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**1 - 6**of**6**### Control Intensive Digital System Synthesis

"... Most of digital synthesis tasks are known to belong to NP-complexity class. Practical tasks often have hidden properties which allow to reduce originally enormous solution space. Combining calculus power of computers and designer 's experience it is possible to #nd near-optimal solution to synt ..."

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Most of digital synthesis tasks are known to belong to NP-complexity class. Practical tasks often have hidden properties which allow to reduce originally enormous solution space. Combining calculus power of computers and designer 's experience it is possible to #nd near-optimal solution to synthesis problem within restricted time limit. Two of VLSI synthesis subtasks are considered in the thesis. The #rst part of the thesis is devoted to HW#SW codesign, based on one and half year studies and research period at the Department of Electronic System Design of Royal Institute of Technology, Sweden. An overview of contemporary codesign techniques is provided and development of one research codesign toolkit AKKA is considered and evaluated. Main emphasis is on multi-level simulation methodology and elaboration of prototyping architectures on Xilinx FPGA chips. Also, future vision of improvements of the toolkit properties is given. The second part of the thesis is devoted to one of register-transfer level synthesis subtask - the controller decomposition using iterative methods. This work was done with several interrupts in Tallinn Technical University, partially in Darmstadt Technical University, during the years 1984-1994. First, the method using of bulk data sorting for partitioning and clustering of FSM descriptions is investigated. Second, stochastic optimization algorithms like simulated annealing and Kohonen's self-organization method are elaborated and evaluated. This part is strongly in#uenced by the partition pair algebra. The following information is presented in the appendix : the de#nitions of used textual formats, table of used Logic Synthesis FSM benchmarks and examples of FSM synthesis from VHDL. v Res#umee Valdavalt on digitaals#usteemide s#unteesi # ulesa...

### Approaches to the Input-Output Encoding Problem in Boolean Decomposition

, 1996

"... Abstract So far, very little has been published in the literature on the encoding problem that occurs in functional (Curtis, Roth-Karp) decomposition. In particular, the encoding techniques used to optimize the decomposition of functions for this problem have tried to optimize only the predecessor o ..."

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Abstract So far, very little has been published in the literature on the encoding problem that occurs in functional (Curtis, Roth-Karp) decomposition. In particular, the encoding techniques used to optimize the decomposition of functions for this problem have tried to optimize only the predecessor or only the successor logic, but not both concurrently. This report presents several approaches to the input-output &quot;Symbol Encoding Problem &quot; that occurs in the decomposition of Boolean functions. We show new methods for encoding, that attempt to optimize concurrently both the predecessor logic and the successor logic.

### A Parallel State Assignment Algorithm for Finite State Machines

"... Abstract. This paper summarizes the design and implementation of a parallel algorithm for state assignment of large Finite State Machines (FSMs). High performance CAD tools are necessary to overcome the computational complexity involved in the optimization of large sequential circuits. FSMs constitu ..."

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Abstract. This paper summarizes the design and implementation of a parallel algorithm for state assignment of large Finite State Machines (FSMs). High performance CAD tools are necessary to overcome the computational complexity involved in the optimization of large sequential circuits. FSMs constitute an important class of logic circuits, and state assignment is one of the key steps in combinational logic optimization. The SMP-based parallel algorithm – based on the sequential program JEDI targeting multilevel logic implementation – scales nearly linearly with the number of processors for FSMs of varying problem sizes chosen from standard benchmark suites while attaining quality of results comparable to the best sequential algorithms. 1

### Functional Decomposition of Composite Finite State Machines

"... . Many of the multiway general decompositions of finite state machines (FSMs) proposed in the past are concerned with the cost reduction of the eventual logic level implementation. In this paper we propose a new method of decomposing a new FSM model called Composite Finite State Machines (CFSMs), wh ..."

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. Many of the multiway general decompositions of finite state machines (FSMs) proposed in the past are concerned with the cost reduction of the eventual logic level implementation. In this paper we propose a new method of decomposing a new FSM model called Composite Finite State Machines (CFSMs), which is ideal for use in a microprocessor based system design environment. Our algorithm partitions the CFSM of the design functionality into a set of interacting CFSMs such that the partitioned CFSMs represent the different sub-functions of the design specification. Unlike existing FSM decomposition schemes, our algorithm is bottom-up and is able to determine suitable devices from a design library to implement the partitioned sub-functions. It is an extension of the behavioural mapping procedure proposed in [12] which addressed the implementability question for a single design function by mapping to a particular device, whereas our algorithm performs a behavioural mapping between a design fu...

### Symbolic Two-Dimensional Minimization of Strongly Unspecied Finite State Machines.

"... Abstract | A generalization of the classical state minimization problem for Finite State Machine (FSM) is proposed and discussed. In contrast to classical state minimization algorithms that minimize in one dimension (states), our algo-rithmminimizes the FSM in two dimensions: the numbers of both inp ..."

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Abstract | A generalization of the classical state minimization problem for Finite State Machine (FSM) is proposed and discussed. In contrast to classical state minimization algorithms that minimize in one dimension (states), our algo-rithmminimizes the FSM in two dimensions: the numbers of both input symbols and internal state symbols are minimized in an iterative sequence of input min-imization and state minimization procedures. This approach leads to an input decomposition of the FSM. A modied formulation of the state minimization problem is also introduced, and an eÆcient branch-and-bound program, FMINI, is presented. FMINI produces an exact minimum result for each component minimization process and a globally quasi-minimum solution to the entire two-dimensional FSM minimization problem. For some benchmarks, especially those with a high percentage of don't cares, as those that occur in Machine Learning, this approach produces a more optimum results than those produced by the state minimization alone. 2