Graph is a well known data structure to represent the associated relationships in a variety of applications,e.g.,data science and machine learning.Despite a wealth of existing efforts on developing graph processing sy...Graph is a well known data structure to represent the associated relationships in a variety of applications,e.g.,data science and machine learning.Despite a wealth of existing efforts on developing graph processing systems for improving the performance and/or energy efficiency on traditional architectures,dedicated hardware solutions,also referred to as graph processing accelerators,are essential and emerging to provide the benefits significantly beyond what those pure software solutions can offer.In this paper,we conduct a systematical survey regarding the design and implementation of graph processing accelerators.Specifically,we review the relevant techniques in three core components toward a graph processing accelerator:preprocessing,parallel graph computation,and runtime scheduling.We also examine the benchmarks and results in existing studies for evaluating a graph processing accelerator.Interestingly,we find that there is not an absolute winner for all three aspects in graph acceleration due to the diverse characteristics of graph processing and the complexity of hardware configurations.We finally present and discuss several challenges in details,and further explore the opportunities for the future research.展开更多
Inherent heterogeneity and distribution of knowledge strongly prevent knowledge from sharing and reusing among different agents and software entities, and a formal ontology has been viewed as a promising means to tack...Inherent heterogeneity and distribution of knowledge strongly prevent knowledge from sharing and reusing among different agents and software entities, and a formal ontology has been viewed as a promising means to tackle this problem. In this paper, a domain-specific formal ontology of archaeology is presented. The ontology mainly consists of three parts: archaeological categories, their relationships and axioms. The ontology not only captures the semantics of archaeological knowledge, but also provides archaeology with an explicit and formal specification of a shared conceptualization, thus making archaeological knowledge shareable and reusable across humans and machines in a structured fashion. Further, we propose a method to verify ontology. correctness based on the individuals of categories. As applications of the ontology,we have developed an ontology-driven approach to knowledge acquisition from archaeological text and a question answering system for archaeological knowledge.展开更多
Domain-specific ontologies are greatly useful in knowledge acquisition,sharing and analysis. In this paper, botany-specific ontology for acquiring and analyzing botanicalknowledge is presented. The ontology is represe...Domain-specific ontologies are greatly useful in knowledge acquisition,sharing and analysis. In this paper, botany-specific ontology for acquiring and analyzing botanicalknowledge is presented. The ontology is represented in a set of well-defined categories, and eachconcept is viewed as an instance of certain category. The authors also introduce botany-specificaxioms, an integral part of the ontology, for checking and reasoning with the acquired knowledge.Consistency, completeness and redundancy of the axioms are discussed.展开更多
Recently,due to the availability of big data and the rapid growth of computing power,artificial intelligence(AI)has regained tremendous attention and investment.Machine learning(ML)approaches have been successfully ap...Recently,due to the availability of big data and the rapid growth of computing power,artificial intelligence(AI)has regained tremendous attention and investment.Machine learning(ML)approaches have been successfully applied to solve many problems in academia and in industry.Although the explosion of big data applications is driving the development of ML,it also imposes severe challenges of data processing speed and scalability on conventional computer systems.Computing platforms that are dedicatedly designed for AI applications have been considered,ranging from a complement to von Neumann platforms to a“must-have”and stand-alone technical solution.These platforms,which belong to a larger category named“domain-specific computing,”focus on specific customization for AI.In this article,we focus on summarizing the recent advances in accelerator designs for deep neural networks(DNNs)-that is,DNN accelerators.We discuss various architectures that support DNN executions in terms of computing units,dataflow optimization,targeted network topologies,architectures on emerging technologies,and accelerators for emerging applications.We also provide our visions on the future trend of AI chip designs.展开更多
This paper presents model-based approach to process-control software development. The presented approach enables modelling of control software in a straightforward manner and, at the same time, on a high level of abst...This paper presents model-based approach to process-control software development. The presented approach enables modelling of control software in a straightforward manner and, at the same time, on a high level of abstraction. The essence of the presented approach is a high-level, domain-specific modelling language ProcGraph, which is based on three types of diagrams that describe the modelled system using a domain-oriented hierarchical structure of interdependent procedural control entities and state-transition diagrams describing the behaviour of the procedural control entities. The presented concept is demonstrated by means of higher-level model segments of a real process-control application that deals with the micronisation process in the production of titanium dioxide. The presented industrial case shows that the application of ProcGraph provides adequate expressive power for an elegant preparation of graphic specifications in a transparent and easy way.展开更多
Decision modeling is an essential part of the combat system effectiveness simulation (CoSES), which needs to cope with the cognitive quality, diversity, flexibility, and higher abstraction of decision making. In this ...Decision modeling is an essential part of the combat system effectiveness simulation (CoSES), which needs to cope with the cognitive quality, diversity, flexibility, and higher abstraction of decision making. In this paper, a multi-paradigm decision modeling framework is proposed to support decision modeling at three levels of abstraction based on domain-specific modeling (DSM). This framework designs a domain-specific modeling language (DSML) for decision modeling to raise the abstraction level of modeling, transforms the domain-specific models to formalism-based models to enable formal analysis and early verification and validation, and implements the semantics of the DSML based on a Python scripts framework which incorporates the decision model into the whole simulation system. The case study shows that the proposed approach incorporates domain expertise and facilitates domain modeler's participation in CoSES to formulate the problem using DSML in the problem domain, and enables formal analysis and automatic implementation of the decision model in the solution domain.展开更多
基金the National Key Research and Development Program of China under Grant No.2018YFB1003502the National Natural Science Foundation of China under Grant Nos.61825202,61832006,61628204 and 61702201.
文摘Graph is a well known data structure to represent the associated relationships in a variety of applications,e.g.,data science and machine learning.Despite a wealth of existing efforts on developing graph processing systems for improving the performance and/or energy efficiency on traditional architectures,dedicated hardware solutions,also referred to as graph processing accelerators,are essential and emerging to provide the benefits significantly beyond what those pure software solutions can offer.In this paper,we conduct a systematical survey regarding the design and implementation of graph processing accelerators.Specifically,we review the relevant techniques in three core components toward a graph processing accelerator:preprocessing,parallel graph computation,and runtime scheduling.We also examine the benchmarks and results in existing studies for evaluating a graph processing accelerator.Interestingly,we find that there is not an absolute winner for all three aspects in graph acceleration due to the diverse characteristics of graph processing and the complexity of hardware configurations.We finally present and discuss several challenges in details,and further explore the opportunities for the future research.
文摘Inherent heterogeneity and distribution of knowledge strongly prevent knowledge from sharing and reusing among different agents and software entities, and a formal ontology has been viewed as a promising means to tackle this problem. In this paper, a domain-specific formal ontology of archaeology is presented. The ontology mainly consists of three parts: archaeological categories, their relationships and axioms. The ontology not only captures the semantics of archaeological knowledge, but also provides archaeology with an explicit and formal specification of a shared conceptualization, thus making archaeological knowledge shareable and reusable across humans and machines in a structured fashion. Further, we propose a method to verify ontology. correctness based on the individuals of categories. As applications of the ontology,we have developed an ontology-driven approach to knowledge acquisition from archaeological text and a question answering system for archaeological knowledge.
文摘Domain-specific ontologies are greatly useful in knowledge acquisition,sharing and analysis. In this paper, botany-specific ontology for acquiring and analyzing botanicalknowledge is presented. The ontology is represented in a set of well-defined categories, and eachconcept is viewed as an instance of certain category. The authors also introduce botany-specificaxioms, an integral part of the ontology, for checking and reasoning with the acquired knowledge.Consistency, completeness and redundancy of the axioms are discussed.
基金the National Science Foundations(NSFs)(1822085,1725456,1816833,1500848,1719160,and 1725447)the NSF Computing and Communication Foundations(1740352)+1 种基金the Nanoelectronics COmputing REsearch Program in the Semiconductor Research Corporation(NC-2766-A)the Center for Research in Intelligent Storage and Processing-in-Memory,one of six centers in the Joint University Microelectronics Program,a SRC program sponsored by Defense Advanced Research Projects Agency.
文摘Recently,due to the availability of big data and the rapid growth of computing power,artificial intelligence(AI)has regained tremendous attention and investment.Machine learning(ML)approaches have been successfully applied to solve many problems in academia and in industry.Although the explosion of big data applications is driving the development of ML,it also imposes severe challenges of data processing speed and scalability on conventional computer systems.Computing platforms that are dedicatedly designed for AI applications have been considered,ranging from a complement to von Neumann platforms to a“must-have”and stand-alone technical solution.These platforms,which belong to a larger category named“domain-specific computing,”focus on specific customization for AI.In this article,we focus on summarizing the recent advances in accelerator designs for deep neural networks(DNNs)-that is,DNN accelerators.We discuss various architectures that support DNN executions in terms of computing units,dataflow optimization,targeted network topologies,architectures on emerging technologies,and accelerators for emerging applications.We also provide our visions on the future trend of AI chip designs.
文摘This paper presents model-based approach to process-control software development. The presented approach enables modelling of control software in a straightforward manner and, at the same time, on a high level of abstraction. The essence of the presented approach is a high-level, domain-specific modelling language ProcGraph, which is based on three types of diagrams that describe the modelled system using a domain-oriented hierarchical structure of interdependent procedural control entities and state-transition diagrams describing the behaviour of the procedural control entities. The presented concept is demonstrated by means of higher-level model segments of a real process-control application that deals with the micronisation process in the production of titanium dioxide. The presented industrial case shows that the application of ProcGraph provides adequate expressive power for an elegant preparation of graphic specifications in a transparent and easy way.
基金Project (Nos. 61273198, 91024015, 61074107, 60974073,60974074, and 71031007) supported by the National Natural Science Foundation of China
文摘Decision modeling is an essential part of the combat system effectiveness simulation (CoSES), which needs to cope with the cognitive quality, diversity, flexibility, and higher abstraction of decision making. In this paper, a multi-paradigm decision modeling framework is proposed to support decision modeling at three levels of abstraction based on domain-specific modeling (DSM). This framework designs a domain-specific modeling language (DSML) for decision modeling to raise the abstraction level of modeling, transforms the domain-specific models to formalism-based models to enable formal analysis and early verification and validation, and implements the semantics of the DSML based on a Python scripts framework which incorporates the decision model into the whole simulation system. The case study shows that the proposed approach incorporates domain expertise and facilitates domain modeler's participation in CoSES to formulate the problem using DSML in the problem domain, and enables formal analysis and automatic implementation of the decision model in the solution domain.
