Computer aided synthesis and optimisation of electronic logic circuits

In this thesis, a variety of algorithms for synthesis and optimisation of combinational and sequential logic circuits are developed. These algorithms could be part of new commercial EGAD package for future VLSI digital designs. The results show that considerable saving in components can be achieved resulting in simpler designs that are smaller, cheaper, consume less power and easier to test. The purpose of generating different sets of coefficients related to Reed Muller (RM) is that they contain different number of terms; therefore the minimum one can be selected to design the circuits with reduced gate count. To widen the search space and achieve better synthesis tools, representations of Mixed Polarity Reed Muller (MPRM), Mixed Polarity Dual Reed Muller (MPDRM), and Pseduo Kronecker Reed Muller (PKRO RM) expansions are investigated. Efficient and fast combinatorial techniques and algorithms are developed for the following: â Bidirectional conversion between MPRM/ MPDRM form and Fixed Polarity Reed Muller forms (FPRM)/Fixed Polarity Dual Reed Muller forms (FPDRM) form respectively. The main advantages for these techniques are their simplicity and suitability for single and multi output Boolean functions. â Computing the coefficients of any polarity related to PKRO_RM class starting from FPRM coefficients or Canonical Sum of Products (CSOP). â Computing the coefficients of any polarity related to MPRM/or MPDRM directly from standard form of CSOP/Canonical Product of sums (CPOS) Boolean functions, respectively. The proposed algorithms are efficient in terms of CPU time and can be used for large functions. For optimisation of combinational circuits, new techniques and algorithms based on algebraic techniques are developed which can be used to generate reduced RM expressions to design circuits in RM/DRM domain starting from FPRM/FPDRM, respectively. The outcome for these techniques is expansion in Reed Muller domain with minimal terms. The search space is 3`" Exclusive OR Sum of Product (ESOP)/or Exclusive NOR Product of Sums (ENPOS) expansions. Genetic Algorithms (GAs) are also developed to optimise combinational circuits to find optimal MPRM/MPDRM among 3° different polarities without the need to do exhaustive search. These algorithms are developed for completely and incompletely specified Boolean functions. The experimental results show that GA can find optimum solutions in a short time compared with long time required running exhaustive search in all the benchmarks tested. Multi Objective Genetic Algorithm (MOGA) is developed and implemented to determine the optimal state assignment which results in less area and power dissipation for completely and incompletely specified sequential circuits. The goal is to find the best assignments which reduce the component count and switching activity simultaneously. The experimental results show that saving in components and switching activity are achieved in most of the benchmarks tested compared with recently published research. All algorithms are implemented in C++.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Computer aided synthesis and optimisation of electronic logic circuits

In this thesis, a variety of algorithms for synthesis and optimisation of combinational and sequential logic circuits are developed. These algorithms could be part of new commercial EGAD package for future VLSI digital designs. The results show that considerable saving in components can be achieved resulting in simpler designs that are smaller, cheaper, consume less power and easier to test.The purpose of generating different sets of coefficients related to Reed Muller (RM) is that they contain different number of terms; therefore the minimum one can be selected to design the circuits with reduced gate count. To widen the search space and achieve better synthesis tools, representations of Mixed Polarity Reed Muller (MPRM), Mixed Polarity Dual Reed Muller (MPDRM), and Pseduo Kronecker Reed Muller (PKRO RM) expansions are investigated. Efficient and fast combinatorial techniques and algorithms are developed for the following:- Bidirectional conversion between MPRM/ MPDRM form and Fixed Polarity Reed Muller forms (FPRM)/Fixed Polarity Dual Reed Muller forms (FPDRM) form respectively. The main advantages for these techniques are their simplicity and suitability for single and multi output Boolean functions.- Computing the coefficients of any polarity related to PKRO_RM class starting from FPRM coefficients or Canonical Sum of Products (CSOP).- Computing the coefficients of any polarity related to MPRM/or MPDRM directly from standard form of CSOP/Canonical Product of sums (CPOS) Boolean functions, respectively. The proposed algorithms are efficient in terms of CPU time and can be used for large functions.For optimisation of combinational circuits, new techniques and algorithms based on algebraic techniques are developed which can be used to generate reduced RM expressions to design circuits in RM/DRM domain starting from FPRM/FPDRM, respectively. The outcome for these techniques is expansion in Reed Muller domain with minimal terms. The search space is 3`" Exclusive OR Sum of Product (ESOP)/or Exclusive NOR Product of Sums (ENPOS) expansions.Genetic Algorithms (GAs) are also developed to optimise combinational circuits to find optimal MPRM/MPDRM among 3° different polarities without the need to do exhaustive search. These algorithms are developed for completely and incompletely specified Boolean functions. The experimental results show that GA can find optimum solutions in a short time compared with long time required running exhaustive search in all the benchmarks tested.Multi Objective Genetic Algorithm (MOGA) is developed and implemented to determine the optimal state assignment which results in less area and power dissipation for completely and incompletely specified sequential circuits. The goal is to find the best assignments which reduce the component count and switching activity simultaneously. The experimental results show that saving in components and switchingactivity are achieved in most of the benchmarks tested compared with recentlypublished research. All algorithms are implemented in C++

An Elitist Non-Dominated Multi-Objective Genetic Algorithm Based Temperature Aware Circuit Synthesis

At sub-nanometre technology, temperature is one of the important design parameters to be taken care of during the target implementation for the circuit for its long term and reliable operation. High device package density leads to high power density that generates high temperatures. The temperature of a chip is directly proportional to the power density of the chip. So, the power density of a chip can be minimized to reduce the possibility of the high temperature generation. Temperature minimization approaches are generally addressed at the physical design level but it incurs high cooling cost. To reduce the cooling cost, the temperature minimization approaches can be addressed at the logic level. In this work, the Non-Dominated Sorting Genetic Algorithm-II (NSGA-II) based multi-objective heuristic approach is proposed to select the efficient input variable polarity of Mixed Polarity Reed-Muller (MPRM) expansion for simultaneous optimization of area, power, and temperature. A Pareto optimal solution set is obtained from the vast solution set of 3n (‘n’ is the number of input variables) different polarities of MPRM. Tabular technique is used for input polarity conversion from Sum-of-Product (SOP) form to MPRM form. Finally, using CADENCE and HotSpot tool absolute temperature, silicon area and power consumption of the synthesized circuits are calculated and are reported. The proposed algorithm saves around 76.20% silicon area, 29.09% power dissipation and reduces 17.06% peak temperature in comparison with the reported values in the literature

Logic synthesis and optimisation using Reed-Muller expansions

This thesis presents techniques and algorithms which may be employed to represent, generate and optimise particular categories of Exclusive-OR SumOf-Products (ESOP) forms. The work documented herein concentrates on two types of Reed-Muller (RM) expressions, namely, Fixed Polarity Reed-Muller (FPRM) expansions and KROnecker (KRO) expansions (a category of mixed polarity RM expansions). Initially, the theory of switching functions is comprehensively reviewed. This includes descriptions of various types of RM expansion and ESOP forms. The structure of Binary Decision Diagrams (BDDs) and Reed-Muller Universal Logic Module (RM-ULM) networks are also examined. Heuristic algorithms for deriving optimal (sub-optimal) FPRM expansions of Boolean functions are described. These algorithms are improved forms of an existing tabular technique [1]. Results are presented which illustrate the performance of these new minimisation methods when evaluated against selected existing techniques. An algorithm which may be employed to generate FPRM expansions from incompletely specified Boolean functions is also described. This technique introduces a means of determining the optimum allocation of the Boolean 'don't care' terms so as to derive equivalent minimal FPRM expansions. The tabular technique [1] is extended to allow the representation of KRO expansions. This new method may be employed to generate KRO expansions from either an initial incompletely specified Boolean function or a KRO expansion of different polarity. Additionally, it may be necessary to derive KRO expressions from Boolean Sum-Of-Products (SOP) forms where the product terms are not minterms. A technique is described which forms KRO expansions from disjoint SOP forms without first expanding the SOP expressions to minterm forms. Reed-Muller Binary Decision Diagrams (RMBDDs) are introduced as a graphical means of representing FPRM expansions. RMBDDs are analogous to the BDDs used to represent Boolean functions. Rules are detailed which allow the efficient representation of the initial FPRM expansions and an algorithm is presented which may be employed to determine an optimum (sub-optimum) variable ordering for the RMBDDs. The implementation of RMBDDs as RM-ULM networks is also examined. This thesis is concluded with a review of the algorithms and techniques developed during this research project. The value of these methods are discussed and suggestions are made as to how improved results could have been obtained. Additionally, areas for future work are proposed