first presents metamodeling which is a surrogate model of a...
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