A. Casotto

Bio: A. Casotto is an academic researcher from University of California, Berkeley. The author has contributed to research in topics: Iterative design & Simulated annealing. The author has an hindex of 4, co-authored 4 publications receiving 323 citations.

A Parallel Simulated Annealing Algorithm for the Placement of Macro-Cells

Abstract: A modification of the classical Simulated Annealing algorithm for the macro-cell placement problem is proposed for implementation on multiprocessor systems. The algorithm has been implemented on the Sequent Balance 8000, a multiprocessor system with a shared-memory architecture. Experimental results show that the new algorithm obtains results comparable in quality to those of the single processor version; processor utilization is greater than 80 percent using up to eight processors.

A Constraint-driven Placement Methodology For Analog Integrated Circuits

Abstract: A new constraint-driven methodology for the placeinent of analog IC's is described. Electrical performance specifications are automatically translated into constraints on the layout parasitics. These constraints and the seiisiitivity iiiforinatioii of the circuit are then used to control a Simulated Annealingbased placement algorithm. At each step of the annealing a fast check on performance degradations is performed to guarantee that the tool has the necessary robur,tness.

Design management based on design traces

Abstract: VOV is an automatic manager for VLSI design. It is based on the idea that CAD tools can leave a trace of their execution. The trace is represented as a bipartite directed and acyclic graph, in which the nodes represent either design data or CAD transactions. By managing and analyzing the traces, VOV offers a wide variety of services related to design management, such as coordination of team design, automatic execution of CAD transactions, and capture of design history and data dependencies. All of these services are provided in a nonintrusive fashion. VOV has the notion of measurement on the design data, an ingredient which is necessary to provide even more services: tracking of design specifications, validation of design data, and design estimation. >

Automated design management using traces

Abstract: An automatic management system for CAD based on the idea that CAD tools can leave a trace of their execution is proposed. The trace, represented as a bipartite directed and acyclic graph in which the nodes represent either design data or tool invocations, is both a record of the design activity and a graph representing the dependencies among the design objects. The architecture of the proposed system is distributed. A server manages the trace, while a number of clients can concurrently interact with the trace through the server. The system is nonintrusive, because it does not affect the way designers interact with the tools. The design manager has been implemented in a system called VOV, which has been tested. >

A Taxonomy of Hybrid Metaheuristics

Abstract: Hybrid metaheuristics have received considerable interest these recent years in the field of combinatorial optimization. A wide variety of hybrid approaches have been proposed in the literature. In this paper, a taxonomy of hybrid metaheuristics is presented in an attempt to provide a common terminology and classification mechanisms. The taxonomy, while presented in terms of metaheuristics, is also applicable to most types of heuristics and exact optimization algorithms. As an illustration of the usefulness of the taxonomy an annoted bibliography is given which classifies a large number of hybrid approaches according to the taxonomy.

Metaheuristics: A bibliography

Abstract: Metaheuristics are the most exciting development in approximate optimization techniques of the last two decades. They have had widespread successes in attacking a variety of difficult combinatorial optimization problems that arise in many practical areas. This bibliography provides a classification of a comprehensive list of 1380 references on the theory and application of metaheuristics. Metaheuristics include but are not limited to constraint logic programming; greedy random adaptive search procedures; natural evolutionary computation; neural networks; non-monotonic search strategies; space-search methods; simulated annealing; tabu search; threshold algorithms and their hybrids. References are presented in alphabetical order under a number of subheadings.

Computer-aided design of analog and mixed-signal integrated circuits

Abstract: This survey presents an overview of recent advances in the state of the art for computer-aided design (CAD) tools for analog and mixed-signal integrated circuits (ICs). Analog blocks typically constitute only a small fraction of the components on mixed-signal ICs and emerging systems-on-a-chip (SoC) designs. But due to the increasing levels of integration available in silicon technology and the growing requirement for digital systems to communicate with the continuous-valued external world, there is a growing need for CAD tools that increase the design productivity and improve the quality of analog integrated circuits. This paper describes the motivation and evolution of these tools and outlines progress on the various design problems involved: simulation and modeling, symbolic analysis, synthesis and optimization, layout generation, yield analysis and design centering, and test. This paper summarizes the problems for which viable solutions are emerging and those which are still unsolved.

A survey of simulated annealing as a tool for single and multiobjective optimization

Abstract: This paper presents a comprehensive review of simulated annealing (SA)-based optimization algorithms. SA-based algorithms solve single and multiobjective optimization problems, where a desired global minimum/maximum is hidden among many local minima/maxima. Three single objective optimization algorithms (SA, SA with tabu search and CSA) and five multiobjective optimization algorithms (SMOSA, UMOSA, PSA, WDMOSA and PDMOSA) based on SA have been presented. The algorithms are briefly discussed and are compared. The key step of SA is probability calculation, which involves building the annealing schedule. Annealing schedule is discussed briefly. Computational results and suggestions to improve the performance of SA-based multiobjective algorithms are presented. Finally, future research in the area of SA is suggested.