By Ricardo Lourenço, Nuno Lourenço, Nuno Horta
This paintings addresses the examine and improvement of an cutting edge optimization kernel utilized to analog built-in circuit (IC) layout. fairly, this works describes the changes contained in the AIDA Framework, an digital layout automation framework totally constructed via on the built-in Circuits Group-LX of the Instituto de Telecomunicações, Lisbon. It focusses on AIDA-CMK, via bettering AIDA-C, that is the circuit optimizer component to AIDA, with a brand new multi-objective multi-constraint optimization module that constructs a base for a number of set of rules implementations. The proposed resolution implements 3 methods to multi-objective multi-constraint optimization, particularly, an evolutionary procedure with NSGAII, a swarm intelligence procedure with MOPSO and stochastic hill mountaineering process with MOSA. furthermore, the carried out constitution permits the simple hybridization among kernels remodeling the former basic NSGAII optimization module right into a extra developed and flexible module assisting a number of unmarried and multi-kernel algorithms. the 3 multi-objective optimization ways have been demonstrated with CEC2009 benchmarks to limited multi-objective optimization and proven with actual analog IC layout difficulties. The completed effects have been in comparison by way of functionality, utilizing statistical effects bought from a number of self sustaining runs. eventually, a few hybrid techniques have been additionally experimented, giving a foretaste to a variety of possibilities to discover in destiny work.
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Additional info for AIDA-CMK: Multi-Algorithm Optimization Kernel Applied to Analog IC Sizing
2 Two-Stage Miller Ampliﬁer The other differential ampliﬁer topology considered in this work is the two-stage miller operational ampliﬁer, whose schematic is shown in Fig. 2. Again, the optimization variables are the width, length, number of ﬁngers and number of rows of the MOS devices, and the length and number of ﬁngers of the MOM capacitor. 3. Like before, the circuit’s performance ﬁgures are measured from the simulation results. 4 indicates the design speciﬁcations for this circuit working as a versatile low power DC buffer.
This design has the advantage that every element can be used by any algorithm, but puts some effort to maintain the data representation in order to be usable by all algorithms. Also allows the optimizers to be used in another types of optimization. The framework is centered around the abstraction layer that implements the general multi-objective problem. This interface can be instantiated as a circuit problem or as a mathematical problem, and each of those problems are evaluated © The Author(s) 2015 R.
In Fig. 8b a more greedy approach is used, following the same principle of using different methods to explore the same space but selects only the best individuals using rank and crowding distance, and setting the same individuals to all the kernels. Another approach is shown in Fig. 8c, where the elements are sorted using some criteria and split into blocks allowing the algorithms to explore different regions of the search space. 8. With this combination, it is possible to optimize a problem; for example, using 400 cycles of NSG-AII and then 100 cycles of MOSA to ﬁne tune the solutions.
AIDA-CMK: Multi-Algorithm Optimization Kernel Applied to Analog IC Sizing by Ricardo Lourenço, Nuno Lourenço, Nuno Horta