Implementation of a Beowulf Cluster and Analysis of its Performance in Applications with Parallel Programming

Huamaní, Enrique Lee; Condori, Patricia; Román-Gonzalez, Avid

doi:10.14569/ijacsa.2019.0100869

Cited by 7 publications

(8 citation statements)

References 4 publications

(4 reference statements)

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“…As explained by the research of [22], Big Data offers improved solutions for high amounts of information. To be able to use this type of architecture, the work implemented in the year 2019 of [23] will be employed to provide predictions utilizing a total of 28 computers working in parallel.…”

Section: ) Decision Tree Prediction Resultmentioning

confidence: 99%

Machine Learning Techniques to Visualize and Predict Terrorist Attacks Worldwide using the Global Terrorism Database

Huamaní¹,

Mantari²,

Román-Gonzalez³

2020

IJACSA

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Terrorist attacks affect the confidence and security of citizens; it is a violent form of a political struggle that ends in the destruction of order. In the current decade, along with the growth of social networks, terrorist attacks around the world are still ongoing and have had potential growth in recent years. Consequently, it is necessary to identify where the attacks were committed and where is the possible area for an attack. The objective is to provide assertive solutions to these events. As a solution, this research focuses on one of the branches of artificial intelligence (AI), which is the Automatic Learning, also called Machine Learning. The idea is to use AI techniques to visualize and predict possible terrorist attacks using classification models, the decision trees, and the Random Forest. The input would be a database that has a systematic record of worldwide terrorist attacks from 1970 to the last recorded year, which is 2018. As a final result, it is necessary to know the number of terrorist attacks in the world, the most frequent types of attacks and the number of seizures caused by region; furthermore, to be able to predict what kind of terrorist attack will occur and in which areas of the world. Finally, this research aims to help the scientific community use artificial intelligence to provide various types of solutions related to global events.

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Section: ) Decision Tree Prediction Resultmentioning

confidence: 99%

Machine Learning Techniques to Visualize and Predict Terrorist Attacks Worldwide using the Global Terrorism Database

Huamaní¹,

Mantari²,

Román-Gonzalez³

2020

IJACSA

Self Cite

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“…Many supercomputers have been built in the world, and the three countries, the United States, China, and Japan are the superpower producers of HPC systems in the world. Summit [9], Titan [10], Fugaku [11], Tianhe-I [12], Sunway [13], and Sierra [14] are among the most powerful supercomputers in the world in the Top500 supercomputer list 2 . In this regard, the articles related to the present study as well as the Top500 method as the closest work done in the field of supercomputer ranking and comparison are categorised and reviewed as follows.…”

Section: Related Workmentioning

confidence: 99%

An integrated taxonomy of standard indicators for ranking and selecting supercomputers

Maleki

Mansouri

Arianyan

2023

IET Computers & Digital Tech

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Due to the ever‐increasing computing requirements of modern applications, supercomputers are at the centre of attraction as a platform for high‐performance computing. Although various features and indicators for testing and evaluating supercomputers are proposed in the literature, a comprehensive feature set to guide designers in comparing supercomputers and selecting an appropriate choice is not provided. Here, an integrated feature‐based taxonomy comprised of seven indicator groups including passive infrastructure, hardware, software, support and maintenance, service, business, and security features is proposed. Also, a case study using our proposed framework is provided and a comparison between some commercial and research supercomputers including Fugaku's ideal supercomputer, Sharif supercomputer, Aramco supercomputer, and ITU supercomputer is presented. Moreover, here, the authors’ proposed method is compared with the Top500 method, which shows that the authors’ proposed method facilitates the ranking, comparison, and selection of the appropriate supercomputer in various fields by considering various aspects of design and implementation. The ranking results show that Aramco supercomputer, ITU supercomputer, and Sharif supercomputer have 65.9%, 57.6%, and 48.2% of ideal supercomputer points, respectively.

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“…In the fourth phase we train all the captured data mentioned in the third phase, when training each face obtained we identify each one of the identified faces with a small size centered on the facial expressions, when trained we return each image with its corresponding number in this case we specify the system with a parameter observed in the following figure [21].…”

Section: Training Modelmentioning

confidence: 99%

Use of Artificial Intelligence for Face Detection with Face Mask in Real Time to Control the Entrance to an Entity

Huamaní¹,

Cunyarachi²

2021

IJETAE

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Due to the pandemic caused by Covid-19, daily life has changed significantly. For this reason, biosecurity measures have been implemented to prevent the spread of the virus as an effective way to reactivate economic activities. In this sense, the present paper focuses on real-time face detection as a measure of control at the entrance to an entity, thus avoiding the spread of the virus while recognizing the identity of workers despite the use of masks and thus reducing the risk of entry of individuals outside the organization. Therefore, the objective is to contribute to the security of a company through the application of machine learning methodology. The selection of methodology is justified due to the adaptation of the same according to the interests of this project. Consequently, algorithms were used in a progressive manner, obtaining as a result the control system that was intended, since each particularity of the face of the individual was recognized in relation to its corresponding identification. Finally, the results of this article benefit the security of organizations regardless of their field or sector. Keywords— Control, Detection, Facial Recognition, Facial Mask, Face recognition, Machine learning.

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Implementation of a Beowulf Cluster and Analysis of its Performance in Applications with Parallel Programming

Cited by 7 publications

References 4 publications

Machine Learning Techniques to Visualize and Predict Terrorist Attacks Worldwide using the Global Terrorism Database

Machine Learning Techniques to Visualize and Predict Terrorist Attacks Worldwide using the Global Terrorism Database

An integrated taxonomy of standard indicators for ranking and selecting supercomputers

Use of Artificial Intelligence for Face Detection with Face Mask in Real Time to Control the Entrance to an Entity

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