Application of Decision Diagrams for Information Storage and Retrieval

Technology is improving at an amazing pace and one reason for this advancement is because of unprecedented growth in the field of Information Technology and also in Digital Integrated Circuit technology over the past few decades. The size of a typical modern database is in the order of high ends of gigabytes and even terabytes. Researchers were successful in designing complex databases but there is still lot of activity on effectively making use of this stored information. There have been significant advancements in the field of Logic optimization and also in Information storage and retrieval but there has been very little transfer of these methods. The purpose of this study is to investigate the use of powerful Computer Aided Design (CAD) techniques for efficient information storage and retrieval. In the work presented in this thesis, it is shown that Decision Diagrams can be used for efficient data storage and information retrieval. An efficient technique is proposed for each of the two key areas of research in Database systems known as Query Optimization and Datamining . Encouraging results are obtained indicating that using hardware techniques for information processing can be a new approach for solving these problems. An SQL query is represented using a hardware data structure known as an AND/OR graph and an SQL parser is interfaced with AND/OR package to achieve query optimization. Optimization using AND/OR graphs works only in the Boolean domain and to make the process of query optimization more complete it has to be investigated in Multivalued domain. The possibility of using MDD as a data structure to represent the query in the multi valued domain is discussed and a synthesis technique is developed to synthesize Multi Valued Logic Networks using MDD. Another useful data structure known as BDD can be used to store the large transaction files used in datamining applications very effectively

Boolean Expression Diagrams

This paper presents a new data structure called Boolean Expression Diagrams (BEDs) for representing and manipulating Boolean functions. BEDs are a generalization of Binary Decision Diagrams (BDDs) which can represent any Boolean circuit in linear space and still maintain many of the desirable properties of BDDs. Two algorithms are described for transforming a BED into a reduced ordered BDD. One is a generalized version of the BDD apply-operator while the other can exploit the structural information of the Boolean expression. This ability is demonstrated by verifying that two di erent circuit implementations of a 16-bit multiplier implement the same Boolean function. Using BEDs, this veri cation problem is solved in less than a second, while using standard BDD techniques this problem is infeasible. Generally, BEDs are useful in applications, for example tautology checking, where the end-result as a reduced ordered BDD is small

Probabilistic representation and manipulation of Boolean functions using free Boolean diagrams

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1994.Includes bibliographical references (p. 145-149).by Amelia Huimin Shen.Ph.D

NuMDG: A New Tool for Multiway Decision Graphs Construction

Multiway Decision Graphs (MDGs) are a canonical representation of a subset of many-sorted first-order logic. This subset generalizes the logic of equality with abstract types and uninterpreted function symbols. The distinction between abstract and concrete sorts mirrors the hardware distinction between data path and control. Here we consider ways to improve MDGs construction. Efficiency is achieved through the use of the Generalized-If-Then-Else (GITE) commonly operator in Binary Decision Diagram packages. Consequently, we review the main algorithms used for MDGs verification techniques. In particular, Relational Product and Pruning by Subsumption are algorithms defined uniformly through this single GITE operator which will lead to a more efficient implementation. Moreover, we provide their correctness proof. This work can be viewed as a way to accommodate the ROBBD algorithms to the realm of abstract sorts and uninterpreted functions. The new tool, called NuMDG, accepts an extended SMV language, supporting abstract data sorts. Finally, we present experimental results demonstrating the efficiency of the NuMDG tool and evaluating its performance using a set of benchmarks from the SMV package

Safety system design optimisation

This thesis investigates the efficiency of a design optimisation scheme that is appropriate for systems which require a high likelihood of functioning on demand. Traditional approaches to the design of safety critical systems follow the preliminary design, analysis, appraisal and redesign stages until what is regarded as an acceptable design is achieved. For safety systems whose failure could result in loss of life it is imperative that the best use of the available resources is made and a system which is optimal, not just adequate, is produced. The object of the design optimisation problem is to minimise system unavailability through manipulation of the design variables, such that limitations placed on them by constraints are not violated. Commonly, with mathematical optimisation problem; there will be an explicit objective function which defines how the characteristic to be minimised is related to the variables. As regards the safety system problem, an explicit objective function cannot be formulated, and as such, system performance is assessed using the fault tree method. By the use of house events a single fault tree is constructed to represent the failure causes of each potential design to overcome the time consuming task of constructing a fault tree for each design investigated during the optimisation procedure. Once the fault tree has been constructed for the design in question it is converted to a BDD for analysis. A genetic algorithm is first employed to perform the system optimisation, where the practicality of this approach is demonstrated initially through application to a High-Integrity Protection System (HIPS) and subsequently a more complex Firewater Deluge System (FDS). An alternative optimisation scheme achieves the final design specification by solving a sequence of optimisation problems. Each of these problems are defined by assuming some form of the objective function and specifying a sub-region of the design space over which this function will be representative of the system unavailability. The thesis concludes with attention to various optimisation techniques, which possess features able to address difficulties in the optimisation of safety critical systems. Specifically, consideration is given to the use of a statistically designed experiment and a logical search approach

論理シミュレーションとハードウェア記述言語に関する研究

京都大学0048新制・論文博士工学博士乙第7496号論工博第2471号新制||工||842(附属図書館)UT51-91-E273(主査)教授 矢島 脩三, 教授 津田 孝夫, 教授 田丸 啓吉学位規則第5条第2項該当Kyoto UniversityDFA