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AocML： A domain-specific language for Model-Driven Development of Activity-Oriented Context-Aware Applications

Journal of Computer Science & Technology 2018年第5期33卷 900-917页

作者： Xuan-Song Li Xian-Ping Tao Wei Song Kai Dong School of Computer Science and Engineering Nanjing University of Science and Technology Nanfing 210093 China State Key Laboratory for Novel Software Technology Nanjing University Nanjing 210023 China School of Computer Science and Engineering Southeast University Nanjing 211189 China

Activity-oriented context-aware （AOCA） applications are representative in pervasive computing. These appli- cations recognize daily-life human activities, perceive the environment status related to the activities, and react to ensure the smooth performance of the activities. Existing research proposed a specific light-weight, incremental method to support the development of such applications; however it is not easy to learn and use. This paper aims to facilitate the development of such applications and improve the productivity of developers. We propose AocML, a textual domain-specific language which provides a high-level abstraction of AOCA applications. specifically, we first show the software model of AOCA applications and the abstract syntax of AocML. Then, we introduce the concrete syntax of AocML. We also implement the tools for AocML, including the development environment as well as the generation of Java code and ontology specification. Moreover, we use a case study and evaluation to demonstrate the advantages of AocML.

关键词： pervasive computing context-awareness model-driven development domain-specific language

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FlexPDA:A Flexible Programming Framework for Deep Learning Accelerators

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Journal of Computer Science & Technology 2022年第5期37卷 1200-1220页

作者：刘磊马秀刘华虓李广力刘雷 College of Computer Science and Technology Jilin UniversityChangchunChina Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin UniversityChangchunChina State Key Laboratory of Computer Architecture Institute of Computing TechnologyChinese Academy of SciencesBeijingChina University of Chinese Academy of Sciences BeijingChina

There are a wide variety of intelligence accelerators with promising performance and energy efficiency,deployed in a broad range of applications such as computer vision and speech ***,programming productivity hinders the deployment of deep learning *** low-level library invoked in the high-level deep learning framework which supports the end-to-end execution with a given model,is designed to reduce the programming burden on the intelligence ***,it is inflexible for developers to build a network model for every deep learning application,which probably brings unnecessary repetitive *** this paper,a flexible and efficient programming framework for deep learning accelerators,FlexPDA,is proposed,which provides more optimization opportunities than the low-level library and realizes quick transplantation of applications to intelligence accelerators for fast *** evaluate FlexPDA by using 10 representative operators selected from deep learning algorithms and an end-to-end *** experimental results validate the effectiveness of FlexPDA,which achieves an end-to-end performance improvement of 1.620x over the low-level library.

关键词： deep learning accelerator programming framework domain-specific language

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Cheap and secure metatransactions on the blockchain using hash-based authorisation and preferred batchers

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Blockchain(Research and Applications) 2023年第2期4卷 41-66页

作者： William Hughes Tobias Magnusson Alejandro Russo Gerardo Schneider Dept.of Computer Science and Engineering University of Gothenburg41296GothenburgSweden Dept.of Computer Science and Engineering Chalmers University41296GothenburgSweden

Smart contracts are self-executing programs running in the blockchain allowing for decentralised storage and execution without a ***-chain execution is expensive,with miners charging fees for distributed execution according to a cost model defined in the *** particular,transactions have a high fixed *** present MultiCall,a transaction-batching interpreter for Ethereum that reduces the cost of smart contract executions by gathering multiple users’transactions into a *** current implementation of MultiCall includes the following features:the ability to emulate Ethereum calls and create transactions,both from MultiCall itself and using an identity unique to the user;the ability to cheaply pay Ether to other MultiCall users;and the ability to authorise emulated transactions on behalf of multiple users in a single transaction using hash-based authorisation rather than more expensive *** improves upon a previous version of *** experiments show that MultiCall provides a saving between 57%and 99%of the fixed transaction cost compared with the standard approach of sending Ethereum transactions directly.

关键词： Ethereum domain-specific language Interpreter Gas optimisation

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