Energy-aware scheduling for dependent tasks in heterogeneous multiprocessor systems

Chen, Jinchao; Yu, Huaiqiang; Zhang, Ying; Han, Pengcheng; Du, Chenglie

doi:10.1016/j.sysarc.2022.102598

Cited by 63 publications

(64 citation statements)

References 24 publications

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“…The randomness in this algorithm greatly improves the flexibility of algorithm design and the possibility of people solving problems. But because of the wide range of random selection, the accuracy rate is not very high [ 9 ].…”

Section: Deconstruction Methods Of Pan-logical Probabilistic Algorith...mentioning

confidence: 99%

Pan-Logical Probabilistic Algorithms Based on Convolutional Neural Networks

Liu

2022

Computational Intelligence and Neuroscience

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A brand-new kind of flexible logic system called universal logic aims to address a variety of uncertain problems. In this study, the role of convolutional neural networks in assessing probabilistic pan-logic algorithms is investigated. A generic logic probability algorithm analysis based on a convolutional neural network is suggested due to the unpredictable outputs of the probabilistic algorithm and the difficulty of its analysis. The stochastic gradient descent technique and the error backpropagation algorithm are used to investigate the broad logic probability algorithm (SGD). The experimental data presented in this research show that the BP algorithm of the convolutional neural network has an accuracy rate of 89 percent when analysing the experimental data. As there are more experimental iterations, the error will go down. The SGD method proves that raising the algorithm’s learning rate reduces the loss value of the function. The loss value can be as low as 100%, and the algorithm analysis is closer to the real.

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Section: Deconstruction Methods Of Pan-logical Probabilistic Algorith...mentioning

confidence: 99%

Pan-Logical Probabilistic Algorithms Based on Convolutional Neural Networks

Liu

2022

Computational Intelligence and Neuroscience

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“…DM modelling is a process of gradual improvement after many revisions and requires constant testing in real-world settings. Automatic modelling and model transformation are currently the two main technical topics under discussion in the DM modelling industry [ 7 ]. DM technology, which is currently the subject of extensive research and has a wide range of applications in industries such as finance, healthcare, aviation, and transportation, is used extensively in many different fields.…”

Section: Introductionmentioning

confidence: 99%

[Retracted] Personalised Recommendation of PE Network Course Environment Resources Using Data Mining Analysis

Min

2022

Journal of Environmental and Public Health

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PE education reform is positively influenced by the creation and use of resources for PE courses as a supplement to and development of traditional teaching strategies. In order to mine the vast amount of data in the network PE curriculum resource system and find useful patterns, this paper uses highly automated DM technology. Additionally, you can forecast users’ upcoming actions and suggest particular course resources to them. This recommendation system makes course resources that users might be interested in based on their browsing history, browsing patterns, and browsing preferences. User registration and login, course retrieval, browsing history, course recommendation, and a module for course scoring are among the system’s primary features. Studies reveal that this method’s recommendation accuracy is up to 96.2 percent, or about 10% higher than that of conventional recommendation methods. The recommendation strategy put forth in this paper has a good recommendation effect, high accuracy, and coverage. It also plays a part in improving the hidden semantic model’s accuracy. For individualised curriculum resource recommendations, this recommendation system offers a good solution.

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“…With the growing use of data mining (DM) technology in the education sector, educators are now required to categorise various research objects, create research models for each type, gather a variety of user data, and then use a variety of algorithms, relational graph models, or music course resource classifiers to create a music expert system based on big data [ 6 , 7 ]. The expressive singing technique used in solfeggio can help students better understand music and increase their desire to express it.…”

Section: Introductionmentioning

confidence: 99%

[Retracted] Practice and Exploration of Music Solfeggio Teaching Based on Data Mining Technology

Zhang

2022

Journal of Environmental and Public Health

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People can learn, understand, and use music using the solfeggio method. People involved in professional music training have given it importance because it is a fundamental discipline of enlightenment music and a necessary training method and technical theory course to enter the professional level. This article presents an in-depth analysis of the music curriculum model based on data mining technology. Additionally, a music style classification method based on FP Growth association rules mining is developed, which decreases the number of frequent element sets needed and speeds up database scanning. To better match the characteristics of music, a multirepetition structure model is used, and the MFCC (Mel-frequency cepstral coefficients) function is used to set the repetition structure model. The results demonstrate that the music style classification method put forth in this article has clear advantages in terms of efficiency: when the minimum support is 0.2 percent, this method’s execution time is about 33 percent compared to the other methods. The outcomes of the experiment suggest that this method can more accurately capture the repeatability of music and enhance separation performance to some extent.

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Energy-aware scheduling for dependent tasks in heterogeneous multiprocessor systems

Cited by 63 publications

References 24 publications

Pan-Logical Probabilistic Algorithms Based on Convolutional Neural Networks

Pan-Logical Probabilistic Algorithms Based on Convolutional Neural Networks

[Retracted] Personalised Recommendation of PE Network Course Environment Resources Using Data Mining Analysis

[Retracted] Practice and Exploration of Music Solfeggio Teaching Based on Data Mining Technology

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