Chip layout method based on area minimization

Abstract

The invention discloses a chip layout method based on area minimization. The method comprises the following steps: converting an area minimization problem into a two-dimensional rectangular strip boxing problem; inputting module information and container information; the candidate length Lh of the module information is preliminarily screened by calculating the linear combination of the lengths of the module information, and the candidate length Lh is not smaller than the maximum width of the module information; establishing a one-dimensional continuous boxing problem model by the group of candidate lengths Lh, and solving to obtain a lower bound of the group of candidate lengths Lh and a solution set of the positions of the group of modules along the Y axis; screening the candidate length Lh again to obtain a minimum candidate length Lh1, and detecting the legality of the x value of the module information; detecting whether the result is qualified or not by adopting an x-check algorithm; according to the chip layout method based on area minimization, the two-dimensional module arrangement problem is relaxed into the one-dimensional module arrangement problem, and a high-efficiency accurate solving algorithm is provided for the area minimization problem in the chip layout design.

Description

Technical Field

[0001] The present invention relates to the technical field of chip design, and in particular to a chip layout method based on area minimization. Background Art

[0002] With the rapid development of integrated circuit technology, the consumer electronics market is in a period of vigorous development, and the demand for high performance, low power consumption, multi-function, ultra-high speed, portability, long life and fast design cycle is becoming more and more urgent. In this fiercely competitive market, integrated circuit design is becoming more and more important, and the chip layout planning problem is extremely urgent.

[0003] One of the current trends in the semiconductor industry is to reduce the area of ​​integrated circuits by processing more digital logic in a shrinking area. In the physical design process of digital chips, area optimization is usually required to reduce manufacturing costs, improve performance, and reduce power consumption. For example, by rearranging the layout of logic elements, the wiring length of the circuit can be reduced, thereby reducing area and power consumption. This type of problem is called the area minimization problem in chip layout design. However, due to the complexity of the problem and the limitations of the manufacturing process, logic rearrangement requires efficient layout planning algorithms and tools to achieve the best optimization of circuit layout. The complexity of these tools often imposes certain restrictions on applications. At the same time, considering that the objective function of the area minimization problem usually exhibits nonlinear characteristics, it further increases the difficulty of solving the problem. To address these challenges, we propose an efficient and exact solution algorithm. By enumerating all possible sizes of one dimension, the area minimization problem in chip layout design can be converted into multiple two-dimensional rectangular strip packing problems (2DSPPs), in which the chip length is fixed and the goal is to place all modules on the chip to minimize the chip width. Since there are many optional chip lengths, how to reduce the number of chip candidate lengths through screening, thereby reducing the number of calls to the two-dimensional rectangular strip packing algorithm, and how to quickly solve the two-dimensional rectangular strip packing problem are key factors affecting the algorithm performance. Summary of the invention

[0004] The purpose of the present invention is to propose a chip layout method based on area minimization. By relaxing the two-dimensional module arrangement problem into a one-dimensional module arrangement problem, an efficient and accurate solution algorithm is proposed for the area minimization problem in chip layout design. Through this algorithm, an efficient layout plan is obtained, providing a practical and feasible solution for chip design.

[0005] To achieve this purpose, the present invention adopts the following technical solution: a chip layout method based on area minimization, comprising the following steps:

[0006] Problem conversion: Convert the area minimization problem into a two-dimensional rectangular strip packing problem;

[0007] Input data: input multiple module information and one container information;

[0008] Preliminary screening: By calculating the linear combination of the lengths of the module information, the candidate lengths L of the module information are h Perform preliminary screening, candidate length L h Not less than the maximum width of the module information;

[0009] Calculate the lower bound of the candidate length: a set of candidate lengths L h Establish a one-dimensional continuous packing problem model and obtain a set of candidate lengths L by solving h The lower bound of and a set of solutions for the positions of each module along the Y axis;

[0010] Screen again: set the candidate length L h Perform another screening to obtain the minimum candidate length L h1 , and check the legitimacy of the x value of the module information;

[0011] Qualification: Use the x-check algorithm to check whether the result is qualified. If the test result is qualified, the output result is the optimal height L h2 ; If the test result is unqualified, the current candidate length is L h1 The corresponding one-dimensional continuous packing problem model adds the cut constraint and returns to the step of calculating the lower bound of the candidate length.

[0012] Preferably, in the preliminary screening step, the following steps are specifically included: based on the linear combination of the width of the module information, a set of candidate lengths L is obtained: h , obtain the maximum width of the module information by comparing the width of the module information; remove a set of candidate lengths L h The candidate length L is smaller than the maximum width of the module information h .

[0013] Preferably, in the step of calculating the lower bound of the candidate length, the two-dimensional rectangular strip packing problem is relaxed into a one-dimensional continuous packing problem through problem conversion and constraint relaxation, and a one-dimensional continuous packing problem model is established to solve each candidate length L h The lower bound of ; specifically includes:

[0014] Cut each module information horizontally into L h The length of the strip is L h =1,2,…,y,…,L h , find the optimal solution for the utilization rate of each strip, and the calculation formula is:

[0015] minW;

[0016]

[0017] where t iy is a variable indicating whether the lower left corner of module i is on the yth strip. If so, t iy =1, otherwise, t iy =0; w i is the width of the target module i; W represents the total width of the solution; Y 0 represents the set of points where the module can be placed along the y-axis; P represents the set of all modules; h i represents the height of module i; q represents the number of rows; Indicates whether the lower left corner of module i is in On a strip, if yes, then otherwise, represents the position of module i on the y-axis obtained by solving the relaxed model, It is obtained by dynamically solving the relaxed model and does not exist in the initial stage; n represents the total number of modules.

[0018] Preferably, the specific steps of relaxing the two-dimensional rectangular strip packing problem into a one-dimensional continuous packing problem include:

[0019] Step S1: solving and obtaining the optimal solution of the one-dimensional continuous packing problem model;

[0020] Step S2: based on the one-dimensional continuous packing problem model, the module y coordinate of the optimal solution is obtained, and the legal x coordinate of the module is calculated by calling the x-check algorithm;

[0021] Step S3: If the x-check algorithm finds a legal x value, then the y value obtained by the one-dimensional continuous bin packing problem model and the found x value constitute the optimal legal solution to the two-dimensional rectangular strip bin packing problem;

[0022] Step S4: Otherwise, find the minimum subset of modules that cannot be legally placed, and strengthen the one-dimensional continuous packing problem model by adding cut constraints;

[0023] Step S5: Repeat steps S1 to S4 to solve the problem, and loop until the optimal legal solution to the two-dimensional rectangular strip packing problem is found.

[0024] Preferably, in the second screening step, each candidate length L h and the corresponding candidate length L h Multiply the lower bound of and select the candidate length L with the smallest product h1 , detection is done by candidate length L h1 Determine the legality of the x-values ​​of the solution set along the y-axis.

[0025] Preferably, the specific formula of the x-check algorithm is:

[0026] x i +(1-z ij )M≥x j +l j ;

[0027] y i +w i ≥y j ;

[0028] y j +w j ≥y i ;

[0029]

[0030] Among them, M represents a very large number; z ij is a variable indicating whether the target module i is on the right side of module j. If yes, it is 1, otherwise it is 0; x i Indicates the placement point of target module i; x j represents the possible placement point of target module j; w i Indicates the width of module i; w j Indicates the width of module j; y i represents the position of module i on the y-axis obtained by solving the relaxed model; y j represents the position of module j on the y-axis obtained by solving the relaxed model; l i Indicates the length of module i; l j represents the length of module j; L represents the candidate length; P represents the set of all modules.

[0031] Preferably, the specific formula for adding the cut constraint is:

[0032]

[0033] in represents the position of module i on the y-axis obtained by solving the relaxed model; represents an optimal solution obtained by the relaxed model; n represents the total number of modules.

[0034] The beneficial effects of a technical solution of the present invention are as follows: for the area minimization problem in chip layout design, an accurate solution algorithm for minimizing the area of ​​a two-dimensional rectangular package based on macroscopic transformation decomposition is proposed, by converting the area minimization problem into several height minimization problems; secondly, through problem conversion and constraint relaxation, the two-dimensional rectangular strip packing problem is relaxed into a one-dimensional continuous packing problem, and the accurate solution algorithm for the height minimization problem based on the decomposition idea can accurately obtain the result of minimizing the area of ​​a two-dimensional rectangular package; finally, in order to improve the efficiency of the algorithm and maximize the use of computing resources, the best adaptation priority strategy is designed to solve and accelerate. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 is a schematic diagram of minimizing the arrangement of modules in one embodiment of the present invention;

[0036] Figure 2 This is a schematic diagram of an algorithm flow for solving an area minimization problem according to an embodiment of the present invention;

[0037] Figure 3 is a schematic diagram of a height minimization problem according to an embodiment of the present invention;

[0038] Figure 4 It is a schematic diagram of constraint relaxation according to an embodiment of the present invention. DETAILED DESCRIPTION

[0039] The technical solution of the present invention is further described below with reference to the accompanying drawings and through specific implementation methods.

[0040] The embodiments of the present invention are described in detail below. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and should not be construed as limiting the present invention.

[0041] In the description of the present invention, unless otherwise specified, "plurality" means two or more.

[0042] For those skilled in the art, the specific meanings of the terms in the present invention can be understood in specific situations. In this embodiment, the original problem mentioned refers to the two-dimensional rectangular strip packing problem.

[0043] See also Figures 1 to 4 As shown, a chip layout method based on area minimization includes the following steps:

[0044] Problem conversion: The nonlinear characteristics of the area minimization problem greatly increase the difficulty of solving the problem. By enumerating all possible sizes of one dimension, the area minimization problem is converted into a two-dimensional rectangular strip packing problem;

[0045] Input data: input multiple module information and one container information;

[0046] The input module information includes: n size w i ×h i The container information includes a rectangular container, and the rectangular container is assumed to have a variable size. i ×h i Rectangles represent different modules in the chip, and rectangular containers represent chips. All rectangles are required to be placed in the container through orthogonal packaging, while considering the following restrictions: rectangles are not allowed to overlap, rectangles can be rotated 90°, and the principle of non-one-size-fits-all is met. The goal is to obtain the area of ​​a fixed container (W c ×H c ), that is, we need to find a container with the smallest area to hold all rectangles. Without loss of generality, we assume that the sizes of all rectangles are integers. The area minimization problem in chip layout design can be transformed into a two-dimensional rectangular package area minimization problem.

[0047] Preliminary screening: By calculating the linear combination of the lengths of the module information, the candidate lengths L of the module information are h Perform preliminary screening, candidate length L h Not less than the maximum width of the module information;

[0048] After converting the area minimization problem in chip layout design into a two-dimensional rectangular package area minimization problem, the chip length is fixed and the goal is to place all modules on the chip so that the total width of the container is minimized. By calculating the candidate length L h , converting the area minimization problem into several width minimization problems, namely the two-dimensional rectangular strip packing problem.

[0049] Calculate the lower bound of the candidate length: a set of candidate lengths L h Establish a one-dimensional continuous packing problem model and update each candidate length L h The lower bound of ; establish a one-dimensional continuous packing problem model and solve the model to determine each candidate length L h The lower bound width and a set of solutions for the positions of each module along the Y axis; a set of solutions for the positions of each module along the Y axis means that one candidate length corresponds to a solution set of one module, so solve a set of L h The established one-dimensional continuous packing problem model will obtain a set of solutions.

[0050] Screen again: Use the best adaptation priority strategy: Specifically, the candidate length L h Perform another screening to obtain the minimum candidate length L h1 , and check the legitimacy of the x value of the module information. Verify that the candidate length L h1Whether the solution set obtained by the established one-dimensional continuous packing problem model meets the legality of the x value. The solution set of the one-dimensional continuous packing problem model only assumes that the Y value is legal. Therefore, it is also necessary to determine whether the x value corresponding to the solution set is legal.

[0051] Qualification: Use the x-check algorithm to check whether the result is qualified. If the test result is qualified, the output result is the optimal height L h2 ; If the test result is unqualified, the current candidate length is L h1 The corresponding one-dimensional continuous packing problem model adds the cut constraint and returns to the step of calculating the lower bound of the candidate length.

[0052] After the problem is converted, multiple two-dimensional rectangular strip packing problems need to be solved. If each two-dimensional rectangular strip packing problem is solved in turn in a fixed order, too many computing resources may be spent on two-dimensional rectangular strip packing problems that do not have an optimal solution, thereby affecting the overall solution efficiency of the algorithm. The existing methods cannot accurately determine in advance which two-dimensional rectangular strip packing problem has the optimal solution to the original problem, and it is also difficult to accurately determine which two-dimensional rectangular strip packing problem is more likely to have an optimal solution. Therefore, this project proposes a best-fit iteration method to improve the solution efficiency of the algorithm. The method proposed by the present invention is that in each iteration process, a two-dimensional rectangular strip packing problem with the smallest product of length and lower bound will be selected for solution, but the solution will end when the lower bound of the two-dimensional rectangular strip packing problem is improved and enter the next iteration. The specific steps are as follows: First, for each candidate length corresponding to the two-dimensional rectangular strip packing problem, calculate the optimal solution of its corresponding relaxed problem, the one-dimensional continuous packing problem, which is the lower bound of the two-dimensional rectangular strip packing problem; in each iteration, select the two-dimensional rectangular strip packing problem with the smallest product of the length and the lower bound, that is, the original problem target, and call the x-check algorithm to find a legal x-coordinate axis for its relaxed one-dimensional continuous packing problem; if a legal x value is found, the optimal solution of the two-dimensional rectangular strip packing problem is found, and the product of the optimal solution and the length is also the optimal solution of the original area minimization problem, and the algorithm ends; otherwise, the one-dimensional continuous packing problem model is strengthened by adding cuts, thereby improving the lower bound of the two-dimensional rectangular strip packing problem; repeat the above iterations until a legal solution to a two-dimensional rectangular strip packing problem is found in a certain iteration process, and the algorithm ends.

[0053] The present invention relaxes the two-dimensional module arrangement problem into a one-dimensional module arrangement problem, and proposes a highly efficient and accurate solution algorithm for the area minimization problem in chip layout design. Through this algorithm, an efficient layout solution is obtained, providing a practical and feasible solution for chip design.

[0054] The present invention proposes an accurate solution algorithm for minimizing the area of ​​a two-dimensional rectangular package based on macroscopic transformation decomposition for the area minimization problem in chip layout design. The area minimization problem is converted into several height minimization problems. Secondly, the two-dimensional rectangular strip packing problem is relaxed into a one-dimensional continuous packing problem through problem conversion and constraint relaxation. The accurate solution algorithm for the height minimization problem based on the decomposition idea is used to obtain the result of minimizing the area of ​​the two-dimensional rectangular package. Finally, in order to improve the efficiency of the algorithm and maximize the use of computing resources, the best adaptation priority strategy is designed to solve and accelerate the problem.

[0055] Specifically, in the preliminary screening step, it specifically includes: based on the linear combination of the width of the module information, a set of candidate lengths L is obtained h , obtain the maximum width of the module information by comparing the width of the module information; remove a set of candidate lengths L h The candidate length L is smaller than the maximum width of the module information h To ensure that all modules can be packed in a length of L h The initial screening is to remove L that is smaller than the width of the maximum module information. h , because all modules must be packed into a candidate with length L h So the candidate length L h The length must be greater than or equal to the maximum width of the module information.

[0056] Specifically, in the step of finding the lower bound of the candidate length, the two-dimensional rectangular strip packing problem is relaxed into a one-dimensional continuous packing problem through problem conversion and constraint relaxation. A one-dimensional continuous packing problem model is established to solve the problem of each candidate length L. h The lower bound of ; specifically includes:

[0057] Cut each module information horizontally into L h The length of the strip is L h =1,2,…,y,…,L h , find the optimal solution for the utilization rate of each strip, and the calculation formula is:

[0058]

[0059] where t iy is a variable indicating whether the lower left corner of module i is on the yth strip. If so, t iy =1, otherwise, t iy =0; w i is the width of the target module i; W represents the total width of the solution; Y 0 represents the set of points where the module can be placed along the y-axis; P represents the set of all modules; h i represents the height of module i; q represents the number of rows; Indicates whether the lower left corner of module i is in On a strip, if yes, then otherwise, represents the position of module i on the y-axis obtained by solving the relaxed model, It is obtained by dynamically solving the relaxed model and does not exist in the initial stage; n represents the total number of modules.

[0060] The second equation indicates that all modules must be cut; the third equation indicates that the total width of the target block covering the qth row of the strip does not exceed the available width of the strip; the fourth equation indicates that the one-dimensional continuous packing problem is strengthened by adding cuts when the x-check detection is illegal. The y value of at least one module in the subset cannot be the y value obtained by the last solution; the fifth equation indicates that t iy is a 0-1 variable.

[0061] After establishing the mathematical programming model of the relaxed one-dimensional continuous packing problem, a third-party solver is called to solve the one-dimensional continuous packing problem model to obtain an optimal solution to the relaxed problem, that is, the y coordinates of the target block arrangement, and then the optimal solution is verified by the x-check algorithm, that is, assigning x coordinates to the target blocks to determine whether there are non-overlapping x coordinates between target blocks. The lower bound corresponding to each candidate length can be solved by calculating the optimal solution of the corresponding relaxed one-dimensional continuous packing problem, which is the lower bound of the problem. By removing the x variable from the original problem, the one-dimensional continuous packing problem model can be obtained.

[0062] Preferably, the specific steps of relaxing the two-dimensional rectangular strip packing problem into a one-dimensional continuous packing problem include:

[0063] Step S1: solving and obtaining the optimal solution of the one-dimensional continuous packing problem model;

[0064] Step S2: based on the one-dimensional continuous packing problem model, the module y coordinate of the optimal solution is obtained, and the legal x coordinate of the module is calculated by calling the x-check algorithm;

[0065] Step S3: If the x-check algorithm finds a legal x value, then the y value obtained by the one-dimensional continuous bin packing problem model and the found x value constitute the optimal legal solution to the two-dimensional rectangular strip bin packing problem;

[0066] Step S4: Otherwise, find the minimum subset of modules that cannot be legally placed, and strengthen the one-dimensional continuous packing problem model by adding cut constraints;

[0067] Step S5: Repeat steps S1 to S4 to solve the problem, and loop until the optimal legal solution to the two-dimensional rectangular strip packing problem is found.

[0068] Through problem transformation and constraint relaxation, the x variable and the overlapping constraints in the x direction are removed, and the two-dimensional rectangular strip packing problem is relaxed into a one-dimensional continuous packing problem. Then, the legal solution of the two-dimensional rectangular strip packing problem is obtained by continuously strengthening the one-dimensional continuous packing problem.

[0069] In the second screening step, the best adaptation priority strategy is adopted, which includes: h and the corresponding candidate length L h Multiply the lower bound of and select the candidate length L with the smallest product h1 , detection is done by candidate length L h1 Determine the legality of the x-values ​​of the solution set along the y-axis.

[0070] Specifically, the specific formula of the x-check algorithm is:

[0071] x i +(1-z ij )M≥x j +l j ;

[0072] y i +w i ≥y j ;

[0073] y j +w j ≥y i ;

[0074]

[0075] Among them, M represents a very large number, specifically a very large number. When mathematical modeling is performed, the variable M can be set to a very large number to ensure that the inequality holds; ij is a variable indicating whether the target module i is on the right side of module j. If yes, it is 1, otherwise it is 0; x i Indicates the placement point of target module i; x j represents the possible placement point of target module j; w i Indicates the width of module i; w j Indicates the width of module j; y i represents the position of module i on the y-axis obtained by solving the relaxed model; y j represents the position of module j on the y-axis obtained by solving the relaxed model; l i Indicates the length of module i; l jrepresents the length of module j; L represents the candidate length; P represents the set of all modules.

[0076] The x-check algorithm mainly checks whether the solution obtained from the relaxed one-dimensional continuous packing problem can produce a legal module x-coordinate solution. If the test meets the requirements, it can be directly output as the optimal solution of the original problem. If it does not meet the requirements, the current y infeasible solution needs to be added to the relaxed problem and continue iterating.

[0077] The first, second and third formulas are used to test the j ,w j +w j ] to ensure that the target blocks do not overlap.

[0078] Since the relaxation problem is obtained by dividing the two-dimensional rectangular strip packing problem into several sub-problems, the optimal solution of the relaxation problem is to ensure that each length is occupied to the maximum extent. Compared with the two-dimensional rectangular strip packing problem, the constraints of the relaxation problem are weaker and there is a lack of constraints on the x-axis position. Therefore, if the optimal solution of the relaxation problem can meet the constraints of the two-dimensional rectangular strip packing problem, it can be determined that this solution is the optimal solution to the two-dimensional rectangular strip packing problem.

[0079] Preferably, the specific formula for adding the cut constraint is:

[0080]

[0081] in represents the position of module i on the y-axis obtained by solving the relaxed model; represents an optimal solution obtained by the relaxed model; n represents the total number of modules.

[0082] When solving the one-dimensional continuous packing problem model, if the solution obtained does not meet the requirements, you can add an additional constraint to the basic model to restrict the problem, and then continue to solve to verify whether a legal solution is obtained. For example, when the x-check test is illegal, add a cut constraint to the one-dimensional continuous packing problem model, and then continue to solve. If the test is legal, terminate the solution.

[0083] In the description of this specification, the description with reference to the terms "embodiment", "example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0084] The technical principle of the present invention is described above in conjunction with specific embodiments. These descriptions are only for explaining the principle of the present invention and cannot be interpreted as limiting the scope of protection of the present invention in any way. Based on the explanations herein, those skilled in the art can associate other specific implementations of the present invention without paying creative labor, and these methods will fall within the scope of protection of the present invention.

Claims

1. A chip layout method based on area minimization, characterized in that: The steps include: Problem conversion: Convert the area minimization problem into a two-dimensional rectangular strip packing problem; Input data: input multiple module information and one container information; Preliminary screening: By calculating the linear combination of the lengths of the module information, the candidate lengths L of the module information are h Perform preliminary screening, candidate length L h Not less than the maximum width of the module information; Calculate the lower bound of the candidate length: a set of candidate lengths L h Establish a one-dimensional continuous packing problem model and obtain a set of candidate lengths L by solving h The lower bound of and a set of solutions for the positions of each module along the Y axis; Screen again: set the candidate length L h Perform another screening to obtain the minimum candidate length L h1 , and check the legitimacy of the x value of the module information; Qualification: Use the x-check algorithm to check whether the result is qualified. If the test result is qualified, the output result is the optimal height L h2 ; If the test result is unqualified, the current candidate length is L h1 The corresponding one-dimensional continuous packing problem model adds the cut constraint and returns to the step of calculating the lower bound of the candidate length.

2. The chip layout method based on area minimization according to claim 1, characterized in that: In the preliminary screening step, specifically including: based on the linear combination of the width of the module information, a set of candidate lengths L is obtained h , obtain the maximum width of the module information by comparing the width of the module information; remove a set of candidate lengths L h The candidate length L is smaller than the maximum width of the module information h .

3. The chip layout method based on area minimization according to claim 1, characterized in that: In the step of calculating the lower bound of the candidate length, the two-dimensional rectangular strip packing problem is relaxed into a one-dimensional continuous packing problem through problem conversion and constraint relaxation. A one-dimensional continuous packing problem model is established to solve each candidate length L. h The lower bound of ; specifically includes: Cut each module information horizontally into L h The length of the strip is L h =1,2,…,y,…,L h , find the optimal solution for the utilization rate of each strip, and the calculation formula is: min W; t iy ={0,1},y∈Y0,i∈P; where t iy is a variable indicating whether the lower left corner of module i is on the yth strip. If so, t iy =1, otherwise, t iy =0; w i is the width of the target module i; W represents the total width of the solution; Y0 represents the set of points where the module can be placed along the y-axis; P represents the set of all modules; h i represents the height of module i; q represents the number of rows; Indicates whether the lower left corner of module i is in On a strip, if yes, then otherwise, represents the position of module i on the y-axis obtained by solving the relaxed model, It is obtained by dynamically solving the relaxed model and does not exist in the initial stage; n represents the total number of modules.

4. The chip layout method based on area minimization according to claim 3, characterized in that: The specific steps to relax the two-dimensional rectangular strip packing problem into a one-dimensional continuous packing problem include: Step S1: solving and obtaining the optimal solution of the one-dimensional continuous packing problem model; Step S2: based on the one-dimensional continuous packing problem model, the module y coordinate of the optimal solution is obtained, and the legal x coordinate of the module is calculated by calling the x-check algorithm; Step S3: If the x-check algorithm finds a legal x value, then the y value obtained by the one-dimensional continuous bin packing problem model and the found x value constitute the optimal legal solution to the two-dimensional rectangular strip bin packing problem; Step S4: Otherwise, find the minimum subset of modules that cannot be legally placed, and strengthen the one-dimensional continuous packing problem model by adding cut constraints; Step S5: Repeat steps S1 to S4 to solve the problem, and loop until the optimal legal solution to the two-dimensional rectangular strip packing problem is found.

5. The chip layout method based on area minimization according to claim 1, characterized in that: In the second screening step, each candidate length L h and the corresponding candidate length L h Multiply the lower bound of and select the candidate length L with the smallest product h1 , detection is done by candidate length L h1 Determine the legality of the x-values ​​of the solution set along the y-axis.

6. The chip layout method based on area minimization according to claim 1, characterized in that: The specific formula of the x-check algorithm is: x i +(1-z ij )M≥x j +l j ; y i +w i ≥y j ; y j +w j ≥y i ; Among them, M represents a very large number; z ij is a variable indicating whether the target module i is on the right side of module j. If yes, it is 1, otherwise it is 0; x i Indicates the placement point of target module i; x j represents the possible placement point of target module j; w i Indicates the width of module i; w j Indicates the width of module j; y i represents the position of module i on the y-axis obtained by solving the relaxed model; y j represents the position of module j on the y-axis obtained by solving the relaxed model; l i Indicates the length of module i; l j represents the length of module j; L represents the candidate length; P represents the set of all modules.

7. The chip layout method based on area minimization according to claim 1, characterized in that: The specific formula for adding a cut constraint is: in represents the position of module i on the y-axis obtained by solving the relaxed model; represents an optimal solution obtained by the relaxed model; n represents the total number of modules.

Images