Pranav Ashar – författare

Computer-aided design (CAD) of very large scale integrated (VLSI) circuits is concerned with the development of computer programs for the automated design and manufacture of ICs. Automated VLSI design is referred to as VLSI synthesis. Synthesis of VLSI circuits involves transforming a specification of circuit behavior into a mask-level layout which can be fabricated using VLSI manufacturing processes. Optimization strategies are vital in VLSI synthesis in order to meet desired specifications. However, the optimization problems encountered in VLSI synthesis are typically nondeterministic polynomial-time (NP)-complete or NP-hard. Therefore, solutions to the optimization problems incorporate heuristic strategies, the development of which requires a thorough understanding of the problem at hand. Thus, optimization-based VLSI synthesis has evolved into a rich and exciting area of research. Automata theory forms a cornerstone of digital VLSI system design. Sequential Logic Synthesis deals exclusively with finite automata theory and practice.The extensive use of finite state automata, finite state machines (FSMs) or simple sequential logic in VLSI circuits and the recent proliferation of CAD research in the area of FSM synthesis has prompted the writing of this book.

3. 2 Input Encoding Targeting Two-Level Logic . . . . . . . . 27 3. 2. 1 One-Hot Coding and Multiple-Valued Minimization 28 3. 2. 2 Input Constraints and Face Embedding 30 3. 3 Satisfying Encoding Constraints . . . . . . . 32 3. 3. 1 Definitions . . . . . . . . . . . . . . . 32 3. 3. 2 Column-Based Constraint Satisfaction 33 3. 3. 3 Row-Based Constraint Satisfaction . . 37 3. 3. 4 Constraint Satisfaction Using Dichotomies . 38 3. 3. 5 Simulated Annealing for Constraint Satisfaction 41 3. 4 Input Encoding Targeting Multilevel Logic. . 43 3. 4. 1 Kernels and Kernel Intersections . . . 44 3. 4. 2 Kernels and Multiple-Valued Variables 46 3. 4. 3 Multiple-Valued Factorization. . . . . 48 3. 4. 4 Size Estimation in Algebraic Decomposition . 53 3. 4. 5 The Encoding Step . 54 3. 5 Conclusion . . . . . . . . . 55 4 Encoding of Symbolic Outputs 57 4. 1 Heuristic Output Encoding Targeting Two-Level Logic. 59 4. 1. 1 Dominance Relations. . . . . . . . . . . . . . . . 59 4. 1. 2 Output Encoding bythe Derivation of Dominance Relations . . . . . . . . . . . . . . . . . . . . . 60 . . 4. 1. 3 Heuristics to Minimize the Number of Encoding Bits . . . . . . . . . . . . 64 4. 1. 4 Disjunctive Relationships . . . . . . . . . . . 65 4. 1. 5 Summary . . . . . . . . . . . . . . . . . . 66 . . 4. 2 Exact Output Encoding Targeting Two-Level Logic. 66 4. 2. 1 Generation of Generalized Prime Implicants . 68 4. 2. 2 Selecting a Minimum Encodeable Cover . . . 68 4. 2. 3 Dominance and Disjunctive Relationships to S- isfy Constraints . . . . . . . . . . . 70 4. 2. 4 Constructing the Optimized Cover 73 4. 2. 5 Correctness of the Procedure . . 73 4. 2. 6 Multiple Symbolic Outputs . . .