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Three-value fprm circuit area and delay optimization method using particle swarm optimization

A particle swarm algorithm and circuit area technology, applied in multi-objective optimization, calculation, calculation model and other directions, can solve the problem of difficult to obtain the optimal solution in the concave area of ​​the front curve, different, poor optimization effect, etc.

Active Publication Date: 2020-12-22
NINGBO UNIV
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  • Application Information

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Problems solved by technology

However, there are several problems in the weighting coefficient method: (1) the weighting coefficient cannot be determined, and the final result may be different if different weighting coefficients are set; (2) the weighting coefficient is sensitive to the shape of the Pareto frontier curve, and it is difficult to obtain the concave area of ​​the frontier curve The optimal solution; (3) The selection of weight coefficients requires prior knowledge, but these prior knowledge are often unknown
However, due to the strong pulling effect of the global optimal particle in the existing particle swarm optimization algorithm, the algorithm is prone to premature convergence, and the global optimal polarity finally searched by the particle swarm optimization algorithm is not the optimal polarity of the three-valued FPRM circuit. Optimum polarity, less optimized

Method used

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  • Three-value fprm circuit area and delay optimization method using particle swarm optimization
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  • Three-value fprm circuit area and delay optimization method using particle swarm optimization

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Embodiment 1

[0075] Embodiment one: a kind of ternary FPRM circuit area and delay optimization method utilizing particle swarm optimization algorithm, comprising the following steps:

[0076] ①Establish the area estimation model and delay estimation model of the ternary FPRM circuit under p polarity:

[0077] ①-1 Express the ternary FPRM circuit under p polarity with the ternary FPRM logic expression as:

[0078]

[0079] Among them, n is the function f p (x n-1 ,x n-2 ,...,x 0 ) the number of input variables; x n-1 ,x n-2 ,...,x 0 for the function f p (x n-1 ,x n-2 ,...,x 0 ) of n input variables; ⊕Σ is the modulo 3 addition operation symbol; b i is the AND coefficient, and b i ∈{0,1,2}; i is the ordinal number of AND item, i=0,1,2,...,3 n -1, i can be expressed as i in ternary n-1 i n-2 …i 0 , i j ∈{0,1,2}, j is an integer greater than or equal to 0 and less than or equal to n-1; p is the polarity of the ternary FPRM circuit, and p can be expressed as p in ternary n-...

Embodiment 2

[0126] Embodiment two: this embodiment is basically the same as embodiment one, the only difference is that in this embodiment, the specific process of calculating the crowding distance of the position of each particle with the lowest number of non-dominated ranks in the initial state in Step3 is:

[0127] Step3-1. Record the number of particles with the lowest non-dominated rank number as size(rep);

[0128] Step3-2. According to the size of the area of ​​the ternary FPRM circuit under the polarity corresponding to the position of each particle with the lowest non-dominated level number, sort the particles with the lowest non-dominated level number in ascending order of area; the initial state The crowding distance of the particle with the lowest non-dominated rank number ranked a is recorded as distance a (0), a=1, 2, ..., size(rep);

[0129] Step3-3. Make the crowding distance distance of the particle with the lowest number of non-dominated levels ranked first 1 (0)=10000...

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Abstract

The invention discloses a particle swarm algorithm-utilized three-valued FPRM circuit area and delay optimization method. According to the optimization method, a particle population is divided into two teams: a first particle sub-population and a second particle sub-population, and particles in the two teams are respectively compared, wherein relatively bad particles are updated to the relativelygood particles, so that the phenomenon of premature convergence of the algorithm is avoided; and meanwhile, a variation mechanism is imported to ensure that the population particles can jump out of asearch range of a locally optimal solution, so that the optimization performance of the algorithm is improved. The method has the advantages that an optimal polarity set of three-valued FPRM circuitscan be searched so that the optimization effect is good, and simulation test is carried out through 13 Benchmark circuits; and experiment results prove that the method has better optimization efficiency and robustness when being compared with optimal polarities searched by a DPSO algorithm and an MODPSO algorithm.

Description

technical field [0001] The invention relates to a method for optimizing a ternary FPRM circuit, in particular to a method for optimizing the area and time delay of a ternary FPRM circuit using a particle swarm algorithm. Background technique [0002] Boolean logic and RM logic are two main manifestations of ternary logic functions. Compared with traditional Boolean logic circuits, circuits based on RM logic (such as arithmetic logic circuits and parity check circuits, etc.) have obvious advantages in terms of area, power consumption, speed and testability. Among them, the three-valued FPRM function expression is a common logical expression in RM logic. There are 3 RM logistic functions of n variables n A three-valued FPRM function expression, each expression is different, and the corresponding circuit area and delay are also different. Therefore, polarity has an important impact on performance indicators such as circuit area and delay. [0003] The optimal polarity searc...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F30/337G06F30/398G06N3/00G06F111/06
CPCG06N3/006G06F30/327G06F30/367
Inventor 汪鹏君王铭波符强张会红
Owner NINGBO UNIV