Modern power systems are evolving into sociotechnical systems with massive complexity, whose real-time operation and dispatch go beyond human capability. Thus,the need for developing and applying new intelligent power...Modern power systems are evolving into sociotechnical systems with massive complexity, whose real-time operation and dispatch go beyond human capability. Thus,the need for developing and applying new intelligent power system dispatch tools are of great practical significance. In this paper, we introduce the overall business model of power system dispatch, the top level design approach of an intelligent dispatch system, and the parallel intelligent technology with its dispatch applications. We expect that a new dispatch paradigm,namely the parallel dispatch, can be established by incorporating various intelligent technologies, especially the parallel intelligent technology, to enable secure operation of complex power grids,extend system operators' capabilities, suggest optimal dispatch strategies, and to provide decision-making recommendations according to power system operational goals.展开更多
In this paper, we consider a class of submanifolds with parallel mean curvacture vector fields. We obitain the suffitient conditions that the above submanifolds is of tatall umbilical and that its codimension is decre...In this paper, we consider a class of submanifolds with parallel mean curvacture vector fields. We obitain the suffitient conditions that the above submanifolds is of tatall umbilical and that its codimension is decrease.展开更多
Prompted by emerging developments in connected and automated vehicles, parallel steering control, one aspect of parallel driving, has become highly important for intelligent vehicles for easing the burden and ensuring...Prompted by emerging developments in connected and automated vehicles, parallel steering control, one aspect of parallel driving, has become highly important for intelligent vehicles for easing the burden and ensuring the safety of human drivers. This paper presents a parallel steering control framework for an intelligent vehicle using moving horizon optimization.The framework considers lateral stability, collision avoidance and actuator saturation and describes them as constraints, which can blend the operation of a human driver and a parallel steering controller effectively. Moreover, the road hazard and the steering operation error are employed to evaluate the operational hazardous of an intelligent vehicle. Under the hazard evaluation,the intelligent vehicle will be mainly operated by the human driver when the vehicle operates in a safe and stable manner.The automated steering driving objective will play an active role and regulate the steering operations of the intelligent vehicle based on the hazard evaluation. To verify the effectiveness of the proposed hazard-evaluation-oriented moving horizon parallel steering control approach, various validations are conducted, and the results are compared with a parallel steering scheme that does not consider automated driving situations. The results illustrate that the proposed parallel steering controller achieves acceptable performance under both conventional conditions and hazardous conditions.展开更多
With user-generated content, anyone can De a content creator. This phenomenon has infinitely increased the amount of information circulated online, and it is beeoming harder to efficiently obtain required information....With user-generated content, anyone can De a content creator. This phenomenon has infinitely increased the amount of information circulated online, and it is beeoming harder to efficiently obtain required information. In this paper, we describe how natural language processing and text mining can be parallelized using Hadoop and Message Passing Interface. We propose a parallel web text mining platform that processes massive amounts data quickly and efficiently. Our web knowledge service platform is designed to collect information about the IT and telecommunications industries from the web and process this in-formation using natural language processing and data-mining techniques.展开更多
The author investigates the query optimization problem for parallel relational databases. A multi - weighted tree based query optimization method is proposed. The method consists of a multi - weighted tree based paral...The author investigates the query optimization problem for parallel relational databases. A multi - weighted tree based query optimization method is proposed. The method consists of a multi - weighted tree based parallel query plan model, a cost model for parallel qury plans and a query optimizer. The parallel query plan model is the first one to model all basic relational operations, all three types of parallelism of query execution, processor and memory allocation to operations, memory allocation to the buffers between operations in pipelines and data redistribution among processors. The cost model takes the waiting time of the operations in pipelining execution into consideration and is computable in a bottom - up fashion. The query optimizer addresses the query optimization problem in the context of Select - Project - Join queries that are widely used in commercial DBMSs. Several heuristics determining the processor allocation to operations are derived and used in the query optimizer. The query optimizer is aware of memory resources in order to generate good - quality plans. It includes the heuristics for determining the memory allocation to operations and buffers between operations in pipelines so that the memory resourse is fully exploit. In addition, multiple algorithms for implementing join operations are consided in the query optimizer. The query optimizer can make an optimal choice of join algorithm for each join operation in a query. The proposed query optimization method has been used in a prototype parallel database management system designed and implemented by the author.展开更多
We present two parallel algorithms based on the domain decomposition methodfor solving a variational inequality over a closed convex cone.First,construct an opencovering {Ω_i}of the original domain Ω∶Ω=(?),where ...We present two parallel algorithms based on the domain decomposition methodfor solving a variational inequality over a closed convex cone.First,construct an opencovering {Ω_i}of the original domain Ω∶Ω=(?),where Ω_i,i=1,…,m,are overlapping.i.e.for each Ω_i there exists at least one Ω_j(j≠i)such that Ω_i∩Ω_i≠φ.Choosing an initial guessu^0 for the solution u,we solve parallelly the inequality in each subdomain Ω_i(i=1,…,m)to obtain m corrections.Take an appropriate average of these m corrections as a correctionover Ω and hence obtain a new approximation to u.In this paper we discuss the convergenceof the continuous problem and also the corresponding discrete problem which is obtained bythe finite element method.展开更多
Abnormal or drastic changes in the natural environment may lead to unexpected events,such as tsunamis and earthquakes,which are becoming a major threat to national economy.Currently,no effective assessment approach ca...Abnormal or drastic changes in the natural environment may lead to unexpected events,such as tsunamis and earthquakes,which are becoming a major threat to national economy.Currently,no effective assessment approach can deduce a situation and determine the optimal response strategy when a natural disaster occurs.In this study,we propose a social evolution modeling approach and construct a deduction model for self-playing,self-learning,and self-upgrading on the basis of the idea of parallel data and reinforcement learning.The proposed approach can evaluate the impact of an event,deduce the situation,and provide optimal strategies for decisionmaking.Taking the breakage of a submarine cable caused by earthquake as an example,we find that the proposed modeling approach can obtain a higher reward compared with other existing methods.展开更多
The Kinetic Monte Carlo(KMC)is one of the commonly used methods for simulating radiation damage of materials.Our team develops a parallel KMC software named Crystal-KMC,which supports the Embedded Atom Method(EAM)pote...The Kinetic Monte Carlo(KMC)is one of the commonly used methods for simulating radiation damage of materials.Our team develops a parallel KMC software named Crystal-KMC,which supports the Embedded Atom Method(EAM)potential energy and utilizes the Message Passing Interface(MPI)technology to simulate the vacancy transition of the Copper(Cu)element under neutron radiation.To make better use of the computing power of modern supercomputers,we develop the parallel efficiency optimization model for the Crystal-KMC on Tianhe-2,to achieve a larger simulation of the damage process of materials under irradiation environment.Firstly,we analyze the performance bottleneck of the Crystal-KMC software and use the MIC offload statement to implement the operation of key modules of the software on the MIC coprocessor.We use Open MP to develop parallel optimization for the Crystal-KMC,combined with existing MPI inter-process communication optimization,finally achieving hybrid parallel optimization.The experimental results show that in the single-node CPU and MIC collaborative parallel mode,the speedup of the calculation hotspot reaches 30.1,and the speedup of the overall software reaches 7.43.展开更多
基金supported by State Grid Corporation of China(SGCC)Science and Technology Project SGTJDK00DWJS1700060
文摘Modern power systems are evolving into sociotechnical systems with massive complexity, whose real-time operation and dispatch go beyond human capability. Thus,the need for developing and applying new intelligent power system dispatch tools are of great practical significance. In this paper, we introduce the overall business model of power system dispatch, the top level design approach of an intelligent dispatch system, and the parallel intelligent technology with its dispatch applications. We expect that a new dispatch paradigm,namely the parallel dispatch, can be established by incorporating various intelligent technologies, especially the parallel intelligent technology, to enable secure operation of complex power grids,extend system operators' capabilities, suggest optimal dispatch strategies, and to provide decision-making recommendations according to power system operational goals.
文摘In this paper, we consider a class of submanifolds with parallel mean curvacture vector fields. We obitain the suffitient conditions that the above submanifolds is of tatall umbilical and that its codimension is decrease.
基金supported by the National Nature Science Foundation of China(61520106008,61790563,U1664263)
文摘Prompted by emerging developments in connected and automated vehicles, parallel steering control, one aspect of parallel driving, has become highly important for intelligent vehicles for easing the burden and ensuring the safety of human drivers. This paper presents a parallel steering control framework for an intelligent vehicle using moving horizon optimization.The framework considers lateral stability, collision avoidance and actuator saturation and describes them as constraints, which can blend the operation of a human driver and a parallel steering controller effectively. Moreover, the road hazard and the steering operation error are employed to evaluate the operational hazardous of an intelligent vehicle. Under the hazard evaluation,the intelligent vehicle will be mainly operated by the human driver when the vehicle operates in a safe and stable manner.The automated steering driving objective will play an active role and regulate the steering operations of the intelligent vehicle based on the hazard evaluation. To verify the effectiveness of the proposed hazard-evaluation-oriented moving horizon parallel steering control approach, various validations are conducted, and the results are compared with a parallel steering scheme that does not consider automated driving situations. The results illustrate that the proposed parallel steering controller achieves acceptable performance under both conventional conditions and hazardous conditions.
文摘With user-generated content, anyone can De a content creator. This phenomenon has infinitely increased the amount of information circulated online, and it is beeoming harder to efficiently obtain required information. In this paper, we describe how natural language processing and text mining can be parallelized using Hadoop and Message Passing Interface. We propose a parallel web text mining platform that processes massive amounts data quickly and efficiently. Our web knowledge service platform is designed to collect information about the IT and telecommunications industries from the web and process this in-formation using natural language processing and data-mining techniques.
基金Supported by the National Natural Science Foundation of China National (9846-004) '863' High -Technique Program of China (8
文摘The author investigates the query optimization problem for parallel relational databases. A multi - weighted tree based query optimization method is proposed. The method consists of a multi - weighted tree based parallel query plan model, a cost model for parallel qury plans and a query optimizer. The parallel query plan model is the first one to model all basic relational operations, all three types of parallelism of query execution, processor and memory allocation to operations, memory allocation to the buffers between operations in pipelines and data redistribution among processors. The cost model takes the waiting time of the operations in pipelining execution into consideration and is computable in a bottom - up fashion. The query optimizer addresses the query optimization problem in the context of Select - Project - Join queries that are widely used in commercial DBMSs. Several heuristics determining the processor allocation to operations are derived and used in the query optimizer. The query optimizer is aware of memory resources in order to generate good - quality plans. It includes the heuristics for determining the memory allocation to operations and buffers between operations in pipelines so that the memory resourse is fully exploit. In addition, multiple algorithms for implementing join operations are consided in the query optimizer. The query optimizer can make an optimal choice of join algorithm for each join operation in a query. The proposed query optimization method has been used in a prototype parallel database management system designed and implemented by the author.
基金A project supported by the National Natural Science Foundation of China
文摘We present two parallel algorithms based on the domain decomposition methodfor solving a variational inequality over a closed convex cone.First,construct an opencovering {Ω_i}of the original domain Ω∶Ω=(?),where Ω_i,i=1,…,m,are overlapping.i.e.for each Ω_i there exists at least one Ω_j(j≠i)such that Ω_i∩Ω_i≠φ.Choosing an initial guessu^0 for the solution u,we solve parallelly the inequality in each subdomain Ω_i(i=1,…,m)to obtain m corrections.Take an appropriate average of these m corrections as a correctionover Ω and hence obtain a new approximation to u.In this paper we discuss the convergenceof the continuous problem and also the corresponding discrete problem which is obtained bythe finite element method.
基金supported by the National Natural Science Foundation of China(No.62072469)the National Key R&D Program of China(No.2018YFE0116700)+1 种基金the Shandong Provincial Natural Science Foundation(No.ZR2019MF049,Parallel Data Driven Fault Prediction under Online-Offline Combined Cloud Computing Environment)the Fundamental Research Funds for the Central Universities(No.2015020031)。
文摘Abnormal or drastic changes in the natural environment may lead to unexpected events,such as tsunamis and earthquakes,which are becoming a major threat to national economy.Currently,no effective assessment approach can deduce a situation and determine the optimal response strategy when a natural disaster occurs.In this study,we propose a social evolution modeling approach and construct a deduction model for self-playing,self-learning,and self-upgrading on the basis of the idea of parallel data and reinforcement learning.The proposed approach can evaluate the impact of an event,deduce the situation,and provide optimal strategies for decisionmaking.Taking the breakage of a submarine cable caused by earthquake as an example,we find that the proposed modeling approach can obtain a higher reward compared with other existing methods.
基金supported by the National Key R&D Program of China(No.2017YFB0202104)。
文摘The Kinetic Monte Carlo(KMC)is one of the commonly used methods for simulating radiation damage of materials.Our team develops a parallel KMC software named Crystal-KMC,which supports the Embedded Atom Method(EAM)potential energy and utilizes the Message Passing Interface(MPI)technology to simulate the vacancy transition of the Copper(Cu)element under neutron radiation.To make better use of the computing power of modern supercomputers,we develop the parallel efficiency optimization model for the Crystal-KMC on Tianhe-2,to achieve a larger simulation of the damage process of materials under irradiation environment.Firstly,we analyze the performance bottleneck of the Crystal-KMC software and use the MIC offload statement to implement the operation of key modules of the software on the MIC coprocessor.We use Open MP to develop parallel optimization for the Crystal-KMC,combined with existing MPI inter-process communication optimization,finally achieving hybrid parallel optimization.The experimental results show that in the single-node CPU and MIC collaborative parallel mode,the speedup of the calculation hotspot reaches 30.1,and the speedup of the overall software reaches 7.43.
