CN108664729A - A kind of GROMACS cloud computings flow control method - Google Patents
A kind of GROMACS cloud computings flow control method Download PDFInfo
- Publication number
- CN108664729A CN108664729A CN201810443967.5A CN201810443967A CN108664729A CN 108664729 A CN108664729 A CN 108664729A CN 201810443967 A CN201810443967 A CN 201810443967A CN 108664729 A CN108664729 A CN 108664729A
- Authority
- CN
- China
- Prior art keywords
- gromacs
- task
- called
- temperature
- energy
- 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
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/10—Protocols in which an application is distributed across nodes in the network
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
- G06F2119/06—Power analysis or power optimisation
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Computer Hardware Design (AREA)
- Evolutionary Computation (AREA)
- Geometry (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The present invention provides a kind of GROMACS cloud computings flow control method, including following steps:Step(1):From ArangoDB databases .res the or .cif files for the forward several crystal structures of energy that cluster ranking obtains are obtained, the structured file of GROMACS is then obtained;Step(2):From ArangoDB databases, the best force field parameter .prm and .rtf that field of force developmental research obtains is obtained, yoda library functions is then called to be automatically converted into the force field parameter file of GROMACS;Step(3):According to the corresponding analog type of different phase, yoda library functions is called to automatically generate the analog parameter file of corresponding GROMACS;Step(4):Mixc library functions are called, GROMACS is calculated and analysis task is submitted to Majorana task scheduling platforms;Step(5)Corresponding monitor task is added to the corresponding same batch task of each structure, obtains the execution state of task in real time;Step(6)After the completion of waiting for that all tasks are carried out, corresponding analysis result is obtained from ArangoDB databases, matplotlib draw libraries is called, corresponding curve is directly made in jupyter.
Description
Technical field
The invention belongs to high-throughput GROMACS scientific algorithms fields, are related to a kind of GROMACS cloud computings Row control side
Method.
Background technology
Molecular dynamics (MD) calculates the every field for being widely used in material science, and GROMACS is opened as one
Source, efficient MD software for calculation, it has also become simulate the first choice of calculating.Currently, almost all of super calculation center and cloud platform are all pacified
The GROMACS softwares of all kinds of versions have been filled, and have had corresponding job management system come the submission, modification and deletion etc. of completing task
Function.
Current GROMACS cloud computing flows are primarily present following defect:
1. cross-platform cannot dispatch:Current almost all of GROMACS cloud computing platforms are required for first manual entry, write and appoint
Business script, then be submitted on respective platform and calculate.
2. being unable to Continuous plus:The follow-up work of general GROMACS is required for using the final structure of a task,
Therefore continuous task such as is required for could submit at the previous task computation completion.
3. storage form is single:All GROMACS are calculated and analysis result is stored on platform, are unfavorable for looking into real time
See and monitor emulation mode.
4. lacking user interface:Current all GROMACS cloud computings and analysis process are all based on the form of script, use
Family experience is poor, be unfavorable for task status monitor, the graphic software platform etc. of result.
Invention content
In order to solve the above technical problems, the present invention provides a kind of GROMACS cloud computings flow control method, including it is following
Several steps:
Step(1):From ArangoDB databases, the .res for the forward several crystal structures of energy that cluster ranking obtains is obtained
Or .cif files, it then calls yoda library functions to carry out symmetry operation, format conversion and structure cell extension, obtains GROMACS's
Structured file;
Step(2):From ArangoDB databases, the best force field parameter .prm and .rtf that field of force developmental research obtains is obtained, so
Yoda library functions are called to be automatically converted into the force field parameter file of GROMACS afterwards;
Step(3):According to the corresponding analog type of different phase, yoda library functions is called to automatically generate corresponding GROMACS's
Analog parameter file;
Step(4):Mixc library functions are called, GROMACS is calculated and analysis task is submitted to Majorana task scheduling platforms;
Step(5)Corresponding monitor task is added to the corresponding same batch task of each structure, obtains the execution shape of task in real time
State;
(6)After the completion of waiting for that all tasks are carried out, corresponding analysis result is obtained from ArangoDB databases, is called
Matplotlib draw libraries directly make corresponding curve in jupyter.
In the prior art, 3 class files necessary to GROMACS simulations include:Structure(.gro), force field parameter(.top and
.itp)And analog parameter(.mdp).The present invention is the temperature stability calculating for the crystal in the pre- flow gauge of crystal form(Free energy
It calculates).Wherein, cluster ranking results of the architectural source in the pre- flow gauge of crystal form(And .cif .res), force field parameter derives from
Result of calculation is developed in the field of force, and analog parameter is then with reference to existing document report and relevant test and optimum results(Base
In different analog types, corresponding Parameter File is automatically generated).Therefore in seamless connection of the present invention crystal form pre- flow gauge
Field of force exploitation, cluster ranking and free energy calculate.
The present invention uses above technical scheme, can solve platform login, mission script is write, analyzes script edit, appoints
Cross-platform and software the tedious steps such as business monitoring, analysis map data, Jupyter is all integrated by all user's operations
In, to substantially increase the efficiency of calculating and analysis.
Preferably, the task parameters are using at least one of task type, mirror image name, memory and check figure.
Preferably, the task type uses MD or REMD.
Preferably, the step(5)In, the operating status includes:In normal termination, failure, preparation, it is lined up in neutralization
Deposit at least one of deficiency.
Correspondingly, the present invention also provides a kind of, the copy based on the GROMACS cloud computings exchanges molecular dynamics flow
Method, including the following steps:
Step is 1.:It is ranked from cluster and chooses the lower crystal structure of N number of energy in result of calculation, after transform format surpasses born of the same parents with extension
Obtain corresponding GROMACS structures;Wherein, the lower crystal structure of N number of energy refers to that energy ranks 5 to 10 forward structures
Step is 2.:Optimal force field parameter is chosen, the isothermal and isobaric relaxation of 1ns is carried out to above-mentioned each structure;It is described optimal
Force field parameter refers to the structure-activity relationship that can be best described by molecule in road known to those skilled in the art, and has good crystalline substance
Body shows.
Step:The structure after relaxation is obtained, the common molecular carried out under given series of temperature under NPT assemblages is dynamic
The temperature scanning of mechanical simulation;
Step:The final structure of every group of temperature scanning is carried out to the REMD simulations under NPT assemblages;By extracting common physics and chemistry
Property changes with time, and the panorama sketch of some property Temporal Evolution at all temperature is directly drawn in Jupyter;
Step is 5. according to REMD simulations as a result, calculate the curve that volume, interior energy and free energy vary with temperature;It is using
When MBAR calculates free energy, while calculating the correlation time between adjacent temperature and overlapping matrix;These data can be direct
The drafting pattern in Jupyter, so as to real time inspection and convergence inspection.
Preferably, the step 5. in, the calculating process of simulation can by temperature, pressure, volume, various energy,
RMSD, centroid motion etc. change with time figure to monitor whether to restrain.The various energy refer to include potential energy, kinetic energy, position
Set at least one of restriction effect energy, electrostatic interaction energy, model ylid bloom action energy and gross energy.
REMD simulations are mainly used for the sampling that reinforcement ties up on configuration space, to traverse potential energy level to the full extent
Upper all the points, to obtain accurate free energy data.But since the computing resource of its needs is very big, in task execution and resource tune
It is very complicated on degree.For this purpose, we devise the complete calculation process of set for REMD, fast and easy submits REMD tasks, and to knot
Fruit carries out automated analysis.
The present invention further uses above technical scheme, the advantage is that, in specified initial configuration, force field parameter and each step
Analog parameter(Including simulation step-length, duration, temperature range etc.)Afterwards, above-mentioned calculating process only need to be submitted once, so that it may
To be automatically performed subsequent all calculating and data analysis task.User can check and change at any time task in Jupyter
Execution state, also can the graphically existing calculating of real time inspection and analysis result.
Present invention offers following effects:
1. realizing the cross-platform scheduling of high-throughput, high parallel GROMACS tasks, the automatic continuous calculation of GROMACS tasks, continuous meter
Calculate the automated analysis with result.
2. the automation for realizing GROMACS structured files, force field parameter file and analog parameter file creates, Yi Jichang
Automated analysis with physicochemical property and integration.
3. the field of force exploitation, cluster ranking in seamless connection crystal form pre- flow gauge calculate and free energy calculates;Design will
Balanced structure, analysis result and the tracks GROMACS are stored separately, and are convenient for quick obtaining result of calculation;Greatly improve result exhibition
Show the speed with convergence.
4. by all GROMACS task creations, submission and management, physicochemical property monitoring, the steps such as interpretation of result and drawing
Suddenly it is integrated into Jupyter, realizes the visualized operation of GROMACS cloud computing flows.
Description of the drawings
Fig. 1 is complete GROMACS cloud computing flow charts of the invention.
Fig. 2 is that the present invention is based on the copies of GROMACS cloud computings to exchange molecular dynamics flow chart.
Fig. 3 is inclined by temperature, pressure, volume, various energy, RMSD, barycenter in the calculating process that MD of the present invention is simulated
Shifting etc. changes with time figure to monitor whether to restrain;2. 3. 4. it is related to step.
Fig. 4 is under different temperatures of the present invention, and volume, interior energy and temperature etc. change with time figure, and the curve in figure is from upper
Temperature is represented under to gradually reduce(Temperature i.e. from top to bottom is from 350K to 10K), the process being related to is 4..
Fig. 5 is the variation with temperature such as volume, interior energy and free energy of the present invention, the process being related to:⑤.
Fig. 6 is the convergence that free energy of the present invention calculates, and the correlation time of adjacent copy is with the change for scanning temperature number
Change(Correlation time all within 10, shows better astringency), the process that is related to:⑤.
Fig. 7 is the convergence that free energy of the present invention calculates, the corresponding energy envelope matrix of different scanning temperature number(It is right
A upper lattice for linea angulata and next lattice have larger colour-difference with whole background, and overlapping is abundant enough between showing adjacent copy), it is related to
Process:⑤.
Specific implementation mode
Below in conjunction with the accompanying drawings, the preferably embodiment of the present invention is described in further detail:
Embodiment 1
Complete GROMACS cloud computing flows, as shown in Figure 1, including following steps:
Step(1):From ArangoDB databases, the .res for the forward several crystal structures of energy that cluster ranking obtains is obtained
Or .cif files, it then calls yoda library functions to carry out symmetry operation, format conversion and structure cell extension, obtains GROMACS's
Structured file;
Step(2):From ArangoDB databases, the best force field parameter .prm and .rtf that field of force developmental research obtains is obtained, so
Yoda library functions are called to be automatically converted into the force field parameter file of GROMACS afterwards;
Step(3):According to the corresponding analog type of different phase, yoda library functions is called to automatically generate corresponding GROMACS's
Analog parameter file;These parameters can be replaced by the input parameter for the json formats that user provides, to realize parameter
Controllable adjustment;
Step(4):Mixc library functions are called, GROMACS is calculated and analysis task is submitted to Majorana task scheduling platforms.
These tasks include:Conventional MD is calculated, and copy exchanges molecular dynamics(REMD), track is reruned, when extending simulation
Between, the polymorphic Bennett receptance of the continuous calculation of breakpoint and multidimensional data calculates(MBAR)Deng.
Task parameters are using task type, mirror image name, memory and check figure etc..
Task can be submitted to specified cloud computing platform by Majorana according to task parameters(Amazon Cloud,
Tencent Cloud etc.)On.For example, according to task type(MD or REMD)Choose whether to need cross-node parallel with check figure,
The cloud platform to be submitted is specified according to the mirror image name of selection.Majorana can obtain the execution state of task and record in real time
Come, user can be by calling obiwan library functions come the execution state for the task of checking.
According to actual needs, can by obiwan library functions and the handle of task come change appointed task parameter and
State.Such as:List_job can check the mission bit stream of submission;Dump_job can obtain standard error/output of task;
Rerun can be recalculated(When task accidental interruption, it can realize that breakpoint is continuous automatically and calculate);Dump_file can be obtained
GROMACS's outputs and inputs file;Kill can delete task dispatching.These orders can automatic trigger Majorana transmission correspondences
Instruction to cloud platform on, to achieve the purpose that remote management task.
(5)In order to realize the automation Continuous plus of task, we are added to the corresponding same batch task of each structure
One monitor task(joiner), it can obtain the execution state of these tasks in real time.
Operating status includes:Normal termination(DONE), failure(FAILED), in preparation(IN_PREP), in queuing(IN_
QUEUE), low memory etc.(FALAT).Once all tasks are carried out success(DONE), data analysis program will be called
(Based on numpy, the libraries pandas and scipy), common physicochemical property is calculated automatically(Including various energy, volume, temperature, pressure
Power, RMSD, centroid motion etc.)Change with time, free energy, correlation time and overlapping matrix etc., and by task execution information,
Parameter, final structure and analysis result are saved in ArangoDB databases.Meanwhile by the big trail file of data volume(.trr
And .xtc), the .csv files of various types of properties Temporal Evolution, convergence data(.npy file)Etc. uploading to S3(Simple
Storage Service, simple storage service)On(Variation, debug and convergence for monitoring parameters in real time
Deng).Because the high-throughput transmission of file may be implemented in S3, convenient to download and analyze at any time intermediate data.Finally, according to need
Automatically the calculating task of next step is submitted.At this point, the state of the joiner tasks becomes DONE, new joiner tasks can weigh
It is newly-generated.
(6)After the completion of waiting for that all tasks are carried out, corresponding analysis result is obtained from ArangoDB databases, is called
Matplotlib draw libraries directly make corresponding curve in jupyter, intuitively to check result of calculation.
Embodiment 2
It is the specific of this flow below as shown in Fig. 2 to 7 that copy based on GROMACS cloud computings, which exchanges molecular dynamics flow,
Step:
Step is 1.:Result of calculation is ranked from cluster(Energy landscape)It is middle to choose N number of lower crystal structure of energy, transform format
Corresponding GROMACS structures are obtained after surpassing born of the same parents with extension.
Step is 2.:Optimal force field parameter is chosen, the isothermal and isobaric of 1ns is carried out to above-mentioned each structure(NPT)Relaxation.
Step:The structure after relaxation is obtained, in given series of temperature(N=68,10 ~ 350 K)Lower carry out 5ns
NPT assemblages under common molecular dynamics simulation(Temperature scanning).
Step:The final structure of every group of temperature scanning is carried out to the REMD simulations under the NPT assemblages of 5ns.Pass through extraction
Common physicochemical property changes with time, some property at all temperature can be directly drawn in Jupyter and is drilled at any time
The panorama sketch of change.
Step is 5. according to REMD simulations as a result, the song that volume, interior energy and free energy vary with temperature can be calculated
Line.When calculating free energy using MBAR, we also calculate correlation time and the overlapping matrix between adjacent temperature simultaneously.This
A little data can directly in Jupyter drafting pattern, so as to real time inspection and convergence inspection.
In addition, the calculating process of MD simulations can pass through temperature, pressure, volume, various energy, RMSD, centroid motion etc.
Figure change with time to monitor whether to restrain, 2., 3., 4. the process being related to includes.
Currently, in specified initial configuration, force field parameter and the analog parameter respectively walked(Including simulation step-length, duration, temperature model
It encloses)Afterwards, above-mentioned calculating process only need to be submitted once, so that it may be appointed with being automatically performed subsequent all calculating and data analysis
Business.User can check and change at any time the execution state of task in Jupyter, also can graphically real time inspection has been
Some calculating and analysis result.
The above content is a further detailed description of the present invention in conjunction with specific preferred embodiments, and it cannot be said that
The specific implementation of the present invention is confined to these explanations.For those of ordinary skill in the art to which the present invention belongs, exist
Under the premise of not departing from present inventive concept, a number of simple deductions or replacements can also be made, all shall be regarded as belonging to the present invention's
Protection domain.
Claims (6)
1. a kind of GROMACS cloud computings flow control method, which is characterized in that including following steps:
Step(1):From ArangoDB databases, the .res for the forward several crystal structures of energy that cluster ranking obtains is obtained
Or .cif files, it then calls yoda library functions to carry out symmetry operation, format conversion and structure cell extension, obtains GROMACS's
Structured file;
Step(2):From ArangoDB databases, the best force field parameter .prm and .rtf that field of force developmental research obtains is obtained, so
Yoda library functions are called to be automatically converted into the force field parameter file of GROMACS afterwards;
Step(3):According to the corresponding analog type of different phase, yoda library functions is called to automatically generate corresponding GROMACS's
Analog parameter file;
Step(4):Mixc library functions are called, GROMACS is calculated and analysis task is submitted to Majorana task scheduling platforms;
Step(5):Corresponding monitor task is added to the corresponding same batch task of each structure, obtains the execution shape of task in real time
State;
Step(6):After the completion of waiting for that all tasks are carried out, corresponding analysis result is obtained from ArangoDB databases, is called
Matplotlib draw libraries directly make corresponding curve in jupyter.
2. the method as described in claim 1, which is characterized in that the task parameters using task type, mirror image name, memory and
At least one of check figure.
3. method as claimed in claim 2, which is characterized in that the task type uses MD or REMD.
4. the method as described in claim 1, which is characterized in that the step(5)In, the operating status includes:Normal knot
Beam, failure, in preparing, be lined up and neutralize at least one of low memory.
5. a kind of copy based on GROMACS cloud computings as described in claim 1 exchanges molecular dynamics flow and method, feature
It is, including the following steps:
Step is 1.:It is ranked from cluster and chooses the lower crystal structure of N number of energy in result of calculation, after transform format surpasses born of the same parents with extension
Obtain corresponding GROMACS structures;
Step is 2.:Optimal force field parameter is chosen, the isothermal and isobaric relaxation of 1ns is carried out to above-mentioned each structure;
Step:The structure after relaxation is obtained, the common molecular dynamics under NPT assemblages is carried out under given series of temperature
The temperature scanning of simulation;
Step:The final structure of every group of temperature scanning is carried out to the REMD simulations under NPT assemblages;By extracting common physics and chemistry
Property changes with time, and the panorama sketch of some property Temporal Evolution at all temperature is directly drawn in Jupyter;
Step is 5. according to REMD simulations as a result, calculate the curve that volume, interior energy and free energy vary with temperature;It is using
When MBAR calculates free energy, while calculating the correlation time between adjacent temperature and overlapping matrix;These data can be direct
The drafting pattern in Jupyter, so as to real time inspection and convergence inspection.
6. method as claimed in claim 5, which is characterized in that the step 5. in, the calculating process of simulation can pass through temperature
Degree, pressure, volume, various energy, RMSD, centroid motion etc. change with time figure to monitor whether to restrain.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201810443967.5A CN108664729B (en) | 2018-05-10 | 2018-05-10 | GROMACS cloud computing flow control method |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201810443967.5A CN108664729B (en) | 2018-05-10 | 2018-05-10 | GROMACS cloud computing flow control method |
Publications (2)
Publication Number | Publication Date |
---|---|
CN108664729A true CN108664729A (en) | 2018-10-16 |
CN108664729B CN108664729B (en) | 2021-11-23 |
Family
ID=63779055
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201810443967.5A Active CN108664729B (en) | 2018-05-10 | 2018-05-10 | GROMACS cloud computing flow control method |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN108664729B (en) |
Cited By (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN109637592A (en) * | 2018-12-21 | 2019-04-16 | 深圳晶泰科技有限公司 | The calculating task management and analysis and its operation method that molecular force field parameter generates |
CN109885390A (en) * | 2019-02-21 | 2019-06-14 | 深圳晶泰科技有限公司 | Molecular docking cloud computing flow control method |
WO2020029513A1 (en) * | 2018-12-21 | 2020-02-13 | 深圳晶泰科技有限公司 | Management and analysis system for computation tasks generated by molecular force field parameters, and operation method thereof |
CN111341391A (en) * | 2020-02-25 | 2020-06-26 | 深圳晶泰科技有限公司 | Free energy perturbation computing and scheduling method used in heterogeneous cluster environment |
WO2020168507A1 (en) * | 2019-02-21 | 2020-08-27 | 深圳晶泰科技有限公司 | Molecular docking cloud computing process control method |
CN112487636A (en) * | 2020-11-26 | 2021-03-12 | 北京迈高材云科技有限公司 | Molecular dynamics computing method and system based on cloud computing technology |
CN114187971A (en) * | 2021-12-10 | 2022-03-15 | 上海智药科技有限公司 | Molecular free energy calculation and stability analysis method, device, equipment and storage medium |
Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20120095743A1 (en) * | 2009-06-24 | 2012-04-19 | Foldyne Technology B. V. | Molecular structure analysis and modeling |
CN102609246A (en) * | 2011-01-21 | 2012-07-25 | 中国科学院计算机网络信息中心 | Grid-based computational chemistry application integrated system |
CN103294483A (en) * | 2013-06-27 | 2013-09-11 | 曙光信息产业(北京)有限公司 | Processing method used for GROMACS computing program |
CN103714006A (en) * | 2014-01-07 | 2014-04-09 | 浪潮(北京)电子信息产业有限公司 | Performance test method of Gromacs software |
CN107729717A (en) * | 2017-11-03 | 2018-02-23 | 四川大学 | A kind of method that computer simulation obtains g protein coupled receptor intermediate structure |
-
2018
- 2018-05-10 CN CN201810443967.5A patent/CN108664729B/en active Active
Patent Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20120095743A1 (en) * | 2009-06-24 | 2012-04-19 | Foldyne Technology B. V. | Molecular structure analysis and modeling |
CN102609246A (en) * | 2011-01-21 | 2012-07-25 | 中国科学院计算机网络信息中心 | Grid-based computational chemistry application integrated system |
CN103294483A (en) * | 2013-06-27 | 2013-09-11 | 曙光信息产业(北京)有限公司 | Processing method used for GROMACS computing program |
CN103714006A (en) * | 2014-01-07 | 2014-04-09 | 浪潮(北京)电子信息产业有限公司 | Performance test method of Gromacs software |
CN107729717A (en) * | 2017-11-03 | 2018-02-23 | 四川大学 | A kind of method that computer simulation obtains g protein coupled receptor intermediate structure |
Non-Patent Citations (3)
Title |
---|
ARI WIBISONO ET AL.: "Cloud Computing Model and Implementation of Molecular Dynamics Simulation using Amber and Gromacs", 《ICACSIS 2012》 * |
VICTOR E. BAZTERRA ET AL.: "A Distributed Computing Method for Crystal Structure Prediction of Flexible Molecules: An Application to N-(2-Dimethyl-4,5-dinitrophenyl) Acetamide", 《JOURNAL OF CHEMICAL THEORY AND COMPUTATION》 * |
王卓等: "材料信息学及其在材料研究中的应用", 《中国材料进展》 * |
Cited By (11)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN109637592A (en) * | 2018-12-21 | 2019-04-16 | 深圳晶泰科技有限公司 | The calculating task management and analysis and its operation method that molecular force field parameter generates |
WO2020029513A1 (en) * | 2018-12-21 | 2020-02-13 | 深圳晶泰科技有限公司 | Management and analysis system for computation tasks generated by molecular force field parameters, and operation method thereof |
CN109637592B (en) * | 2018-12-21 | 2022-04-12 | 深圳晶泰科技有限公司 | Calculation task management analysis system for molecular force field parameter generation and operation method thereof |
US11609807B2 (en) | 2018-12-21 | 2023-03-21 | Shenzhen Jingtai Technology Co., Ltd. | Computing task management and analysis system for molecular force field parameter building and operation method thereof |
CN109885390A (en) * | 2019-02-21 | 2019-06-14 | 深圳晶泰科技有限公司 | Molecular docking cloud computing flow control method |
WO2020168507A1 (en) * | 2019-02-21 | 2020-08-27 | 深圳晶泰科技有限公司 | Molecular docking cloud computing process control method |
CN111341391A (en) * | 2020-02-25 | 2020-06-26 | 深圳晶泰科技有限公司 | Free energy perturbation computing and scheduling method used in heterogeneous cluster environment |
CN111341391B (en) * | 2020-02-25 | 2023-12-01 | 深圳晶泰科技有限公司 | Free energy perturbation calculation scheduling method for heterogeneous cluster environment |
CN112487636A (en) * | 2020-11-26 | 2021-03-12 | 北京迈高材云科技有限公司 | Molecular dynamics computing method and system based on cloud computing technology |
CN112487636B (en) * | 2020-11-26 | 2023-12-26 | 北京迈高材云科技有限公司 | Molecular dynamics calculation method and system based on cloud calculation technology |
CN114187971A (en) * | 2021-12-10 | 2022-03-15 | 上海智药科技有限公司 | Molecular free energy calculation and stability analysis method, device, equipment and storage medium |
Also Published As
Publication number | Publication date |
---|---|
CN108664729B (en) | 2021-11-23 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN108664729A (en) | A kind of GROMACS cloud computings flow control method | |
Seghir et al. | A hybrid approach using genetic and fruit fly optimization algorithms for QoS-aware cloud service composition | |
Zhao et al. | A finite-time approach to formation control of multiple mobile robots with terminal sliding mode | |
CN108037973A (en) | A kind of data flow modeling interacted with data processing tools and processing system | |
CN106022245A (en) | Multi-source remote sensing satellite data parallel processing system and method based on algorithm classification | |
Williams et al. | Ultrascale visualization of climate data | |
US10922453B2 (en) | GROMACS cloud computing process control method | |
CN111414658A (en) | Rock mass mechanics parameter inverse analysis method | |
CN109202895A (en) | The medium of design support apparatus, design support method and design Storage support program | |
CN110096838A (en) | A kind of helicopter flow field numerical value Parallel Implicit method for solving based on N-S equation | |
CN108763741A (en) | A kind of hydraulic hose fluid structurecoupling Numerical Predicting Method | |
CN113157694A (en) | Database index generation method based on reinforcement learning | |
CN113674135A (en) | Calculation method for realizing CALPUFF high performance based on workflow | |
CN114116778A (en) | Database query optimization method | |
CN114676522A (en) | Pneumatic shape optimization design method, system and equipment integrating GAN and transfer learning | |
Jiang et al. | A general scenario-agnostic reinforcement learning for traffic signal control | |
CN109885390A (en) | Molecular docking cloud computing flow control method | |
WO2024046458A1 (en) | Hierarchical system, operation method and apparatus, and electronic device and storage medium | |
Xue et al. | The analysis and research of parallel genetic algorithm | |
CN113705060B (en) | Topology optimization method, system and storage medium considering boundary optimization | |
CN111797576B (en) | Batch construction and submission method for aerospace multivariable CFD operation | |
CN115935662A (en) | Multidisciplinary collaborative simulation optimization platform, storage medium and electronic equipment | |
CN109031979A (en) | A kind of general purpose simulation system and method for missile flight dynamic and control | |
CN115169578A (en) | AI model production method and system based on meta-space data markers | |
CN103605849A (en) | Implementation method for linkage computing in product design analysis and development environment |
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 | ||
CB02 | Change of applicant information | ||
CB02 | Change of applicant information |
Address after: 3 / F, Shunfeng industrial building, No.2 Hongliu Road, Fubao community, Fubao street, Futian District, Shenzhen City, Guangdong Province Applicant after: Shenzhen Jingtai Technology Co.,Ltd. Address before: 518000 workshop, 4th floor, building 9, Hualian Industrial Zone, 91 Huaning Road, Dalang street, Longhua District, Shenzhen City, Guangdong Province Applicant before: Shenzhen Jingtai Technology Co.,Ltd. |
|
GR01 | Patent grant | ||
GR01 | Patent grant |