CN109583071A - A kind of parallel optimization method and system based on cloud emulation - Google Patents
A kind of parallel optimization method and system based on cloud emulation Download PDFInfo
- Publication number
- CN109583071A CN109583071A CN201811405957.9A CN201811405957A CN109583071A CN 109583071 A CN109583071 A CN 109583071A CN 201811405957 A CN201811405957 A CN 201811405957A CN 109583071 A CN109583071 A CN 109583071A
- Authority
- CN
- China
- Prior art keywords
- simulation
- software
- cloud
- optimization
- emulation
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
Abstract
The embodiment of the present application provides a kind of parallel optimization method and system based on cloud emulation, wherein the step of this method includes: to be virtualized based on computing system, carries out the building of cloud simulation modular to single group simulation software；Based on cloud simulation modular, multiple groups simulation software example is created；Multiple groups simulation software example is associated with optimization software, completes the parallel optimization of software.Herein described technical solution can be improved the efficiency of simulation software (group) deployment, and user only needs one group of simulation software of installation and deployment, so that it may according to the needs of optimization software, emulate other groups of simulation software examples of automatic deployment by cloud.When the example required for parallel optimization is more, efficiency is higher.
Description
Technical field
This application involves intelligent simulation field, in particular to a kind of parallel optimization method and system based on cloud emulation.
Background technique
Currently, many optimisation techniques all use parallel optimization.Such as Swarm Intelligent Algorithm and relevant improvement are calculated
Method is arranged multiple examples and carries out optimizing parallel in solution space, using the information sharing between example each in group to optimal solution,
So that the direction of search of entire group generates the evolutionary process from disorder to order in solution space.Also such as collateral learning is each
The neural network model of multiple examples is arranged in class algorithm, carries out model instruction on different data sets respectively using each example
Practice, finally each model parameter is integrated in reasonable time to obtain the parameter of final mask.
Due to the complexity of optimization problem, the calculating of solution space at present or the generation of training dataset are required to call and be imitated
True software is calculated.Such as ISIGHT software multidisciplinary optimization software is provided special with a variety of mainstream CAE analysis tools
With interface, user is supported visually quickly to establish simulation analysis process in a manner of pulling, and easily setting and modification are set
Variable and design constraint and target are counted, it is automatic to carry out repeatedly analysis circulation.
But the multidisciplinary optimizations such as ISIGHT software software is mainly still serially optimized.The simulation analysis that they are established
It is single simulation software example that process links are associated, and it is good that these simulation software examples by user shift to an earlier date manually dispose.Such as
Fruit needs to carry out parallel optimization, needs user to dispose a lot of group simulation software examples in advance, and in simulation analysis process in advance
Relationship between the relationship and each group simulation software example and optimization software of good each Zu Zu simulation software example is described.And
And these relationships be it is cured, if necessary to increase parallel optimization example number, it is also necessary to redeploy and again change stream
Journey carries out parallel optimization to user and causes big inconvenience.
Summary of the invention
One of in order to solve the above problem, this application provides a kind of parallel optimization methods based on cloud emulation.
According to the first aspect of the embodiment of the present application, a kind of parallel optimization method based on cloud emulation, the party are provided
The step of method includes:
It is virtualized based on computing system, constructs the cloud simulation modular of single group simulation software；
Based on cloud simulation modular, multiple groups simulation software example is created；
Multiple groups simulation software example is associated with optimization software, completes the parallel optimization of software.
Preferably, described to be virtualized based on computing system, the step of cloud simulation modular constructs is carried out to single group simulation software
Include:
The single group simulation run established in cloud simulation modular relies on environmental encapsulation template, and the basis for installing multiple nodes is soft
Part installs the simulation software of different subjects on different nodes, and carries out demand to computing resource, storage resource and Internet resources
Description；
The single group emulation collaboration established in cloud simulation modular relies on environmental encapsulation template, installation multidisciplinary collaboration emulation support
Software, and multidisciplinary collaboration artificial service is described.
Preferably, described the step of being based on cloud simulation modular, creating multiple groups simulation software example, includes:
Based on the cloud simulation modular, computing resource needed for distributing, storage resource and Internet resources, in multiple sections of distribution
It is soft to form single group emulation to point for starting basic software and corresponding simulation software, starting multidisciplinary collaboration artificial supporting software above
Part example；
Based on the cloud simulation modular, previous step is repeated, creates multiple groups simulation software example.
Preferably, described the step of being based on cloud simulation modular, creating multiple groups simulation software example further include:
Multiple groups simulation software example is isolated using computing system virtualization technology.
Preferably, described to be associated multiple groups simulation software example with optimization software, complete the parallel optimization of software
Step includes:
The connection of each group simulation software example and optimization software is established by gateway, realizes each group multidisciplinary collaboration emulation branch
Support the integrated of software and optimization software；
Optimization software is assigned design parameter and is given each group simulation software reality based on integrated multidisciplinary collaboration artificial supporting software
Example calls multi-disciplinary simulation software inside each group to carry out collaborative simulation analysis, collects simulation analysis as a result, obtaining corresponding design
The result of parameter is fed back.
Preferably, step further include: according to Optimized Operation, iterate, obtain optimal optimum results.
According to the second aspect of the embodiment of the present application, a kind of parallel optimization system based on cloud emulation is provided, this is
System includes:
Simulation modular management module is virtualized based on computing system, constructs the cloud simulation modular of single group simulation software；
Simulation example creation module is based on cloud simulation modular, creates multiple groups simulation software example；
Optimize driving simulation scheduler module, multiple groups simulation software example is associated with optimization software, completes software
Parallel optimization.
Preferably, the template building module specifically executes following steps:
The single group simulation run established in cloud simulation modular relies on environmental encapsulation template, and the basis for installing multiple nodes is soft
Part installs the simulation software of different subjects on different nodes, and carries out demand to computing resource, storage resource and network and retouch
It states；
The single group emulation collaboration established in cloud simulation modular relies on environmental encapsulation template, installation multidisciplinary collaboration emulation support
Software, and multidisciplinary collaboration artificial service is described.
Preferably, which specifically executes following steps:
Based on the cloud simulation modular, computing resource needed for distributing, storage resource and Internet resources；
Start basic software and corresponding simulation software, starting multidisciplinary collaboration emulation branch on multiple nodes of distribution
Software is supportted, single group simulation software example is formed；
Based on the cloud simulation modular, previous step is repeated, creates multiple groups simulation software example.
Preferably, the association emulation module specifically executes following steps:
The connection of each group simulation software example and optimization software is established by gateway, realizes each group multidisciplinary collaboration emulation branch
Support the integrated of software and optimization software；
Optimization software is assigned design parameter and is given each group simulation software reality based on integrated multidisciplinary collaboration artificial supporting software
Example calls multi-disciplinary simulation software inside each group to carry out collaborative simulation analysis, collects simulation analysis as a result, obtaining corresponding design
The result of parameter is fed back.
Herein described technical solution can be improved the efficiency of simulation software (group) deployment, and user only needs installation and deployment
One group of simulation software, so that it may according to the needs of optimization software, other groups of simulation software examples of automatic deployment be emulated by cloud.When
When example required for parallel optimization is more, efficiency is higher.
Herein described technical solution provides more Case Simulation analysis process of flexibility under parallel optimization frame, and user is only
Need to describe the simulation analysis process of one group of simulation software example, so that it may according to the needs of parallel optimization, certainly by cloud emulation
The dynamic multiple example type for realizing simulation analysis process.User does not need additional process change, convenient and efficient；It supports high based on emulation
Effect carries out swarm intelligence optimization and parallel machine study.
Detailed description of the invention
The drawings described herein are used to provide a further understanding of the present application, constitutes part of this application, this Shen
Illustrative embodiments and their description please are not constituted an undue limitation on the present application for explaining the application.In the accompanying drawings:
Fig. 1 shows the schematic diagram of a kind of herein described parallel optimization method based on cloud emulation.
Specific embodiment
In order to which technical solution in the embodiment of the present application and advantage is more clearly understood, below in conjunction with attached drawing to the application
Exemplary embodiment be described in more detail, it is clear that described embodiment be only the application a part implement
Example, rather than the exhaustion of all embodiments.It should be noted that in the absence of conflict, embodiment and reality in the application
The feature applied in example can be combined with each other.
The core ideas of this programme is to carry out more Case Simulation analysis process of flexibility under parallel optimization frame, is used
Family only needs to describe the simulation analysis process of one group of simulation software example, so that it may imitative by cloud according to the needs of parallel optimization
Very automatically realize simulation analysis process multiple example type, thus solve multiple groups simulation software example automatically create and with optimize it is soft
The problem of part auto-associating.
Embodiment 1
As shown in Figure 1, this example discloses a kind of parallel optimization method based on cloud emulation, the step of this method, includes:
Step 1 is virtualized based on computing system, constructs the cloud simulation modular of single group simulation software.Wherein, the cloud emulation
Template includes: that the operation of single group simulation software relies on environmental encapsulation template and single group simulation software collaboration dependence environmental encapsulation template.
In the step, firstly, the single group simulation run established in cloud simulation modular relies on environmental encapsulation template, the base of multiple nodes is installed
Plinth software is installed the simulation software of different subjects on different nodes, and is carried out to computing resource, storage resource and Internet resources
Requirement description；Wherein, computing resource includes the resources such as CPU, memory and storage.In addition, basic software respective operations system is (such as
Windows, Linux etc.), run-time library (library C++, the library .Net etc.)；Simulation software corresponds to CAE, EDA, and these come from different subjects
Simulation software.Secondly, the single group emulation collaboration established in cloud simulation modular relies on environmental encapsulation template, multidisciplinary collaboration is installed
Artificial supporting software, and multidisciplinary collaboration artificial service is described；Wherein, collaborative simulation business includes data interaction relationship
With temporal and logic relation etc..It wherein, is more typically RTI (Run-time in multidisciplinary collaboration artificial supporting software
Infrastructure)
Step 2 is based on cloud simulation modular, creates multiple groups simulation software example.In the step, firstly, imitative based on the cloud
True template, computing resource needed for distributing, storage resource and Internet resources, start on multiple nodes of distribution basic software and
Corresponding simulation software starts multidisciplinary collaboration artificial supporting software, forms single group simulation software example；Then, based on described
Cloud simulation modular repeats previous step, creates multiple groups simulation software example.In this example, computing system virtualization can use
Multiple groups simulation software example is isolated in technology.
Multiple groups simulation software example and optimization software are associated by step 3, complete the parallel optimization of software.Firstly, logical
Cross the connection that gateway establishes each group simulation software example and optimization software, realize each group multidisciplinary collaboration artificial supporting software with it is excellent
Change the integrated of software；Then, optimization software assigns design parameter to each group based on integrated multidisciplinary collaboration artificial supporting software
Simulation software example calls multi-disciplinary simulation software inside each group to carry out collaborative simulation analysis, collects simulation analysis as a result, obtaining
The result feedback of design parameter must be corresponded to.
A kind of parallel optimization system based on cloud emulation is further provided in this example, which includes:
Simulation modular management module is virtualized based on computing system, constructs the cloud simulation modular of single group simulation software；It is described
Template building module specifically executes following steps: the single group simulation run established in cloud simulation modular relies on environmental encapsulation template,
The basic software of multiple nodes is installed, the simulation software of different subjects is installed on different nodes, and provide to computing resource, storage
Source and Internet resources carry out requirement description；The single group emulation collaboration established in cloud simulation modular relies on environmental encapsulation template, installation
Multidisciplinary collaboration artificial supporting software, and multidisciplinary collaboration artificial service is described.
Simulation example creation module is based on cloud simulation modular, creates multiple groups simulation software example；Example creation module tool
Body executes following steps: being based on the cloud simulation modular, computing resource needed for distributing, storage resource and Internet resources are distributing
Multiple nodes above start basic software and corresponding simulation software, start multidisciplinary collaboration artificial supporting software, formed single
Group simulation software example；Based on the cloud simulation modular, previous step is repeated, creates multiple groups simulation software example.
Optimize driving simulation scheduler module, multiple groups simulation software example is associated with optimization software, completes software
Parallel optimization.The association emulation module specifically executes following steps: establishing each group simulation software example and optimization by gateway
The connection of software, realization each group multidisciplinary collaboration artificial supporting software and optimization software integrate；Optimization software is based on integrated
Multidisciplinary collaboration artificial supporting software assigns design parameter and gives each group simulation software example, calls multi-disciplinary imitative inside each group
True software carries out collaborative simulation analysis, collects simulation analysis as a result, obtaining the result feedback of corresponding design parameter.
Herein described technical solution can be improved the efficiency of simulation software (group) deployment, and user only needs installation and deployment
One group of simulation software, so that it may according to the needs of optimization software, other groups of simulation software examples of automatic deployment be emulated by cloud.When
When example required for parallel optimization is more, efficiency is higher.Herein described technical solution provides flexible under parallel optimization frame
The more Case Simulation analysis process changed, user only need to describe the simulation analysis process of one group of simulation software example, so that it may root
According to the needs of parallel optimization, the automatic multiple example type for realizing simulation analysis process is emulated by cloud.User does not need additional stream
Cheng Genggai, it is convenient and efficient.
Embodiment 2
A kind of parallel optimization method based on cloud emulation is present embodiments provided, this method can be realized by electronic equipment
Its corresponding function, the electronic equipment include: memory, one or more processors；Memory and processor pass through communication bus
It is connected；Processor is configured as executing the instruction in memory；It is stored in the storage medium for executing side as described above
The instruction of each step in method.This method can also realize device corresponding function by computer storage medium, and this computer can
It reads to be stored with computer program on storage medium, which realizes each step of method as described above when being executed by processor.
It can specifically implement in accordance with the following steps:
The first step establishes the cloud simulation modular of single group simulation software
It is virtualized based on computing system, the encapsulation of cloud simulation modular is carried out to single group simulation software.Cloud simulation modular encapsulation package
It includes the operation of single group simulation software and relies on environmental encapsulation and single group simulation software collaboration dependence environmental encapsulation.The former includes to required
The installation of the operation depended software such as the requirement description of the computing resources such as CPU, memory, storage and operating system；The latter includes pair
The description of the collaborative simulations business such as data interaction relationship and temporal and logic relation and as flow engine software or HLA RTI it is soft
The installation of the collaboration depended software such as part.
Second step is based on cloud emulation and automatically creates multiple groups simulation software example
Multiple groups simulation software example is automatically created on demand based on cloud emulation.The operation packet of one group of simulation software example of every creation
It includes, distributes required computing resource automatically according to the requirement description of the computing resources such as required CPU, memory, storage, cloud is emulated
Template is instantiated on the computing resource of distribution, and start-up operation system etc. runs depended software and such as flow engine software
Or HLA RTI software etc. cooperates with depended software, finally each simulation software in starting group, and establishes each group simulation software example
Between be effectively isolated.
Third step establishes the auto-associating of each group simulation software example and optimization software
The connection of each group mutually isolated simulation software example and optimization software is established by gateway, realizes association inside each group
With the integrated of depended software and optimization software, optimization software is supported to give each group emulation by cooperateing with depended software to assign design parameter
Software instances support collaboration depended software to call simulation software inside each group to carry out simulation analysis according to sequential logic, support association
Simulation analysis result is collected with depended software and feeds back to optimization software, supports iterating for the above process.Wherein, for branch
Hold collaboration depended software according to sequential logic call each group inside simulation software carry out simulation analysis can be it is soft by flow engine
Part is scheduled according to simulation analysis process or HLA RTI software is adjusted according to Time Advance Mechanism and Data Dissemination
Degree.
In the present embodiment, it can realize that more examples are excellent parallel by Cloud Server, simulation run time management device and optimizer etc.
Change.It is possible, firstly, to construct the cloud simulation modular of single group simulation software using computing system virtualization technology, be stored in cloud service
In device；Then, need to utilize cloud simulation modular stored in cloud server creation relevant to simulation object more according to emulation
Group simulation software example, using simulation run time management device to visualization, control condition, dynamic condition, etc. simulation run project
It is managed scheduling；Further, the connection that each group simulation software example and optimization software are established by gateway, makes inside each group
The integrated of cloud simulation modular and optimization software cooperates with the integrated of depended software and optimization software；Optimization software is according to integrated collaboration
Depended software carries out simulation analysis, simulation result is collected and simulation result feedback；Finally, being changed repeatedly according to emulation dispatch
In generation, obtains optimal optimum results.
This programme improves the efficiency of simulation software (group) deployment, as soon as user only needs installation and deployment group simulation software,
Other groups of simulation software examples of automatic deployment can be emulated by cloud according to the needs of optimization software.Required for parallel optimization
Example it is more when, efficiency is higher.In addition, more Case Simulations that this programme provides flexibility under parallel optimization frame analyze stream
Journey, user only need to describe the simulation analysis process of one group of simulation software example, so that it may which volume leads to according to the needs of parallel optimization
Cross the automatic multiple example type for realizing simulation analysis process of cloud emulation.User does not need additional process change, convenient and efficient.
The application is referring to method, the process of equipment (system) and computer program product according to the embodiment of the present application
Figure and/or block diagram describe.It should be understood that every one stream in flowchart and/or the block diagram can be realized by computer program instructions
The combination of process and/or box in journey and/or box and flowchart and/or the block diagram.It can provide these computer programs
Instruct the processor of general purpose computer, special purpose computer, Embedded Processor or other programmable data processing devices to produce
A raw machine, so that being generated by the instruction that computer or the processor of other programmable data processing devices execute for real
The device for the function of being specified in present one or more flows of the flowchart and/or one or more blocks of the block diagram.
These computer program instructions, which may also be stored in, is able to guide computer or other programmable data processing devices with spy
Determine in the computer-readable memory that mode works, so that it includes referring to that instruction stored in the computer readable memory, which generates,
Enable the manufacture of device, the command device realize in one box of one or more flows of the flowchart and/or block diagram or
The function of being specified in multiple boxes.
These computer program instructions also can be loaded onto a computer or other programmable data processing device, so that counting
Series of operation steps are executed on calculation machine or other programmable devices to generate computer implemented processing, thus in computer or
The instruction executed on other programmable devices is provided for realizing in one or more flows of the flowchart and/or block diagram one
The step of function of being specified in a box or multiple boxes.
The above is only the embodiment of the present invention, are not intended to restrict the invention, all in the spirit and principles in the present invention
Within, any modification, equivalent substitution, improvement and etc. done, be all contained in apply pending scope of the presently claimed invention it
It is interior.
Claims (10)
1. a kind of parallel optimization method based on cloud emulation, which is characterized in that the step of this method includes:
It is virtualized based on computing system, constructs the cloud simulation modular of single group simulation software；
Based on cloud simulation modular, multiple groups simulation software example is created；
Multiple groups simulation software example is associated with optimization software, completes the parallel optimization of software.
2. the parallel optimization method according to claim 1 based on cloud emulation, which is characterized in that described to be based on computing system
Virtualization, carrying out the step of cloud simulation modular constructs to single group simulation software includes:
The single group simulation run established in cloud simulation modular relies on environmental encapsulation template, installs the basic software of multiple nodes,
The simulation software of different subjects is installed on different nodes, and requirement description is carried out to computing resource, storage resource and Internet resources；
The single group emulation collaboration established in cloud simulation modular relies on environmental encapsulation template, and installation multidisciplinary collaboration emulation support is soft
Part, and multidisciplinary collaboration artificial service is described.
3. the parallel optimization method according to claim 2 based on cloud emulation, which is characterized in that described to emulate mould based on cloud
Plate, create multiple groups simulation software example the step of include:
Based on the cloud simulation modular, computing resource needed for distributing, storage resource and Internet resources, on multiple nodes of distribution
Face starts basic software and corresponding simulation software, starts multidisciplinary collaboration artificial supporting software, and it is real to form single group simulation software
Example；
Based on the cloud simulation modular, previous step is repeated, creates multiple groups simulation software example.
4. the parallel optimization method according to claim 3 based on cloud emulation, which is characterized in that described to emulate mould based on cloud
The step of plate, creation multiple groups simulation software example further include:
Multiple groups simulation software example is isolated using computing system virtualization technology.
5. it is according to claim 3 based on cloud emulation parallel optimization method, which is characterized in that it is described multiple groups are emulated it is soft
The step of part example is associated with optimization software, completes the parallel optimization of software include:
The connection of each group simulation software example and optimization software is established by gateway, realizes that the emulation support of each group multidisciplinary collaboration is soft
Part and optimization software it is integrated；
Optimization software is assigned design parameter and is given each group simulation software example based on integrated multidisciplinary collaboration artificial supporting software,
It calls multi-disciplinary simulation software inside each group to carry out collaborative simulation analysis, collects simulation analysis as a result, obtaining corresponding design ginseng
Several result feedbacks.
6. the parallel optimization method according to claim 5 based on cloud emulation, which is characterized in that the step further include: root
It according to Optimized Operation, iterates, obtains optimal optimum results.
7. a kind of parallel optimization system based on cloud emulation, which is characterized in that the system includes:
Simulation modular management module is virtualized based on computing system, constructs the cloud simulation modular of single group simulation software；
Simulation example creation module is based on cloud simulation modular, creates multiple groups simulation software example；
Optimize driving simulation scheduler module, multiple groups simulation software example is associated with optimization software, completes the parallel of software
Optimization.
8. parallel optimization system according to claim 7, which is characterized in that the template building module specifically executes as follows
Step:
The single group simulation run established in cloud simulation modular relies on environmental encapsulation template, installs the basic software of multiple nodes,
The simulation software of different subjects is installed on different nodes, and requirement description is carried out to computing resource, storage resource and network；
The single group emulation collaboration established in cloud simulation modular relies on environmental encapsulation template, and installation multidisciplinary collaboration emulation support is soft
Part, and multidisciplinary collaboration artificial service is described.
9. parallel optimization system according to claim 8, which is characterized in that the example creation module specifically executes following step
It is rapid:
Based on the cloud simulation modular, computing resource needed for distributing, storage resource and Internet resources；
Start basic software and corresponding simulation software on multiple nodes of distribution, starting multidisciplinary collaboration emulation support is soft
Part forms single group simulation software example；
Based on the cloud simulation modular, previous step is repeated, creates multiple groups simulation software example.
10. parallel optimization system according to claim 9, which is characterized in that the association emulation module specifically executes such as
Lower step:
The connection of each group simulation software example and optimization software is established by gateway, realizes that the emulation support of each group multidisciplinary collaboration is soft
Part and optimization software it is integrated；
Optimization software is assigned design parameter and is given each group simulation software example based on integrated multidisciplinary collaboration artificial supporting software,
It calls multi-disciplinary simulation software inside each group to carry out collaborative simulation analysis, collects simulation analysis as a result, obtaining corresponding design ginseng
Several result feedbacks.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811405957.9A CN109583071B (en) | 2018-11-23 | 2018-11-23 | Parallel optimization method and system based on cloud simulation |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811405957.9A CN109583071B (en) | 2018-11-23 | 2018-11-23 | Parallel optimization method and system based on cloud simulation |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN109583071A true CN109583071A (en) | 2019-04-05 |
| CN109583071B CN109583071B (en) | 2023-09-15 |
Family
ID=65924242
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201811405957.9A Active CN109583071B (en) | 2018-11-23 | 2018-11-23 | Parallel optimization method and system based on cloud simulation |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109583071B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110991040A (en) * | 2019-12-02 | 2020-04-10 | 北京仿真中心 | Complex product collaborative simulation environment construction method |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105843665A (en) * | 2015-01-13 | 2016-08-10 | 北京仿真中心 | Virtual prototype system building and operation method based on cloud simulation technique |
| US20160357885A1 (en) * | 2015-06-04 | 2016-12-08 | International Business Machines Corporation | Hybrid simulation in a cloud computing environment |
| CN106250204A (en) * | 2016-07-21 | 2016-12-21 | 北京理工大学 | A kind of optimizer developing plug method of multidisciplinary optimization simulation software |
| CN108021446A (en) * | 2017-11-24 | 2018-05-11 | 北京动力机械研究所 | A kind of cloud service of simulation association and resource scheduling system |
-
2018
- 2018-11-23 CN CN201811405957.9A patent/CN109583071B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105843665A (en) * | 2015-01-13 | 2016-08-10 | 北京仿真中心 | Virtual prototype system building and operation method based on cloud simulation technique |
| US20160357885A1 (en) * | 2015-06-04 | 2016-12-08 | International Business Machines Corporation | Hybrid simulation in a cloud computing environment |
| CN106250204A (en) * | 2016-07-21 | 2016-12-21 | 北京理工大学 | A kind of optimizer developing plug method of multidisciplinary optimization simulation software |
| CN108021446A (en) * | 2017-11-24 | 2018-05-11 | 北京动力机械研究所 | A kind of cloud service of simulation association and resource scheduling system |
Non-Patent Citations (2)
| Title |
|---|
| 周际锋 等: ""云环境下的多学科设计优化研究"", 《机械设计与制造》 * |
| 毛虎平 等: ""基于多领域仿真的SQP并行优化算法"", 《中国机械工程》 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110991040A (en) * | 2019-12-02 | 2020-04-10 | 北京仿真中心 | Complex product collaborative simulation environment construction method |
Also Published As
| Publication number | Publication date |
|---|---|
| CN109583071B (en) | 2023-09-15 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| JP6937357B2 (en) | Data processing methods and related products | |
| US11614927B2 (en) | Off-load servers software optimal placement method and program | |
| CN105447643B (en) | Scientific workflow system and method for cloud computing platform | |
| US20200042856A1 (en) | Scheduler for mapping neural networks onto an array of neural cores in an inference processing unit | |
| CN110780914B (en) | Service publishing method and device | |
| CN103955373B (en) | A kind of method for designing of SDN application integration development environment | |
| US10977076B2 (en) | Method and apparatus for processing a heterogeneous cluster-oriented task | |
| CN107423823B (en) | R language-based machine learning modeling platform architecture design method | |
| CN113032963A (en) | Simulink model simulation acceleration method and device | |
| US11055139B2 (en) | Smart accelerator allocation and reclamation for deep learning jobs in a computing cluster | |
| CN105607952A (en) | Virtual resource scheduling method and apparatus | |
| CN110532044A (en) | A kind of big data batch processing method, device, electronic equipment and storage medium | |
| US20230118325A1 (en) | Method and apparatus having a memory manager for neural networks | |
| CN112541836A (en) | Multi-energy system digital twin application process modeling and deployment method and system | |
| CN109583071A (en) | A kind of parallel optimization method and system based on cloud emulation | |
| CN105207215B (en) | A kind of electric load dispatch control method | |
| Menard et al. | Mocasin—rapid prototyping of rapid prototyping tools: A framework for exploring new approaches in mapping software to heterogeneous multi-cores | |
| CN114565102A (en) | Method, electronic device and computer program product for deploying machine learning model | |
| CN104778320A (en) | Configurable HLA (high level architecture) federal member construction method and configurable HLA federal member construction system | |
| Stier et al. | Ensuring model continuity when simulating self-adaptive software systems | |
| CN110290206A (en) | A kind of distributed computing system and method for cafe environment | |
| CN110515595A (en) | A kind of Resource Modeling and management method of aviation electronics distributed management system | |
| Nägele et al. | Scalability analysis of cloud-based distributed simulations of IoT systems using HLA | |
| Nadeem et al. | Task scheduling in large-scale distributed systems utilizing partial reconfigurable processing elements | |
| Menard et al. | Mocasin—Rapid Prototyping of Rapid Prototyping Tools |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |