CN109918074A - Compiling link optimization method - Google Patents
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Abstract
The present invention relates to a kind of compiling link optimization methods, it is using the address space allocation function of the linker LD of GNU open source compiling link tool BINUTILS, symbol resolution function and resets bit function, the linking functions of linker are optimized, also, the function of optimization includes the query function that symbol table is established in function, locating function and link process.Compiling link optimization method provided by the invention overcomes the slow-footed defect of compiling link, memory usage when can reduce link, to achieve the purpose that promote compiling link speed, save time cost, improve production efficiency.
Description
Technical field
The present invention relates to computer software programs running technology fields, and in particular to a kind of compiling link optimization method.
Background technique
Effect of the GNU tools chain in linux system is great, and compiling link occupies important proportion.In recent years, Linux system
System rapidly develops, and with the continuous development of computer technology, more and more personal and enterprises start largely using Linux system
System, the type of various application programs are continuously increased, and program function constantly changes, the multiplicity further and complexity of change, such
Phenomenon results in the increase of program code amount sharply increased with module, while also bringing greatly to the compiling link of program
Burden.It compiles in integrating process, the increase of module results in the increase of binary object file, directly results in the symbol for needing to link
It number increases significantly, such order of magnitude will occupy a large amount of system resources, seriously drag the speed of service of slow system, so will introduce
A kind of Mode in Query Process of big data, to solve the problems, such as that link is brought.
Original linker has used hash algorithm.Hash algorithm is exactly by data (character or the number of any given length
Value etc.) shorter, regular length numerical value is mapped as by given function, this numerical value is referred to as hash value, this numerical value is just
As index.Hash table is that one set of keyword is mapped to one by given hash function H (key) and method of handling conflicts
On the memory headroom applied, for H (key) as given storage location of the keyword in memory headroom, this partial memory is empty
Between be referred to as hash table or hash, gained storage location is known as the address hash or hash address.As linear data structure and table
Lattice and queue etc. are compared, and it is a kind of than faster that hash table is undoubtedly search speed.
In entire link process, the foundation of symbol table searches that part is the most time-consuming, essentially consist in foundation to symbol table,
The consumption of aspect is searched and located, the more slightly smaller file destination of quantity can not perceive the consumption of this respect, but if face
The link of a file destinations up to a hundred, and when each file destination includes the symbol that (more than) needs up to a hundred link, it is such
The order of magnitude will expose the deficiency of Loongson platform hardware aspect.If continuing to make under such order of magnitude or the higher order of magnitude
With the existing hash algorithm of linker, it will the major defect of exposure hash algorithm, is exactly that space efficiency is low, that is to say, that when
In the case where higher amount level, it will generate hash conflict, conflict for solution hash it is necessary to open up more memories；Link
The hash algorithm that device uses now will occupy bigger memory, system speed is influenced during this period it is very big, easily cause be
System Caton, system resource caused by linking, which is largely occupied, can not be ignored the influence of system.
Summary of the invention
To solve the shortcomings of the prior art, the present invention provides a kind of compiling link optimization methods, are increased income using GNU
The address space allocation function of the linker LD of compiling link tool BINUTILS, symbol resolution function and bit function is reset,
The linking functions of linker are optimized, also, the function of optimizing includes that symbol table establishes function, locating function and link
Query function in the process.
Wherein, the symbol table establish function be optimized for creation GL_KV symbol table.
Wherein, symbol table is established in the optimization of function, creates GL_KV symbol table by following step:
Step S1: the library GNU symbol and basic graphics library symbol are collected respectively；
Step S2: the symbolic name for the symbol collected in step S1 is inputted into Bloom filter；
Step S3: the input by the output of Bloom filter as Index Algorithm determines position of the symbol in symbol table；
Step S4: symbol table is written into symbolic information.
Wherein, further includes:
Step S5: if discovery has repetition after indexed algorithm calculates, table storage data are separately filled out, if repeat by
GL_KV_sym- > rep- > sym_r is determined；
In the step S3, Index Algorithm is Hash Index Algorithm；
Also, in the step S3- step S4, Bloom filter has obtained multiple values by multiple hash functions, with this
Multiple values are index to mark GL_KV bit array, while using multiple value as the input of hash Index Algorithm, obtaining each symbol
Symbolic information is written in GL_KV table for position number in GL_KV table.
Wherein, the optimization of the locating function, is completed by following step:
Step SA: the inquiry table for being directed to GL_KV symbol is established；
Step SB: input sym_key, positioning corresponding sym_key by Bloom filter whether there is in inquiry table；
Step SC: if it does not exist, then feedback search fails；If it exists, SD is thened follow the steps；
Step SD: whether the searched sym_key of judgement is flase positive, if so, feedback search fails,
If it is not, then feedback search success.
Wherein, in the step SB, Bloom filter is made of multiple hash functions and a units group, also, described
In step SD, judge whether searched sym_key is flase positive by the value of GL_KV_sym- > sym_key.
Wherein, the query function optimization in the link process, is completed by following step:
Step Sa: an inquiry table for OL_KV symbol and GL_KV symbol is established respectively；
Step Sb: input sym_key；
Step Sc: determining and whether there is satisfactory labeled sym_key in the inquiry table for OL_KV symbol,
If it exists, then its presence is marked；
Step Sd: determining and whether there is satisfactory labeled sym_key in the inquiry table for GL_KV symbol,
If it exists, its presence is also marked；
Step Se: if by step Sc and step Sd, there is no satisfactory labeled in two inquiry tables
Sym_key then reports an error；
If there is the sym_key that there is label in two inquiry tables, the corresponding sym_value of the sym_key is used；
If the sym_key in two inquiry tables in the presence of label, stronger and weaker, if the label in two inquiry tables
Sym_key is strong symbol, then reports an error, if the sym_key of the label in two inquiry tables has one for strong symbol, selection is strong
The corresponding sym_value of symbol.
Wherein, the step Sc includes:
Step Sc1: positioning corresponding sym_key by Bloom filter whether there is in the inquiry for being directed to OL_KV symbol
In table；If it does not exist, Sd is thened follow the steps, and if it exists, then follow the steps Sc2；
Step Sc2: judging whether corresponding sym_key is the sym_key of flase positive, if it is not, then marking
This sym_key, the sym_key marked simultaneously execute step Sd；If so, thening follow the steps Sc3；
Step Sc3: whether there is this sym_key in inquiry repeated data, if so, then marking this sym_key, marked
Sym_key simultaneously executes step Sd；If nothing, directly execution step Sd.
Wherein, the step Sd includes:
Step Sd1: positioning corresponding sym_key by Bloom filter whether there is in the inquiry for being directed to GL_KV symbol
In table；If it does not exist, Se is thened follow the steps, and if it exists, then follow the steps Sd2；
Step Sd2: judging whether corresponding sym_key is the sym_key of flase positive, if it is not, then marking
This sym_key, the sym_key marked simultaneously execute step Se；If so, thening follow the steps Sd3；
Step Sd3: whether there is this sym_key in inquiry repeated data, if so, then marking this sym_key, marked
Sym_key simultaneously executes step Se；If nothing, directly execution step Se.
Wherein, in the step Sa, for the inquiry table of OL_KV symbol and GL_KV symbol by multiple hash functions and one
The Bloom filter of units group composition and a hash Index Algorithm are calculated.
Compiling link optimization method provided by the invention overcomes the slow-footed defect of compiling link, when can reduce link
Memory usage, to achieve the purpose that promote compiling link speed, save time cost, improve production efficiency.
Detailed description of the invention
Fig. 1: symbol of the invention establishes function optimization implementation process；
Fig. 2: locating function of the invention optimizes implementation process；
Fig. 3: the query function in link process of the invention optimizes implementation process.
Specific embodiment
In order to have further understanding to technical solution of the present invention and beneficial effect, it is described in detail with reference to the accompanying drawing
Technical solution of the present invention and its beneficial effect of generation.
Compiling link optimization method of the invention, main inventive concept are compiling link tool of increasing income using GNU
The functions such as the address space allocation of the linker LD of BINUTILS, symbol resolution and reorientation, to the linking functions of linker into
Row optimization.Symbol foundation, the algorithm searched and reset bit function are all improved, original common hash algorithm is given up,
Then Bloom filter is used, and the symbol that the library in the library of GNU component and fundamental figure can be provided is safeguarded, Quan Mianti
The speed in compiling link stage is risen, the yoke of hardware is solved with software mode.
Specifically, as shown in Figure 1-Figure 3, symbol corresponding to compiling link optimization method respectively of the invention establishes function
It can optimize, the implementation process that the query function in locating function optimization and link process optimizes.
Firstly, being compiled chain refering to Figure 1, establish the implementation process of function optimization for symbol of the invention
When connecing optimization, the most basic symbol table for making GNU component safeguard that a GNU tools chain and basic graphics library can be provided first,
This symbol table mainly has symbolic name, value of symbol (address), type, place file, symbolic number of the same name etc., and symbol is as key, ground
As value, this list item is that (xx can be 64, be also possible to 32) this structural body to system struct Elfxx_Sym for location
One extension.Be only used as before this entry compiling link use, so can't memory-resident, need not worry about this table pair
System will cause any burden.This table is named as GL_KV (G:GNU, L: linker, K:key, V:value), list item GL_
KV_sym, these data are stored in a data file.In one embodiment of the invention, the general configuration of GL_KV is as follows:
The step of creating GL_KV symbol table data file:
(1) library GNU symbol and basic graphics library symbol are collected respectively；
(2) using the symbolic name in the glossary of symbols of above-mentioned collection as the input of Bloom filter；
(3) input by the output of Bloom filter as Index Algorithm, determines the position of symbol in the data file；
(4) symbolic information is written in symbol table；
(5) if there is after Index Algorithm discovery have repetition, then separately establish table storage data, if having repetition then by
GL_KV_sym- > rep- > sym_r is determined.
Then, it please refers to shown in Fig. 2, for the implementation process that locating function of the invention optimizes, in locating function optimization, uses
N hash function and a units group form an inquiry table, this inquiry table (being exactly this bit array) is specifically in GL_
This table of KV, for carrying out inquiry operation to this table of GL_KV；It is opposite that sym_key can be positioned rapidly using Bloom filter
The sym_value answered whether there is, and use hash [0] (...) ..., hash [n-1] (...) as Index Algorithm because
Son determines rapidly the value of sym_value.Wherein, it is contemplated that the use of Bloom filter is by bring " false positive "
Although as a result, such probability very it is small, for link process, such mistake be very it is fatal, so
As a result then as the value of GL_KV_sym- > sym_key (as shown in following codes) to determine whether being " false positive "
Sym_value, both eliminated influences brought by Bloom filter " false positive " in this way, also ensures the grand filtering of cloth
The correctness of device use aspect in link process.
if(Del_FP(Get_S_K(key),Get_S_K(gl_sym_key)))
goto F_Positon；
else{
...
}
Be the implementation process of the query function optimization in link process of the invention finally, please refer to shown in Fig. 3, into
During row link, the link of several hundred a file destinations also takes identical mode to be inquired easily, initially sets up one
The table of OL_KV (O: L: file destination links) (shown in following code).
An inquiry table is formed specifically in OL_KV using n hash function and a units group, is used for OL_KV
Table carries out inquiry operation, uses hash [0] (...) ..., hash [n-1] (...) as the factor of Index Algorithm, determines sym_
The value of value is completed to the reorientation of symbol and the amendment of address.In order to avoid Bloom filter bring " false
It is influenced caused by positive ", guarantees correctness using OL_KV- > sym_key.When establishing table, just symbol of the same name is carried out
Determine, if there is point of strong and weak symbol, then uses strong symbol；If being all weak symbol, it is designated generally as 0, finally display is looked into
It looks for unsuccessfully；If being all strong symbol, report an error at once, failure is searched in same display.
Specifically, being involved in many symbols of the same name in link process.When link, in the process inquired key
In, OL_KV table is first looked for, checks whether that there are the key, if it does, this symbol is marked；Then GL_ is inquired again
This table of KV, inquiring the key whether there is, if it is present being compared with the symbol in OL_KV table, which is strong symbol,
All it is strong symbol, then reports an error, wherein having one is strong symbol, selects strong symbol；If be not present in GL_KV and OL_KV table
Key then reports an error, if only existing a key in the two, uses the corresponding value of this key.
Note: OL_KV establish mode and GL_KV to establish mode identical
Compiling link optimization method provided by the invention overcomes the slow-footed defect of compiling link, when can reduce link
Memory usage, to achieve the purpose that promote compiling link speed, save time cost, improve production efficiency.
Compiling link optimization method provided by the invention, is applicable to the optimization of the compiling link under multi software platform,
The compiling link being particularly suitable under Loongson platform.
It is so-called " linker " in the present invention, refer to the linker LD of GNU open source compiling link tool BINUTILS, uses
In many target binary files are linked into an executable binary file.
It is so-called " GNU tools chain " in the present invention, it is in each large-scale open source code project (including linux kernel sheet
Body) strength that supports quietly behind.They are by one group of necessary tool and software sharing, for compiling and debugging from the smallest work
Has software to the most complicated various softwares with linux kernel feature.
So-called " hash algorithm " in the present invention, also known as hashing algorithm, it is a kind of one-way cipher system, i.e., it is
One irreversible mapping from plaintext to ciphertext, only ciphering process, without decrypting process.
It is so-called " Bloom filter " in the present invention, refer to a very long binary vector and a series of Random Maps
Function.Bloom filter can be used for retrieving an element whether in a set, and its advantages are space efficiency and inquiry
Time, the disadvantage is that having certain false recognition rate and deleting difficulty, such misrecognition was just claimed all considerably beyond general algorithm
For false positive.
Although the present invention is illustrated using above-mentioned preferred embodiment, the protection model that however, it is not to limit the invention
It encloses, anyone skilled in the art are not departing within the spirit and scope of the present invention, and opposite above-described embodiment carries out various changes
It is dynamic still to belong to the range that the present invention is protected with modification, therefore protection scope of the present invention subjects to the definition of the claims.
Claims (10)
1. a kind of compiling link optimization method, it is characterised in that: utilize the linker of GNU open source compiling link tool BINUTILS
The address space allocation function of LD, symbol resolution function and bit function is reset, the linking functions of linker are optimized, and
And the function of optimization includes the query function that symbol table is established in function, locating function and link process.
2. compiling link optimization method as described in claim 1, it is characterised in that: the symbol table establishes being optimized for for function
Create GL_KV symbol table.
3. compiling link optimization method as claimed in claim 2, it is characterised in that: symbol table is established in the optimization of function, is led to
Cross following step creation GL_KV symbol table:
Step S1: the library GNU symbol and basic graphics library symbol are collected respectively；
Step S2: the symbolic name for the symbol collected in step S1 is inputted into Bloom filter；
Step S3: the input by the output of Bloom filter as Index Algorithm determines position of the symbol in symbol table；
Step S4: symbol table is written into symbolic information.
4. translating link optimized method as claimed in claim 3, it is characterised in that further include:
Step S5: if discovery has repetition after indexed algorithm calculates, a table storage data are separately filled out, if repeat by GL_
KV_sym- > rep- > sym_r is determined；
In the step S3, Index Algorithm is Hash Index Algorithm；
Also, in the step S3- step S4, Bloom filter has obtained multiple values by multiple hash functions, multiple with this
Value is index to mark GL_KV bit array, while using multiple value as the input of hash Index Algorithm, showing that each symbol exists
Symbolic information is written in GL_KV table for position in GL_KV table.
5. the compiling link optimization method as described in claim 2-4, it is characterised in that: the optimization of the locating function is led to
Cross following step completion:
Step SA: the inquiry table for being directed to GL_KV symbol is established；
Step SB: input sym_key, positioning corresponding sym_key by Bloom filter whether there is in inquiry table；
Step SC: if it does not exist, then feedback search fails；If it exists, SD is thened follow the steps；
Step SD: whether the searched sym_key of judgement is flase positive, if so, feedback search fails, if not
It is, then feedback search success.
6. compiling link optimization method as claimed in claim 5, it is characterised in that: in the step SB, Bloom filter by
Multiple hash functions and units group composition, also, in the step SD, sentenced by the value of GL_KV_sym- > sym_key
Whether disconnected searched sym_key is flase positive.
7. the compiling link optimization method stated such as claim 1, it is characterised in that: the query function in the link process is excellent
Change, completed by following step:
Step Sa: an inquiry table for OL_KV symbol and GL_KV symbol is established respectively；
Step Sb: input sym_key；
Step Sc: it determines and whether there is satisfactory labeled sym_key in the inquiry table for OL_KV symbol, if depositing
Then marking its presence；
Step Sd: it determines and whether there is satisfactory labeled sym_key in the inquiry table for GL_KV symbol, if depositing
Also its presence is being marked；
Step Se: if by step Sc and step Sd, satisfactory labeled sym_ is not present in two inquiry tables
Key then reports an error；
If there is the sym_key that there is label in two inquiry tables, the corresponding sym_value of the sym_key is used；
It is stronger and weaker if there is the sym_key of label in two inquiry tables, if the sym_ of the label in two inquiry tables
Key is strong symbol, then reports an error, if the sym_key of the label in two inquiry tables has one for strong symbol, selects strong symbol
Corresponding sym_value.
8. compiling link optimization method as claimed in claim 7, it is characterised in that: the step Sc includes:
Step Sc1: positioning corresponding sym_key by Bloom filter whether there is in the inquiry table for OL_KV symbol；
If it does not exist, Sd is thened follow the steps, and if it exists, then follow the steps Sc2；
Step Sc2: judging whether corresponding sym_key is the sym_key of flase positive, if it is not, then marking this
Sym_key, the sym_key marked simultaneously execute step Sd；If so, thening follow the steps Sc3；
Whether step Sc3: having this sym_key in inquiry repeated data, if so, this sym_key is then marked, the sym_ marked
Key simultaneously executes step Sd；If nothing, directly execution step Sd.
9. compiling link optimization method as claimed in claim 7, it is characterised in that: the step Sd includes:
Step Sd1: positioning corresponding sym_key by Bloom filter whether there is in the inquiry table for GL_KV symbol；
If it does not exist, Se is thened follow the steps, and if it exists, then follow the steps Sd2；
Step Sd2: judging whether corresponding sym_key is the sym_key of flase positive, if it is not, then marking this
Sym_key, the sym_key marked simultaneously execute step Se；If so, thening follow the steps Sd3；
Whether step Sd3: having this sym_key in inquiry repeated data, if so, this sym_key is then marked, the sym_ marked
Key simultaneously executes step Se；If nothing, directly execution step Se.
10. compiling link optimization method as claimed in claim 7, it is characterised in that: in the step Sa, accorded with for OL_KV
Number and GL_KV symbol the inquiry table Bloom filter and a hash index that are made of multiple hash functions and a units group
Algorithm is calculated.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111208978A (en) * | 2019-12-31 | 2020-05-29 | 杭州安恒信息技术股份有限公司 | Character bloom filter realized by taking Python as interface C + + |
| CN111736816A (en) * | 2020-07-20 | 2020-10-02 | 华控清交信息科技(北京)有限公司 | Compiling and linking method and device and compiling and linking device |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH10275088A (en) * | 1997-03-31 | 1998-10-13 | Hitachi Ltd | Link optimizing method |
| CN102385524A (en) * | 2011-12-23 | 2012-03-21 | 浙江大学 | Method for replacing compiling chain order based on mixed-compiling order set |
| CN103034486A (en) * | 2012-11-28 | 2013-04-10 | 清华大学 | Automatic optimization method based on full-system expansion call graph for mobile terminal operation system |
| CN104951290A (en) * | 2014-03-31 | 2015-09-30 | 国际商业机器公司 | Method and equipment for optimizing software |
| CN105320654A (en) * | 2014-05-28 | 2016-02-10 | 中国科学院深圳先进技术研究院 | Dynamic bloom filter and element operating method based on same |
-
2017
- 2017-12-08 CN CN201711294532.0A patent/CN109918074B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH10275088A (en) * | 1997-03-31 | 1998-10-13 | Hitachi Ltd | Link optimizing method |
| CN102385524A (en) * | 2011-12-23 | 2012-03-21 | 浙江大学 | Method for replacing compiling chain order based on mixed-compiling order set |
| CN103034486A (en) * | 2012-11-28 | 2013-04-10 | 清华大学 | Automatic optimization method based on full-system expansion call graph for mobile terminal operation system |
| CN104951290A (en) * | 2014-03-31 | 2015-09-30 | 国际商业机器公司 | Method and equipment for optimizing software |
| CN105320654A (en) * | 2014-05-28 | 2016-02-10 | 中国科学院深圳先进技术研究院 | Dynamic bloom filter and element operating method based on same |
Non-Patent Citations (1)
| Title |
|---|
| 陈瑜等: ""龙芯链接后优化器设计与分析"", 《计算机研究与发展》 * |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111208978A (en) * | 2019-12-31 | 2020-05-29 | 杭州安恒信息技术股份有限公司 | Character bloom filter realized by taking Python as interface C + + |
| CN111208978B (en) * | 2019-12-31 | 2023-05-23 | 杭州安恒信息技术股份有限公司 | Character bloom filter implemented by taking Python as interface C++, and method for implementing character bloom filter |
| CN111736816A (en) * | 2020-07-20 | 2020-10-02 | 华控清交信息科技(北京)有限公司 | Compiling and linking method and device and compiling and linking device |
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