As the mean-time-between-failures(MTBF)continues to decline with the increasing number of components on large-scale high performance computing(HPC)systems,program failures might occur during the execution period with ...
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As the mean-time-between-failures(MTBF)continues to decline with the increasing number of components on large-scale high performance computing(HPC)systems,program failures might occur during the execution period with high *** successful execution of the HPC programs has become an issue that the unprivileged users should be *** the user perspective,if the program failure cannot be detected and handled in time,it would waste resources and delay the progress of program ***,the unprivileged users are unable to perform program state checking due to execution control by the job management system as well as the limited ***,automated tools for supporting user-level failure detection and autorecovery of parallel programs in HPC systems are *** paper proposes an innovative method for the unprivileged user to achieve failure detection of job execution and automatic resubmission of failed *** state checker in our method is encapsulated as an independent job to reduce interference with the user *** addition,we propose a dual-checker mechanism to improve the robustness of our *** implement the proposed method as a tool named automatic re-launcher(ARL)and evaluate it on the Tianhe-2 *** results show that ARL can detect the execution failures effectively on Tianhe-2 *** addition,the communication and performance overhead caused by ARL is *** good scalability of ARL makes it applicable for large-scale HPC systems.
Aiming at the problem of integrating open tools in a user development environment in complex product design, an integration strategy of model engineering environment based on OpenMBEE is studied. It is based on the te...
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The data stream processing framework processes the stream data based on event-time to ensure that the request can be responded to in *** reality,streaming data usually arrives out-of-order due to factors such as netwo...
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The data stream processing framework processes the stream data based on event-time to ensure that the request can be responded to in *** reality,streaming data usually arrives out-of-order due to factors such as network *** data stream processing framework commonly adopts the watermark mechanism to address the data *** is a special kind of data inserted into the data stream with a timestamp,which helps the framework to decide whether the data received is late and thus be *** watermark generation strategies are periodic;they cannot dynamically adjust the watermark distribution to balance the responsiveness and *** paper proposes an adaptive watermark generation mechanism based on the time series prediction model to address the above *** mechanism dynamically adjusts the frequency and timing of watermark distribution using the disordered data ratio and other lateness properties of the data stream to improve the system responsiveness while ensuring acceptable result *** implement the proposed mechanism on top of Flink and evaluate it with realworld *** experiment results show that our mechanism is superior to the existing watermark distribution strategies in terms of both system responsiveness and result accuracy.
To enhance the convergence capability of grey wolf optimizer (GWO), this research investigates an evolved GWO using weighted-leader strategy (WLS), namely WLSGWO. The key issue of WLS is realizing the adaptive adjustm...
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Since OpenAI opened access to ChatGPT,large language models(LLMs)become an increasingly popular topic attracting researchers’attention from abundant ***,public researchers meet some problems when developing LLMs give...
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Since OpenAI opened access to ChatGPT,large language models(LLMs)become an increasingly popular topic attracting researchers’attention from abundant ***,public researchers meet some problems when developing LLMs given that most of the LLMs are produced by industries and the training details are typically *** datasets are an important setup of LLMs,this paper does a holistic survey on the training datasets used in both the pre-train and fine-tune *** paper first summarizes 16 pre-train datasets and 16 fine-tune datasets used in the state-of-the-art ***,based on the properties of the pre-train and fine-tune processes,it comments on pre-train datasets from quality,quantity,and relation with models,and comments on fine-tune datasets from quality,quantity,and *** study then critically figures out the problems and research trends that exist in current LLM *** study helps public researchers train and investigate LLMs by visual cases and provides useful comments to the research community regarding data *** the best of our knowledge,this paper is the first to summarize and discuss datasets used in both autoregressive and chat *** survey offers insights and suggestions to researchers and LLM developers as they build their models,and contributes to the LLM study by pointing out the existing problems of LLM studies from the perspective of data.
Macao science Satellite-1(known as MSS-1)is a low-inclination mission that will be launched at the beginning of *** optical bench is used for accessing high-precision strength and direction measurements of the magneti...
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Macao science Satellite-1(known as MSS-1)is a low-inclination mission that will be launched at the beginning of *** optical bench is used for accessing high-precision strength and direction measurements of the magnetic *** this paper,we present a thermal stability design for the optical bench based on quasi-kinematic support by kinematic hinges on the *** change in angles with the finite element method(FEM)model modified by thermal deformation test data is *** robustness of the structure is also investigated via the Monte Carlo *** main results are ***,the peak-to-peak value(Vp-p)of the inter-boresight angle is at most 1.24″,and the Vp-p of the inter-boresight angle modification and analysis is no more than 3.13″,both of which are better than those on the Swarm satellites in ***,the 90°fibers of the carbon-reinforced arm need to be strictly controlled during the technological process.
As the development of Internet of things (IOT), massive sensors have been deployed as the public infrastructure. With the development of in-depth applications in IOT, service discovery and composition are challenges t...
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As the development of Internet of things (IOT), massive sensors have been deployed as the public infrastructure. With the development of in-depth applications in IOT, service discovery and composition are challenges to the end users. To handle this challenge, we develop a service mining scheme based on semantic for IOT to provide users with interesting composite services. In this scheme, services can be combined and recommended to users actively according to the calculation of service similarity and an updatable semantic database. By the results of service similarity, useless compositions can be filtered out so that energy consumption on service flooding will be reduced. The update strategy of semantic database is also given out, by which the composite services can keep up with time and be more applicative. The benefits of the proposed method are that all operations such as calculating, filtering, and updating are simple enough to be performed in sensor networks.
In Information Centric Networking(ICN)where content is the object of exchange,in-network caching is a unique functional feature with the ability to handle data storage and distribution in remote sensing satellite *** ...
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In Information Centric Networking(ICN)where content is the object of exchange,in-network caching is a unique functional feature with the ability to handle data storage and distribution in remote sensing satellite *** up cache space at any node enables users to access data nearby,thus relieving the processing pressure on the ***,the existing caching strategies still suffer from the lack of global planning of cache contents and low utilization of cache resources due to the lack of fine-grained division of cache *** address the issues mentioned,a cooperative caching strategy(CSTL)for remote sensing satellite networks based on a two-layer caching model is *** two-layer caching model is constructed by setting up separate cache spaces in the satellite network and the ground *** caching of popular contents in the region at the ground station to reduce the access delay of users.A content classification method based on hierarchical division is proposed in the satellite network,and differential probabilistic caching is employed for different levels of *** cached content is also dynamically adjusted by analyzing the subsequent changes in the popularity of the cached *** the two-layer caching model,ground stations and satellite networks collaboratively cache to achieve global planning of cache contents,rationalize the utilization of cache resources,and reduce the propagation delay of remote sensing *** results show that the CSTL strategy not only has a high cache hit ratio compared with other caching strategies but also effectively reduces user request delay and server load,which satisfies the timeliness requirement of remote sensing data transmission.
On-device training Neural Networks (NNs) has been a crucial catalyst towards privacy-preserving and personalized mobile intelligence. Recently, a novel training paradigm, namely Parameter-Efficient Training (PET), is ...
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Target data detected by multi-sensors often differ from each other due to different sensor performances, resulting in uncertainty of target identity information. Traditional Dempster-Shafer (DS) evidence theory may ac...
Target data detected by multi-sensors often differ from each other due to different sensor performances, resulting in uncertainty of target identity information. Traditional Dempster-Shafer (DS) evidence theory may achieve counter-intuitive outcomes facing evidence conflicts caused by the uncertainty. Aiming for this, a novel target identity fusion method based on improved DS evidence theory is proposed in this paper. Specifically, the method considers the correlation between evidences and the importance of evidences integrally. First, an improved conflict measurement method based on Pearson correlation coefficient matrix is devised to measure the evidence credibility. Next the information volume of evidences is measured by Deng-entropy to indicate the evidence uncertainty. Then the credibility and uncertainty are weighted and combined to modify the basic probability assignment (BPA) of evidences. Ultimately, the modified evidences are fused by Dempster’s combination rule to acquire the final results. Through three numerical analysis examples, this paper demonstrates the superiority of the proposed method over typical previous approaches, which can effectively process evidence conflicts in multi-sensors information fusion.
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