CN105260175B - The processing method of astronomy software Gridding based on OpenMP - Google Patents
The processing method of astronomy software Gridding based on OpenMP Download PDFInfo
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- CN105260175B CN105260175B CN201510591875.8A CN201510591875A CN105260175B CN 105260175 B CN105260175 B CN 105260175B CN 201510591875 A CN201510591875 A CN 201510591875A CN 105260175 B CN105260175 B CN 105260175B
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- 238000003672 processing method Methods 0.000 title claims abstract description 12
- 230000004087 circulation Effects 0.000 claims abstract description 62
- 238000000034 method Methods 0.000 description 17
- 238000010586 diagram Methods 0.000 description 8
- 238000004364 calculation method Methods 0.000 description 4
- 230000007547 defect Effects 0.000 description 3
- 230000015572 biosynthetic process Effects 0.000 description 2
- 238000004064 recycling Methods 0.000 description 2
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Abstract
The processing method of the invention discloses a kind of astronomy software Gridding based on OpenMP, comprising: open up nT OpenMP thread, suppv is calculated into circulation be converted to the son that nT execute parallel and calculate circulation.Wherein, it is described suppv calculated into circulation be converted to the son that nT is executed parallel and calculate circulation specifically include: array is divided into nT data block, is each data block one OpenMP thread of distribution；Bs is indexed for the starting that each OpenMP thread distributes data and terminates index be；It is parallel to execute the nT suppv calculating circulations from bs to be.The present invention for Gridding calculate core include three re-computations circulation the characteristics of, by multithreading setting suppv calculate circulation, it is ensured that the data that different cross-threads possesses be it is entirely different, the memory access collision problem during parallelization is avoided with this.
Description
Technical field
The present invention relates to computer application technology, in particular to a kind of astronomy software based on OpenMP
The processing method of Gridding.
Background technique
Square kilometre radio telescope array SKA is the maximum synthesis radiotelescope that will be built in the world, is used
In the great number of issues of answer puzzlement at present scientific circles, as how first generation celestial body is formed, galactic evolution, cosmic magnetic field, gravitation
Essential, extraterrestrial life and alien civilization, dark matter and dark energy etc..The telescope is by quantity up to 3000 teledish structures
At, it will be than current maximum 50 times of centimeter wave synthesis telescope JVLA sensitivity raising after building up, search speed improves 10000
Times.But performance boost also means that the growth of geometry grade will be presented in the speed of SKA gather data and quantity, and according to plan, SKA is per second
The data volume of acquisition is greater than 12Tb, needs the sum of the performance of all supercomputers of current TOP500 that could complete data processing.
Gridding is to calculate that step is most complicated, time-consuming most data processing link in SKA, is approached in entire project
50% data need to be handled by the software.Fig. 1 is the program processing figure that Gridding calculates core.As shown in Figure 1,
It includes three calculating circulations that Gridding, which calculates core, and outermost circulation is that dind calculates circulation, and intercycle is that suppv is calculated
Circulation, most inner side circulation are that suppu calculates circulation, wherein store input data to be treated in samples array.Dind meter
When calculating cycle calculations gind and cind value, since samples [dind] .iu and samples [dind] .iv is by generating random number
, the gind value calculated accordingly also has randomness, it means that different calculating is recycled, the value of gind may be identical
's.It is introduced for Gridding for by multithreading, if calculating circulation according to dind and carrying out data division, different numbers
Identical gind element may be contained according to block, these elements are directed toward same memory address, when these elements are in multi-thread environment
It is lower while when being accessed, it will cause that memory read-write is inconsistent, cause the memory access conflict between thread.
Fig. 2 is to calculate the schematic diagram that circulation carries out data division according to dind.It is deposited in data gind as shown in Fig. 2, calculating
In some elements with identical value, such as 3,8 and 13.It distributes when by gind to three thread Thread 0,1 and of Thread
When in Thread 2, element 3 appears in first position of thread Thread 0 Yu Thread 1, due to thread Thread 0 with
Thread 1 starts simultaneously at calculating, this will lead to the two threads and will be operated to the same memory address (because in gind
Identical element value is directed toward same memory address), i.e. memory access conflict between generation thread.
Summary of the invention
The place of in order to solve the above technical problem, the present invention provides a kind of astronomy software Gridding based on OpenMP
Reason method effectively overcomes and calculates the defect that circulation carries out memory access conflict between data division generation thread according to dind.
In order to reach the object of the invention, the place of the present invention provides a kind of astronomy software Gridding based on OpenMP
Reason method, comprising:
NT OpenMP thread is opened up, wherein nT is the total number of thread；
Suppv is calculated into circulation and is converted to the nT son calculating circulations executed parallel.
Further, it is described suppv calculated into circulation be converted to the son that nT is executed parallel and calculate circulation specifically include:
Array is divided into nT data block, distributes an OpenMP thread for each data block；
Bs is indexed for the starting that each OpenMP thread distributes data and terminates index be；
It is parallel to execute the nT suppv calculating circulations from bs to be.
Further, the parallel execution nT suppv from bs to be calculate in circulation, and a son calculates circulation tool
Body includes:
Suppv=bs is set；
Suppu=0 is set；
Calculate gind array；
Judge whether suppu is less than sSize, be then incremental suppu, re-executes and calculate gind array step, otherwise hold
Row next step；
Execute gind=gind+gSize；Cind=cind+sSize；
Judge whether suppv is less than be, be then incremental suppv, re-executes setting suppu=0 step, otherwise execute
Dind calculates circulation.
Further, described to open up nT OpenMP thread setting in suppv calculating circulation.
Further, described to open up nT OpenMP thread setting in dind calculating circulation.
The processing method of the present invention provides a kind of astronomy software Gridding based on OpenMP, for Gridding
The characteristics of core includes three re-computations circulation is calculated, multithreading setting is calculated in suppv and is recycled, it is ensured that different cross-threads
The data possessed be it is entirely different, the memory access collision problem during parallelization is avoided with this.Meanwhile OpenMP thread
Expansion and merging are placed on outermost circulation, cause additional load to avoid excessive the opening up and discharge of thread.The present invention
Method has the characteristics that high scalability, high efficiency, is easily achieved, and to the effectively optimizing of Gridding, can save huge calculating
Investment and daily expenditure of the entire project in terms of computing platform is greatly reduced in effective progress for pushing SKA research by amount, right
SKA project and world's astronomical community have very important significance.
Other features and advantages of the present invention will be illustrated in the following description, also, partly becomes from specification
It obtains it is clear that understand through the implementation of the invention.The objectives and other advantages of the invention can be by specification, right
Specifically noted structure is achieved and obtained in claim and attached drawing.
Detailed description of the invention
Attached drawing is used to provide to further understand technical solution of the present invention, and constitutes part of specification, with this
The embodiment of application technical solution for explaining the present invention together, does not constitute the limitation to technical solution of the present invention.
Fig. 1 is the program processing figure that Gridding calculates core；
Fig. 2 is to calculate the schematic diagram that circulation carries out data division according to dind；
Fig. 3 is the schematic diagram of the invention by convolutional calculation map procedures to two-dimensional grid；
Fig. 4 is that the present invention is based on the process flow diagrams of the processing method of the astronomy software Gridding of OpenMP；
Fig. 5 is the process flow diagram of the invention for calculating suppv and recycling and being converted to the son calculating circulation that nT execute parallel；
Fig. 6 is that the present invention is based on the processes of the processing method specific embodiment of the astronomy software Gridding of OpenMP
Figure.
Specific embodiment
To make the objectives, technical solutions, and advantages of the present invention clearer, below in conjunction with attached drawing to the present invention
Embodiment be described in detail.It should be noted that in the absence of conflict, in the embodiment and embodiment in the application
Feature can mutual any combination.
Step shown in the flowchart of the accompanying drawings can be in a computer system such as a set of computer executable instructions
It executes.Also, although logical order is shown in flow charts, and it in some cases, can be to be different from herein suitable
Sequence executes shown or described step.
The present invention provides a kind of new data division modes, calculate core for Gridding and recycle comprising three re-computations
The characteristics of, data are divided setting and recycled in middle layer by the present invention, i.e., multithreading are arranged and recycle in suppv calculating, avoid
Memory access conflict between thread efficiently solves and calculates memory access conflict between circulation progress data division generation thread according to dind
Defect.
Gridding according to figure 1, which calculates core process flow, can be seen that its suppu calculating circulation and suppv
Calculating circulation is actually to calculate convolution to samples array, and convolution kernels function is array C, the size of calculating be sSize ×
sSize.Fig. 3 is the schematic diagram of the invention by convolutional calculation map procedures to two-dimensional grid.As shown in figure 3, the present invention pass through by
The convolutional calculation map procedures carry out data division to two-dimensional grid, for calculating circulation in suppv, substantially along the two dimension
The traveling row data of grid divide, i.e., carry out data division along the direction suppv.After carrying out data division in this way, each thread
The task amount got is sSize/nT, and wherein nT is the total number of thread.The range calculated for i-th d thread, suppv
Are as follows:
It can be seen that according to data division mode proposed by the present invention, the data volume that each thread obtains is approximately equal, and each
The memory block that thread is assigned to is entirely different, is not overlapped between the memory block of each thread, therefore effectively prevents memory access conflict
Problem.
Fig. 4 is that the present invention is based on the process flow diagrams of the processing method of the astronomy software Gridding of OpenMP.Such as Fig. 4
Shown, processing method of the present invention includes:
Step 1 opens up nT OpenMP thread；
Suppv is calculated circulation and is converted to the son that nT is executed parallel and calculates circulation by step 2.
In actual use, the present invention shares memory parallel programming OpenMP (Open Multi-Processing) thread
Suppv can be both placed on by, which opening up, calculates circulation, can also be placed on dind and calculate circulation.For opening up OpenMP thread
It is placed on suppv and calculates circulation, the dind of outer layer calculates the circulation each time of circulation, and the thread of OpenMP then needs to open up and discharge
Once.In view of the number that dind calculates circulation is very more, it will lead to excessive thread and open up the cost discharged with thread, this hair
It is bright that preferably opening up for OpenMP thread is placed on dind and calculated in circulation, thread open up and thread release only once, from
And the expense of thread management is reduced to the full extent.
Suppv is calculated circulation and is converted in the son calculating circulation that nT execute parallel by the present invention, first by gind array
It is respectively divided into nT data block with cind array, an OpenMP thread is distributed for each data block, then calculates suppv
The size sSize of circulation is also divided into nT parts, makes the calculating in each thread by bs, be terminates.Wherein, OpenMP thread
Open up and discharge, array divide, for data block distribute OpenMP thread, OpenMP thread parallel execute etc. be all made of existing skill
Art means, which is not described herein again.
Fig. 5 is the process flow diagram of the invention for calculating suppv and recycling and being converted to the son calculating circulation that nT execute parallel.
As shown in Figure 5, comprising:
Gind array and cind array are respectively divided into nT data block by step 21, distribute one for each data block
OpenMP thread；
Step 22, the starting that data are distributed for each OpenMP thread index bs and terminate index be；
Step 23, parallel a suppv from bs to be of nT that executes calculate circulation.
In practical application, id first can be numbered to each OpenMP thread, be based on number id later, obtain each line
The starting index bs of data and termination index be in journey.
The processing method of the present invention provides a kind of astronomy software Gridding based on OpenMP, by well-designed
Method for parallel processing solve according to dind calculate circulation carry out data divide generate thread between memory access conflict defect.This
Invention calculates the characteristics of core includes three re-computations circulation for Gridding, and multithreading setting is calculated in suppv and is recycled, really
Protected the data that different cross-threads possesses be it is entirely different, the memory access collision problem during parallelization is avoided with this.
Meanwhile the expansion and merging of OpenMP thread are placed on outermost circulation, cause to avoid excessive the opening up and discharge of thread
Additional load.New data proposed by the present invention divide, and data are divided into muti-piece, each piece of size is approximately uniform, each
A OpenMP thread gets its corresponding one piece according to the thread number of itself, and number is written to the unique memory headroom of cross-thread
According to not only ensuring that the data volume that each thread obtains is approximately equal, and the data for ensuring that each thread possesses do not repeat, greatly
Improve the parallel performance of Gridding program.The method of the present invention has the characteristics that high scalability, high efficiency, is easily achieved.
Fig. 6 is that the present invention is based on the processes of the processing method specific embodiment of the astronomy software Gridding of OpenMP
Figure.Through this embodiment, it can clearly illustrate technical solution of the present invention.As shown in fig. 6, the present embodiment includes:
Step 31 opens up nT OpenMP thread；
Step 32, setting dind=0；
Step 33 calculates gind array and cind array；
Gind array and cind array are respectively divided into nT data block by step 34, distribute one for each data block
OpenMP thread；
Step 35, the starting that data are distributed for each OpenMP thread index bs and terminate index be；
Step 36, setting suppv=bs；
Step 37, setting suppu=0；
Step 38 calculates gind array；
Step 39 judges whether suppu is less than sSize, is that then incremental suppu, execution step 38 are no to then follow the steps
40；
Step 40 executes gind=gind+gSize；Cind=cind+sSize；
Step 41 judges whether suppv is less than be, is that then incremental suppv, execution step 37 are no to then follow the steps 42；
Step 42 judges whether dind is less than int (samples size ()), is then incremental dind, executes step 33,
It is no to then follow the steps 43；
Step 43 terminates.
Wherein, step 36~step 41 is that nT OpenMP thread parallel executes.
So far the processing that astronomy software Gridding calculates core is completed, using method of the invention, in multithreading
In the case of, the promotion of Gridding performance is approximately linearly, close to theoretical performance.
Although disclosed herein embodiment it is as above, the content only for ease of understanding the present invention and use
Embodiment is not intended to limit the invention.Technical staff in any fields of the present invention is taken off not departing from the present invention
Under the premise of the spirit and scope of dew, any modification and variation, but the present invention can be carried out in the form and details of implementation
Scope of patent protection, still should be subject to the scope of the claims as defined in the appended claims.
Claims (1)
1. a kind of processing method of the astronomy software Gridding based on OpenMP, it includes that three calculating follow that Gridding, which is calculated,
Ring, outermost dind calculate circulation, and intermediate suppv calculates circulation, and innermost suppu calculates circulation, which is characterized in that
Data are divided into setting and calculate circulation in suppv, comprising:
Circulation is calculated in dind and opens up nT OpenMP thread, and wherein nT is the total number of thread；
Suppv is calculated into circulation and is converted to the nT son calculating circulations executed parallel, comprising: array is divided into nT data
Block distributes an OpenMP thread for each data block；The starting for distributing data for each OpenMP thread indexes bs and termination
Index be；It is parallel to execute the nT suppv calculating circulations from bs to be；
The parallel execution nT suppv from bs to be calculate in circulation, and a son calculates circulation and specifically includes:
Suppv=bs is set；
Suppu=0 is set；
Calculate gind array；
Judge whether suppu is less than sSize, be then incremental suppu, re-execute and calculate gind array step, under otherwise executing
One step；
Execute gind=gind+gSize；Cind=cind+sSize；
Judge whether suppv is less than be, be then incremental suppv, re-execute setting suppu=0 step, otherwise executes dind meter
Calculate circulation.
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| CN106897131B (en) * | 2017-02-22 | 2020-05-29 | 浪潮(北京)电子信息产业有限公司 | Parallel computing method and device for astronomical software Griding |
| CN107908477A (en) * | 2017-11-17 | 2018-04-13 | 郑州云海信息技术有限公司 | A kind of data processing method and device for radio astronomy data |
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| CN102707955A (en) * | 2012-05-18 | 2012-10-03 | 天津大学 | Method for realizing support vector machine by MPI programming and OpenMP programming |
| CN104035781A (en) * | 2014-06-27 | 2014-09-10 | 北京航空航天大学 | Method for quickly developing heterogeneous parallel program |
| CN104375838A (en) * | 2014-11-27 | 2015-02-25 | 浪潮电子信息产业股份有限公司 | OpenMP-based astronomy software Gridding optimization method |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN102707955A (en) * | 2012-05-18 | 2012-10-03 | 天津大学 | Method for realizing support vector machine by MPI programming and OpenMP programming |
| CN104035781A (en) * | 2014-06-27 | 2014-09-10 | 北京航空航天大学 | Method for quickly developing heterogeneous parallel program |
| CN104375838A (en) * | 2014-11-27 | 2015-02-25 | 浪潮电子信息产业股份有限公司 | OpenMP-based astronomy software Gridding optimization method |
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