Method and system for reducing search space of compilation option sequence and medium

Abstract

The invention discloses a method, a system and a medium for reducing a search space of a compilation option sequence, and the method comprises the following steps: starting programs in a single compilation option sampling template program set item by item, and obtaining speed-up ratio data relative to a preset compilation option sequence under each compilation option; calculating a harmonic average value, and screening out an effective compiling option set; constructing a two-dimensional option matrix, comparing acceleration effects of the binary option sequence, and establishing a compilation option relation directed graph; applying depth-first search to obtain a to-be-selected compilation option sequence set; and carrying out iterative optimization on the target program by adopting a genetic algorithm to generate an optimal compilation option sequence with the shortest running time. The method aims at solving the problem of low optimization efficiency caused by numerous compiling options and complex association of a compiler, the search space is reduced by establishing the compiling option relation model and generating the sequence set of the to-be-selected compiling options, the number of iterations of a genetic algorithm is reduced, and the compiling optimization overhead is remarkably reduced while it is guaranteed that program performance is optimized.

Description

Technical Field

[0001] The present invention belongs to the field of compilation optimization, and in particular relates to a method, system and medium for reducing the search space of compilation option sequences. Background Art

[0002] Compilers are essential tools for software development. They are responsible for converting intermediate and high-level computer languages ​​into executable low-level machine languages. They are fundamental and important. The quality of compiler code conversion has a significant impact on the final software performance. However, there are multiple technical barriers to selecting the optimal sequence of compilation options for a specific program. With the widespread use of large-scale applications and the diversified development of software and hardware platforms, the high overhead and poor results of traditional compilation optimization methods have become a major obstacle to program performance optimization. Existing studies have shown that preset compilation option sequences (such as ) is not very versatile and is difficult to adapt to a variety of program types or platforms. Summary of the invention

[0003] Technical problem to be solved by the present invention: In view of the above-mentioned problems in the prior art, a method, system and medium for reducing the search space of compilation option sequences are provided. The present invention aims to solve the problem of low optimization efficiency caused by the large number of compiler options and complex associations by establishing a compilation option relationship model to narrow the search space and reduce the number of genetic algorithm iterations, thereby significantly reducing the compilation optimization overhead while ensuring that the program performance is optimized.

[0004] In order to solve the above technical problems, the technical solution adopted by the present invention is: A method for reducing the search space of compilation option sequences comprises the following steps: S1, open a single compilation option item by item to sample the programs in the template assembly, and obtain the relative preset compilation option sequence of the programs in the template assembly under each compilation option Speedup data of S2, calculate the harmonic mean of the speedup data, and filter out the valid compilation option set based on the harmonic mean ; S3, using a valid set of compilation options Construct a two-dimensional option matrix, compare the acceleration effects of binary option sequences based on the two-dimensional option matrix, and establish a directed graph of compilation option relationships; S4, use depth-first search on the directed graph of compilation option relations to obtain the set of compilation option sequences to be selected ; S5, using genetic algorithm to select the compilation option sequence set The compile option subsequence in Iterative optimization is performed on the target program to generate the optimal compilation option sequence with the shortest running time.

[0005] Optionally, in step S1, the template assembly is relatively preset in the compilation option sequence under each compilation option. The speedup ratio data is The matrix ,in is the total number of template programs in the template program set, The number of compile options for a particular version of the compiler; the matrix Any OK The column elements represent the The program is in The speedup ratio under the optimization of the compilation options is .

[0006] Optionally, calculating the harmonic mean of the acceleration ratio data in step S2 refers to The matrix The acceleration ratio data is composed of the matrix The harmonic mean of each column of data in represents the optimization effect of the compilation option corresponding to the column on the template assembly; and for any Harmonic mean of the column If the optimization effect satisfy , then put the Add compilation options to the set of valid compilation options ,in .

[0007] Optionally, in step S3, a valid compilation option set is used Construct a two-dimensional option matrix, compare the acceleration effects of binary option sequences based on the two-dimensional option matrix, and establish a directed graph of compilation option relationships, including: S3.1, Use a valid compilation option set Build The two-dimensional option matrix ~ , any A two-dimensional option matrix Middle Line The column values ​​represent Programs in binary sequences The optimization effect under optimization, where A set of valid compilation options The number of elements in , They are the a and b compilation options respectively. ; S3.2, yes The two-dimensional option matrix ~ Sum and get the size The matrix , take the matrix The median of all values ​​in ; S3.3, Establishment Adjacency matrix of the compilation option relationship graph , for the matrix Each value of , if the condition is met , then the adjacency matrix The value of the corresponding position is set to 1; if the condition is met , then the adjacency matrix The corresponding position value is set to 0; the adjacency matrix Middle Line The column value is 1, representing a binary sequence The optimization effect is acceptable; if it is 0, it means a binary sequence The optimization effect is unacceptable; the adjacency matrix Used to define the directed graph of compilation option relationships , where the vertex set V Represents a set of compilation options, edge set From the adjacency matrix The directed edges in are determined; if the adjacency matrix Middle Line Column value , then it means that from the compilation option relationship directed graph The vertices in To the top There is a directed edge from vertex Compile options to Vertex The optimization effect of the compilation options is acceptable.

[0008] Optionally, in step S3.1, a valid compilation option set is applied Build The two-dimensional option matrix ~ At any time A two-dimensional option matrix The construction process is as follows: Get the Programs in binary sequences Optimize relative preset compilation option sequence Speedup ; Get binary sequence Optimize relative preset compilation option sequence Speedup ; Take the matrix Middle Line Column value ; Take the matrix Middle Line Column value ;when When the two-dimensional option matrix Middle Line The column is recorded as 1. When the two-dimensional option matrix Middle Line The column is recorded as 0, and the two-dimensional option matrix is ​​obtained by traversing in this way. All the values ​​in the final result are A two-dimensional option matrix .

[0009] Optionally, in step S4, a depth-first search is performed on the directed graph of compilation option relationships to obtain a set of compilation option subsequences to be selected. When , the binary compilation option sequence searched is connected one by one to obtain the compilation option subsequence , and add it to the list of compilation options to be selected , ensure that the list of compilation options to be selected is entered All elements in are not subsequences of any other element.

[0010] Optionally, in step S5, a genetic algorithm is used to select a set of compilation option sequences. The compile option subsequence in When iterative optimization is performed on the target program to generate the optimal compilation option sequence with the shortest running time, the set of candidate compilation option sequences is included. As the initial population of the genetic algorithm, iterative optimization is performed on the target program, and finally the optimal compilation option sequence with the shortest running time is obtained.

[0011] In addition, this embodiment also provides a system for reducing a compilation option sequence search space, comprising a microprocessor and a memory connected to each other, wherein the microprocessor is programmed or configured to execute the method for reducing a compilation option sequence search space.

[0012] In addition, this embodiment further provides a computer-readable storage medium, in which a computer program or instruction is stored. The computer program or instruction is programmed or configured to execute the method of reducing the compilation option sequence search space through a processor.

[0013] In addition, this embodiment also provides a computer program product, including a computer program or instructions, where the computer program or instructions are programmed or configured to execute the method of reducing the compilation option sequence search space through a processor.

[0014] Compared with the prior art, the present invention can mainly achieve the following beneficial effects: the present invention first screens the effective compilation option set and explores the optimization effect of the binary compilation option sequence, determines the influence of the compilation option sequence on continuous optimization, greatly reduces the compilation option search space, and is conducive to obtaining high-quality compilation option subsequences with low overhead. The high-quality subsequence is used as the initial population of the genetic algorithm to ensure the effectiveness of the individuals in the initial population, improve the convergence speed, and achieve the goal of determining the optimal compilation option sequence with low overhead, so that the present invention can effectively solve the problem of low optimization efficiency caused by the large number of compiler compilation options and complex associations, narrow the search space by establishing a compilation option relationship model, and reduce the number of optimization attempts by combining genetic algorithms, while ensuring that the program performance is optimized, the compilation optimization overhead is significantly reduced, which is particularly suitable for the compilation optimization scenario of large programs. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 Schematic diagram of the basic flow of the method of the embodiment of the present invention.

[0016] Figure 2 The directed graph of compilation option relationships expressed by the adjacency matrix obtained in the embodiment of the present invention is Example. DETAILED DESCRIPTION

[0017] In order to enable those skilled in the art to better understand the technical solution of the present invention, the technical solution of the present invention will be further described in detail below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0018] like Figure 1 As shown, the method for reducing the compilation option sequence search space in this embodiment includes the following steps: S1, open a single compilation option item by item to sample the programs in the template assembly, and obtain the relative preset compilation option sequence of the programs in the template assembly under each compilation option (like etc.) S2, calculate the harmonic mean of the speedup data, and filter out the valid compilation option set based on the harmonic mean ; S3, using a valid set of compilation options Construct a two-dimensional option matrix, compare the acceleration effects of binary option sequences based on the two-dimensional option matrix, and establish a directed graph of compilation option relationships; S4, use depth-first search on the directed graph of compilation option relations to obtain the set of compilation option sequences to be selected ; S5, using genetic algorithm to select the compilation option sequence set The compile option subsequence in Iterative optimization is performed on the target program to generate the optimal compilation option sequence with the shortest running time.

[0019] Taking the 14.0.0 version of the Clang / LLVM compiler as an example, the compiler has a total of 134 compilation options (such as -tti, -targetlibinfo, -targetpassconfig, etc.). Among them, -machine-branch-prob will use branch probability information to optimize the branch layout of the machine code, and improve the CPU pipeline efficiency by optimizing branches; -machine-cse is used to eliminate repeated calculations in the machine code and reuse the calculated results to reduce redundant memory accesses; when compiling a program, these compilation options optimize the intermediate representation of the program in turn according to the order of input to generate an optimized binary program; for a template program , enable individual compilation options , get its relative expert preset compilation option sequence (such as ) as an example: Get the speedup using When compiling, run Time ; Get usage When compiling, run Time ; Enable individual compilation options relatively The speedup ratio is ; In step S1 of this embodiment, the template assembly is relatively preset in the compilation option sequence under each compilation option The speedup ratio data is The matrix ,in is the total number of template programs in the template program set, The number of compile options for a particular version of the compiler; the matrix Any OK The column elements represent the The program is in The speedup ratio under the optimization of the compilation options is .

[0020] In step S2 of this embodiment, the harmonic mean value of the speedup ratio data is calculated for The matrix The acceleration ratio data is composed of the matrix The harmonic mean of each column of data in represents the optimization effect of the compilation option corresponding to the column on the template assembly; and for any Harmonic mean of the column If the optimization effect satisfy , then put the Add compilation options to the set of valid compilation options ,in .

[0021] In step S3 of this embodiment, a valid compilation option set is used Construct a two-dimensional option matrix, compare the acceleration effects of binary option sequences based on the two-dimensional option matrix, and establish a directed graph of compilation option relationships, including: S3.1, Use a valid compilation option set Build The two-dimensional option matrix ~ , any A two-dimensional option matrix Middle Line The column values ​​represent Programs in binary sequences The optimization effect under optimization, where A set of valid compilation options The number of elements in , They are the a and b compilation options respectively. ; S3.2, yes The two-dimensional option matrix ~ Sum and get the size The matrix , take the matrix The median of all values ​​in ; S3.3, Establishment Adjacency matrix of the compilation option relationship graph , for the matrix Each value of , if the condition is met , then the adjacency matrix The value of the corresponding position is set to 1; if the condition is met , then the adjacency matrix The corresponding position value is set to 0; the adjacency matrix Middle Line The column value is 1, representing a binary sequence The optimization effect is acceptable; if it is 0, it means a binary sequence The optimization effect is unacceptable; the adjacency matrix Used to define the directed graph of compilation option relationships , where the vertex set V Represents a set of compilation options, edge set From the adjacency matrix The directed edges in are determined; if the adjacency matrix Middle Line Column value , then it means that from the compilation option relationship directed graph The vertices in To the top There is a directed edge from vertex Compile options to Vertex The optimization effect of the compilation option is acceptable. Figure 2 The directed graph of compilation option relationships expressed by the adjacency matrix obtained in this embodiment is The example shows the dependencies of some compilation options. Each node is a compilation option: -assumption-cache-tracker: Assumption cache tracker, this option is used to track and optimize the cache behavior assumed by the compiler. -targetlibinfo: Target library information, this option is used to provide information about the target platform library to help the compiler optimize. -deadargelim: Remove dead parameters, this option is used to remove parameters that are not used in the function to reduce code size and improve performance. -callsite-splitting: Call site splitting, this option is used to split the code at the call site to improve code locality and performance. -block-freq: Block frequency, this option is used to collect and use the execution frequency information of code blocks to guide compiler optimization. -early-cse: Early common subexpression elimination, this option is used to eliminate common subexpressions in the early stage of compilation to reduce code redundancy. -lower-expect: Lower expectations, this option is used to lower the compiler's expectations of the code execution path to improve the accuracy of optimization. -lazy-value-info: Delayed value information, this option is used to delay the collection and use of value information to reduce compilation time. -postdomtree: Post-dominator tree, this option is used to build a post-dominator tree, which is a data structure used to analyze control flow graphs. Figure 2Any directed edge in , such as edge ①, indicates the optimization dependency between the two compilation options -lower-expect and -postdomtree. When the sequence formed by the two compilation options is <-lower-expect,-postdomtree>, the performance optimization effect is better than any other possible sequence formed by the two compilation options (for example, <-postdomtree,-lower-expect>, <-lower-expect>, <-postdomtree>).

[0022] In step S3.1 of this embodiment, a valid compilation option set is used Build The two-dimensional option matrix ~ At any time A two-dimensional option matrix The construction process is as follows: Get the Programs in binary sequences Optimize relative preset compilation option sequence Speedup ; Get binary sequence Optimize relative preset compilation option sequence Speedup ; Take the matrix Middle Line Column value ; Take the matrix Middle Line Column value ;when When the two-dimensional option matrix Middle Line The column is recorded as 1. When the two-dimensional option matrix Middle Line The column is recorded as 0, and the two-dimensional option matrix is ​​obtained by traversing in this way. All the values ​​in the final result are A two-dimensional option matrix .

[0023] In step S4 of this embodiment, a depth-first search is performed on the directed graph of compilation option relations to obtain a set of compilation option subsequences to be selected. When , the binary compilation option sequence searched is connected one by one to obtain the compilation option subsequence , and add it to the list of compilation options to be selected , ensure that the list of compilation options to be selected is entered All elements in are not subsequences of any other element.

[0024] In step S5 of this embodiment, a genetic algorithm is used to select a set of compilation option sequences. The compile option subsequence in When iterative optimization is performed on the target program to generate the optimal compilation option sequence with the shortest running time, the set of candidate compilation option sequences is included. As the initial population of the genetic algorithm, iterative optimization is performed on the target program, and finally the optimal compilation option sequence with the shortest running time is obtained. The value range is generally 0.7~0.8, and the mutation probability The value range is generally 0.05~0.15), the iterative algebra The value range is generally 800 to 1500. It should be noted that the genetic algorithm is an existing well-known algorithm, so its implementation details are not described in detail here.

[0025] In summary, the method of reducing the search space of compilation option sequences in this embodiment pre-samples the optimization effect of each compilation option on the template program set, compares it with the effect of the compilation option sequence on the template program to obtain a relationship diagram of the compilation options, obtains a high-quality compilation option subsequence through depth-first search, uses it as the initial population of the genetic algorithm, and obtains the optimal compilation option sequence through multiple rounds of iterative compilation. Therefore, the method of this embodiment can reduce the selection overhead of the program compilation option sequence, and can make up for the problem of low optimization efficiency caused by the large number of compiler compilation options and complex associations.

[0026] In addition, this embodiment also provides a system for reducing a compilation option sequence search space, comprising a microprocessor and a memory connected to each other, wherein the microprocessor is programmed or configured to execute the method for reducing a compilation option sequence search space.

[0027] In addition, this embodiment further provides a computer-readable storage medium, in which a computer program or instruction is stored. The computer program or instruction is programmed or configured to execute the method of reducing the compilation option sequence search space through a processor.

[0028] In addition, this embodiment also provides a computer program product, including a computer program or instructions, where the computer program or instructions are programmed or configured to execute the method of reducing the compilation option sequence search space through a processor.

[0029] Those skilled in the art should understand that the technical solution provided by the present invention may be in the form of a method, a system, or a computer program product. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-readable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes. The present invention is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present invention. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the functions in the process. Figure 1 A process or multiple processes and / or boxes Figure 1 These computer program instructions can also be stored in a computer-readable memory that can guide a computer or other programmable data processing device to work in a specific way, so that the instructions stored in the computer-readable memory produce a product including an instruction device, which implements the functions specified in the process. Figure 1 A process or multiple processes and / or boxes Figure 1 These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to produce a computer-implemented process, so that the instructions executed on the computer or other programmable device provide for implementing the process in the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0030] The above is only a preferred embodiment of the present invention, and the protection scope of the present invention is not limited to the above embodiments. All technical solutions under the concept of the present invention belong to the protection scope of the present invention. It should be pointed out that for ordinary technicians in this technical field, some improvements and modifications without departing from the principle of the present invention should also be regarded as the protection scope of the present invention.

Claims

1. A method for reducing the search space of compilation option sequences, characterized in that: The steps include: S1, open a single compilation option item by item to sample the programs in the template assembly, and obtain the relative preset compilation option sequence of the programs in the template assembly under each compilation option Speedup data of S2, calculate the harmonic mean of the speedup data, and filter out the valid compilation option set based on the harmonic mean ; S3, using a valid set of compilation options Construct a two-dimensional option matrix, compare the acceleration effects of binary option sequences based on the two-dimensional option matrix, and establish a directed graph of compilation option relationships; S4, use depth-first search on the directed graph of compilation option relations to obtain a set of compilation option subsequences to be selected ; S5, using genetic algorithm to select the compilation option sequence set The compile option subsequence in Iterative optimization is performed on the target program to generate the optimal compilation option sequence with the shortest running time.

2. The method for reducing the compilation option sequence search space according to claim 1, characterized in that: In step S1, the template assembly is set relative to the preset compilation option sequence under each compilation option The speedup data is The matrix ,in is the total number of template programs in the template program set, The number of compile options for a particular version of the compiler; the matrix Any OK The column elements represent the The program is in The speedup ratio under the optimization of the compilation options is .

3. The method for reducing the search space of compilation option sequences according to claim 2, characterized in that: The calculation of the harmonic mean of the acceleration ratio data in step S2 refers to The matrix The acceleration ratio data is composed of the matrix The harmonic mean of each column of data in represents the optimization effect of the compilation option corresponding to the column on the template assembly; and for any Harmonic mean of the column If the optimization effect satisfy , then put the Add the compilation options to the set of valid compilation options ,in .

4. The method for reducing the compilation option sequence search space according to claim 1, characterized in that: In step S3, a valid compilation option set is applied. Construct a two-dimensional option matrix, compare the acceleration effects of binary option sequences based on the two-dimensional option matrix, and establish a directed graph of compilation option relationships, including: S3.1, Use a valid compilation option set Build The two-dimensional option matrix ~ , any A two-dimensional option matrix Middle Line The column values ​​represent Programs in binary sequences The optimization effect under optimization, where A set of valid compilation options The number of elements in , They are the a and b compilation options respectively. ; S3.2, yes The two-dimensional option matrix ~ Sum and get the size The matrix , take the matrix The median of all values ​​in ; S3.3, Establishment Adjacency matrix of the compilation option relationship graph , for the matrix Each value of , if the condition is met , then the adjacency matrix The value of the corresponding position is set to 1; if the condition is met , then the adjacency matrix The corresponding position value is set to 0; the adjacency matrix Middle Line The column value is 1, representing a binary sequence The optimization effect is acceptable; if it is 0, it means a binary sequence The optimization effect is unacceptable; the adjacency matrix Used to define the directed graph of compilation option relationships , where the vertex set V Represents a set of compilation options, edge set From the adjacency matrix The directed edges in are determined; if the adjacency matrix Middle Line Column value , then it means that from the compilation option relationship directed graph The vertices in To the top There is a directed edge from vertex Compile options to Vertex The optimization effect of the compilation option is acceptable.

5. The method for reducing the search space of compilation option sequences according to claim 4, characterized in that: Step S3.1 applies a valid compilation option set Build The two-dimensional option matrix ~ At any time A two-dimensional option matrix The construction process is as follows: Get the Programs in binary sequences Optimize relative preset compilation option sequence Speedup ; Get binary sequence Optimize relative preset compilation option sequence Speedup ; Take the matrix Middle Line Column value ; Take the matrix Middle Line Column value ;when When the two-dimensional option matrix Middle Line The column is recorded as 1. When the two-dimensional option matrix Middle Line The column is recorded as 0, and the two-dimensional option matrix is ​​obtained by traversing in this way. All the values ​​in the final result are A two-dimensional option matrix .

6. The method for reducing the search space of compilation option sequences according to claim 5, characterized in that: In step S4, a depth-first search is performed on the directed graph of compilation option relationships to obtain a set of compilation option subsequences to be selected. When , the binary compilation option sequence searched is connected one by one to obtain the compilation option subsequence , and add it to the list of compilation options to be selected , ensure that the list of compilation options to be selected is entered All elements in are not subsequences of any other element.

7. The method for reducing the compilation option sequence search space according to claim 6, characterized in that: In step S5, a genetic algorithm is used to select a set of compilation option sequences. The compile option subsequence in When iterative optimization is performed on the target program to generate the optimal compilation option sequence with the shortest running time, the set of candidate compilation option sequences is included. As the initial population of the genetic algorithm, iterative optimization is performed on the target program, and finally the optimal compilation option sequence with the shortest running time is obtained.

8. A system for reducing the search space of a compilation option sequence, comprising a microprocessor and a memory connected to each other, characterized in that: The microprocessor is programmed or configured to execute the method for reducing the search space of compilation option sequences as claimed in any one of claims 1 to 7.

9. A computer-readable storage medium having a computer program or instruction stored therein, characterized in that: The computer program or instruction is programmed or configured to execute the method for reducing the search space of compilation option sequences as claimed in any one of claims 1 to 7 through a processor.

10. A computer program product comprising a computer program or instructions, characterized in that The computer program or instruction is programmed or configured to execute the method for reducing the search space of compilation option sequences as claimed in any one of claims 1 to 7 through a processor.

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