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Journal articles on the topic 'OpenBCI'

Author: Grafiati

Published: 4 June 2021

Last updated: 28 May 2022

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1

Wu, Na, Hao JIN, Xiachuan Pei, Shurong Dong, Jikui Luo, Ruijian Yan, and Gang Feng. "Gesture recognition system based on CNN-IndRNN and OpenBCI." MATEC Web of Conferences 336 (2021): 06003. http://dx.doi.org/10.1051/matecconf/202133606003.

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Surface electromyography (sEMG), as a key technology of non-invasive muscle computer interface, is an important method of human-computer interaction. We proposed a CNN-IndRNN (Convolutional Neural Network-Independent Recurrent Neural Network) hybrid algorithm to analyse sEMG signals and classify hand gestures. Ninapro’s dataset of 10 volunteers was used to develop the model, and by using only one time-domain feature (root mean square of sEMG), an average accuracy of 87.43% on 18 gestures is achieved. The proposed algorithm obtains a state-of-the-art classification performance with a significantly reduced model. In order to verify the robustness of the CNN-IndRNN model, a compact real¬time recognition system was constructed. The system was based on open-source hardware (OpenBCI) and a custom Python-based software. Results show that the 10-subject rock-paper-scissors gesture recognition accuracy reaches 99.1%.

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Jukiewicz, Marcin, and Anna Cysewska-Sobusiak. "Stimuli design for SSVEP-based brain computer-interface." International Journal of Electronics and Telecommunications 62, no. 2 (June 1, 2016): 109–13. http://dx.doi.org/10.1515/eletel-2016-0014.

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Abstract The paper presents a process of stimuli design for SSVEP-based brain computer-interface. A brain computer-interface can be used in direct communication between a brain and a computer, without using muscles. This device is useful for paralyzed people to communicate with the surrounding environment. Design process should provide high accuracy recognition of presented stimuli and high user comfort. It is widely known how to make stimuli for BCI which are using high-grade EEG. Over recent years cheaper EEGs are becoming more and more popular, for example OpenBCI, which uses ADS1299 amplifier. In this article we review past works of other authors and compare it with our results, obtained using EEG mentioned before. We try to confirm that it is possible to use successfully OpenBCI in BCI projects.

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3

Xin, Xu, Chen Zan, Li Xiaojian, and Jiang Lan. "Design and Implementation of Brain-Apparatus Conversations Portable EEG Monitoring System based on OpenBCI." International Journal of Performability Engineering 16, no. 10 (2020): 1646. http://dx.doi.org/10.23940/ijpe.20.10.p16.16461654.

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4

Suryotrisongko, Hatma, and Febriliyan Samopa. "Evaluating OpenBCI Spiderclaw V1 Headwear's Electrodes Placements for Brain-Computer Interface (BCI) Motor Imagery Application." Procedia Computer Science 72 (2015): 398–405. http://dx.doi.org/10.1016/j.procs.2015.12.155.

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5

Dang, Xin, Bingbing Kang, Xuyang Liu, and Guangyu Cui. "An Interactive Care System Based on a Depth Image and EEG for Aged Patients with Dementia." Journal of Healthcare Engineering 2017 (2017): 1–8. http://dx.doi.org/10.1155/2017/4128183.

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Due to the limitations of the body movement and functional decline of the aged with dementia, they can hardly make an efficient communication with nurses by language and gesture language like a normal person. In order to improve the efficiency in the healthcare communication, an intelligent interactive care system is proposed in this paper based on a multimodal deep neural network (DNN). The input vector of the DNN includes motion and mental features and was extracted from a depth image and electroencephalogram that were acquired by Kinect and OpenBCI, respectively. Experimental results show that the proposed algorithm simplified the process of the recognition and achieved 96.5% and 96.4%, respectively, for the shuffled dataset and 90.9% and 92.6%, respectively, for the continuous dataset in terms of accuracy and recall rate.

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6

Zou, Guoxia. "The Recognition of Action Idea EEG with Deep Learning." Complexity 2022 (January 29, 2022): 1–13. http://dx.doi.org/10.1155/2022/5308885.

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The recognition in electroencephalogram (EEG) of action idea is to identify what action people want to do by EEG. The significance of this project is to help people who have trouble in movement. Their action ideas are identified by EEG, and then robot hands can assist them to complete the action. This paper, with comparative experiments, used OpenBCI to collect EEG action ideas during static action and dynamic action and used the EEG recognition model Conv1D-GRU to training and recognition action, respectively. The experimental result shows that the brain wave action idea is easier to recognize in static state. The accuracy of brain wave action idea recognition in dynamic state is only 72.27%, and the accuracy of brain wave action idea recognition in static state is 99.98%. The experimental result confirms that the action idea will be of great help to people with mobility difficulties.

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Martínez-Cerveró, Jayro, Majid Khalili Ardali, Andres Jaramillo-Gonzalez, Shizhe Wu, Alessandro Tonin, Niels Birbaumer, and Ujwal Chaudhary. "Open Software/Hardware Platform for Human-Computer Interface Based on Electrooculography (EOG) Signal Classification." Sensors 20, no. 9 (April 25, 2020): 2443. http://dx.doi.org/10.3390/s20092443.

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Electrooculography (EOG) signals have been widely used in Human-Computer Interfaces (HCI). The HCI systems proposed in the literature make use of self-designed or closed environments, which restrict the number of potential users and applications. Here, we present a system for classifying four directions of eye movements employing EOG signals. The system is based on open source ecosystems, the Raspberry Pi single-board computer, the OpenBCI biosignal acquisition device, and an open-source python library. The designed system provides a cheap, compact, and easy to carry system that can be replicated or modified. We used Maximum, Minimum, and Median trial values as features to create a Support Vector Machine (SVM) classifier. A mean of 90% accuracy was obtained from 7 out of 10 subjects for online classification of Up, Down, Left, and Right movements. This classification system can be used as an input for an HCI, i.e., for assisted communication in paralyzed people.

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8

Md Ahnaf Shariar, Syeda Maliha Monowara, Md. Shafayat Ul Islam, Muhammed Junaid Noor Jawad, and Saifur Rahman Sabuj. "Brainwave assistive system for paralyzed individuals." ITU Journal on Future and Evolving Technologies 2, no. 3 (July 15, 2021): 79–89. http://dx.doi.org/10.52953/ibjp6517.

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The Brain-Computer Interface (BCI) is a system based on brainwaves that can be used to translate and comprehend the innumerable activities of the brain. Brainwave refers to the bioelectric impulses invariably produced in the human brain during neurotransmission, often measured as the action potential. Moreover, BCI essentially uses the widely studied Electroencephalography (EEG) technique to capture brainwave data. Paralysis generally occurs when there is a disturbance in the central nervous system prompted by a neurodegenerative or unforeseen event. To overcome the obstacles associated with paralysis, this paper on the brainwave-assistive system is based on the BCI incorporated with Internet-of-things. BCI can be implemented to achieve control over external devices and applications. For instance, the process of cursor control, motor control, neuroprosthetics and wheelchair control, etc. In this paper, the OpenBCI Cyton-biosensing board has been used for the collection of the EEG data. The accumulated EEG data is executed subsequently to obtain control over the respective systems in real-time. Hence, it can be concluded that the experiments of the paper support the idea of controlling an interfaced system through the real-time application of EEG data.

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9

Durka, P. J., R. Kuś, J. Żygierewicz, M. Michalska, P. Milanowski, M. Łabęcki, T. Spustek, D. Laszuk, A. Duszyk, and M. Kruszyński. "User-centered design of brain-computer interfaces: OpenBCI.pl and BCI Appliance." Bulletin of the Polish Academy of Sciences: Technical Sciences 60, no. 3 (December 1, 2012): 427–31. http://dx.doi.org/10.2478/v10175-012-0054-1.

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Abstract Brain-Computer Interface (BCI) allows for non-muscular communication with external world, which may be the only way of communication for patients in a locked-in state. This paper presents a complete software framework for BCI, a novel hardware solution for stimuli rendering in BCIs based on Steady State Visual Evoked Potentials (SSVEP), and a univariate algorithm for detection of SSVEP in the EEG time series. OpenBCI is a complete software framework for brain-computer interfaces. Owing to an open license and modular architecture, it allows for flexible implementations of different communication channels in the serial or parallel hybrid mode, minimization of costs and improvements of stability and efficiency. Complete software is freely available from http://openbci.pl. BCI Appliance is a hardware solution that allows for dynamic control of menus with stable generation of stimuli for the SSVEP paradigm. The novelty consists of a design, whereby the LCD screen is illuminated from behind using an array of LEDs. Design pioneers also proposed a new line of thought about the user-centered design of BCI systems: a simple box with one on/off button, minimum embedded software, wireless connections to domotic and EEG acquisition devices, and user-controlled mode switching in a hybrid BCI.

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10

Castro-García, Juan Antonio, Alberto Jesús Molina-Cantero, Isabel María Gómez-González, Sergio Lafuente-Arroyo, and Manuel Merino-Monge. "Towards Human Stress and Activity Recognition: A Review and a First Approach Based on Low-Cost Wearables." Electronics 11, no. 1 (January 4, 2022): 155. http://dx.doi.org/10.3390/electronics11010155.

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Detecting stress when performing physical activities is an interesting field that has received relatively little research interest to date. In this paper, we took a first step towards redressing this, through a comprehensive review and the design of a low-cost body area network (BAN) made of a set of wearables that allow physiological signals and human movements to be captured simultaneously. We used four different wearables: OpenBCI and three other open-hardware custom-made designs that communicate via bluetooth low energy (BLE) to an external computer—following the edge-computingconcept—hosting applications for data synchronization and storage. We obtained a large number of physiological signals (electroencephalography (EEG), electrocardiography (ECG), breathing rate (BR), electrodermal activity (EDA), and skin temperature (ST)) with which we analyzed internal states in general, but with a focus on stress. The findings show the reliability and feasibility of the proposed body area network (BAN) according to battery lifetime (greater than 15 h), packet loss rate (0% for our custom-made designs), and signal quality (signal-noise ratio (SNR) of 9.8 dB for the ECG circuit, and 61.6 dB for the EDA). Moreover, we conducted a preliminary experiment to gauge the main ECG features for stress detection during rest.

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11

Wülfers, Eike M., Zhasur Zhamoliddinov, Olaf Dössel, and Gunnar Seemann. "Accelerating mono-domain cardiac electrophysiology simulations using OpenCL." Current Directions in Biomedical Engineering 1, no. 1 (September 1, 2015): 413–17. http://dx.doi.org/10.1515/cdbme-2015-0100.

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AbstractUsing OpenCL, we developed a cross-platform software to compute electrical excitation conduction in cardiac tissue. OpenCL allowed the software to run parallelized and on different computing devices (e.g., CPUs and GPUs). We used the macroscopic mono-domain model for excitation conduction and an atrial myocyte model by Courtemanche et al. for ionic currents. On a CPU with 12 HyperThreading-enabled Intel Xeon 2.7 GHz cores, we achieved a speed-up of simulations by a factor of 1.6 against existing software that uses OpenMPI. On two high-end AMD FirePro D700 GPUs the OpenCL software ran 2.4 times faster than the OpenMPI implementation. The more nodes the discretized simulation domain contained, the higher speed-ups were achieved.

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12

Bonati, Claudio, Enrico Calore, Massimo D’Elia, Michele Mesiti, Francesco Negro, Francesco Sanfilippo, Sebastiano Fabio Schifano, Giorgio Silvi, and Raffaele Tripiccione. "Portable multi-node LQCD Monte Carlo simulations using OpenACC." International Journal of Modern Physics C 29, no. 01 (January 2018): 1850010. http://dx.doi.org/10.1142/s0129183118500109.

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This paper describes a state-of-the-art parallel Lattice QCD Monte Carlo code for staggered fermions, purposely designed to be portable across different computer architectures, including GPUs and commodity CPUs. Portability is achieved using the OpenACC parallel programming model, used to develop a code that can be compiled for several processor architectures. The paper focuses on parallelization on multiple computing nodes using OpenACC to manage parallelism within the node, and OpenMPI to manage parallelism among the nodes. We first discuss the available strategies to be adopted to maximize performances, we then describe selected relevant details of the code, and finally measure the level of performance and scaling-performance that we are able to achieve. The work focuses mainly on GPUs, which offer a significantly high level of performances for this application, but also compares with results measured on other processors.

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13

Matsusaka, Yosuke. "OpenHRI." Journal of the Robotics Society of Japan 31, no. 3 (2013): 216–21. http://dx.doi.org/10.7210/jrsj.31.216.

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14

Kan, Guangyuan, Xiaoyan He, Liuqian Ding, Jiren Li, Ke Liang, and Yang Hong. "A heterogeneous computing accelerated SCE-UA global optimization method using OpenMP, OpenCL, CUDA, and OpenACC." Water Science and Technology 76, no. 7 (June 6, 2017): 1640–51. http://dx.doi.org/10.2166/wst.2017.322.

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The shuffled complex evolution optimization developed at the University of Arizona (SCE-UA) has been successfully applied in various kinds of scientific and engineering optimization applications, such as hydrological model parameter calibration, for many years. The algorithm possesses good global optimality, convergence stability and robustness. However, benchmark and real-world applications reveal the poor computational efficiency of the SCE-UA. This research aims at the parallelization and acceleration of the SCE-UA method based on powerful heterogeneous computing technology. The parallel SCE-UA is implemented on Intel Xeon multi-core CPU (by using OpenMP and OpenCL) and NVIDIA Tesla many-core GPU (by using OpenCL, CUDA, and OpenACC). The serial and parallel SCE-UA were tested based on the Griewank benchmark function. Comparison results indicate the parallel SCE-UA significantly improves computational efficiency compared to the original serial version. The OpenCL implementation obtains the best overall acceleration results however, with the most complex source code. The parallel SCE-UA has bright prospects to be applied in real-world applications.

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15

Ramírez-Moreno, Mauricio A., Patricio Carrillo-Tijerina, Milton Osiel Candela-Leal, Myriam Alanis-Espinosa, Juan Carlos Tudón-Martínez, Armando Roman-Flores, Ricardo A. Ramírez-Mendoza, and Jorge de J. Lozoya-Santos. "Evaluation of a Fast Test Based on Biometric Signals to Assess Mental Fatigue at the Workplace—A Pilot Study." International Journal of Environmental Research and Public Health 18, no. 22 (November 12, 2021): 11891. http://dx.doi.org/10.3390/ijerph182211891.

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Non-pathological mental fatigue is a recurring, but undesirable condition among people in the fields of office work, industry, and education. This type of mental fatigue can often lead to negative outcomes, such as performance reduction and cognitive impairment in education; loss of focus and burnout syndrome in office work; and accidents leading to injuries or death in the transportation and manufacturing industries. Reliable mental fatigue assessment tools are promising in the improvement of performance, mental health and safety of students and workers, and at the same time, in the reduction of risks, accidents and the associated economic loss (e.g., medical fees and equipment reparations). The analysis of biometric (brain, cardiac, skin conductance) signals has proven to be effective in discerning different stages of mental fatigue; however, many of the reported studies in the literature involve the use of long fatigue-inducing tests and subject-specific models in their methodologies. Recent trends in the modeling of mental fatigue suggest the usage of non subject-specific (general) classifiers and a time reduction of calibration procedures and experimental setups. In this study, the evaluation of a fast and short-calibration mental fatigue assessment tool based on biometric signals and inter-subject modeling, using multiple linear regression, is presented. The proposed tool does not require fatigue-inducing tests, which allows fast setup and implementation. Electroencephalography, photopletismography, electrodermal activity, and skin temperature from 17 subjects were recorded, using an OpenBCI helmet and an Empatica E4 wristband. Correlations to self-reported mental fatigue levels (using the fatigue assessment scale) were calculated to find the best mental fatigue predictors. Three-class mental fatigue models were evaluated, and the best model obtained an accuracy of 88% using three features, β/θ (C3), and the α/θ (O2 and C3) ratios, from one minute of electroencephalography measurements. The results from this pilot study show the feasibility and potential of short-calibration procedures and inter-subject classifiers in mental fatigue modeling, and will contribute to the use of wearable devices for the development of tools oriented to the well-being of workers and students, and also in daily living activities.

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16

Maruyama, Naoya, and Tetsuya Hoshino. "3. OpenACC Programming." Journal of the Institute of Image Information and Television Engineers 66, no. 10 (2012): 817–22. http://dx.doi.org/10.3169/itej.66.817.

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17

Krischmann, T., H. Urban, and C. Schranz. "Entwicklung eines openBIM-Bewilligungsverfahrens/Development of an openBIM submission process." Bauingenieur 95, no. 09 (2020): 335–44. http://dx.doi.org/10.37544/0005-6650-2020-09-61.

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Zusammenfassung Das BIM-Modell als zentrale Stelle der Daten und Informationen weist vielfältige Potenziale für den gesamten Lebenszyklus eines Bauwerks auf. Noch weitgehend ungenutzt sind diese Vorteile im Baubewilligungsverfahren. Die Stadt Wien betritt einen sehr innovativen Weg und startete das von der EU geförderte Forschungsprojekt BRISE-Vienna, in dem ein komplettes openBIM-Bewilligungsverfahren entwickelt wird. Dieser Artikel befasst sich mit den dafür notwendigen openBIM-Grundlagen, den Prüfroutinen sowie der rechtlichen Situation in Wien. Sie dienen als Basis für die Definition unterschiedlicher BIM-basierter Modelle, die im Zuge des Baubewilligungsverfahrens erforderlich sind. Neben dem von den Planenden eingereichtem Bauantragsmodell entstehen aus baurechtlichen Anforderungen ein Referenzmodell und ein Antragsinformationsmodell. Die letzteren Modelle dienen der teilautomatischen baurechtlichen Überprüfung des Bauantragsmodells. Für die Modellprüfung ist die Entwicklung eines detaillierten Prüfsettings erforderlich. Dies ist ein iterativer Entwicklungsprozess, der im Anschluss an das Forschungsprojekt schrittweise in den Realbetrieb eines openBIM-Bewilligungsverfahrens übergehen soll.

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18

Stolarski, Kamil. "OpenBIM kompatybilny z prawem." MATERIAŁY BUDOWLANE 1, no. 3 (March 5, 2018): 86–87. http://dx.doi.org/10.15199/33.2018.03.34.

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19

Meinel, Christoph. "MOOCs – am Beispiel openHPI." Informatik-Spektrum 38, no. 2 (February 5, 2015): 142–46. http://dx.doi.org/10.1007/s00287-015-0873-1.

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20

Xiao, Yanjia, Xiaobin Ji, Beijiang Liu, and Xi’an Xiong. "Partial wave analysis with OpenAcc." EPJ Web of Conferences 245 (2020): 06040. http://dx.doi.org/10.1051/epjconf/202024506040.

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Partial wave analysis(PWA) is an important tool in hadron physics. Large data sets from the experiments in high precision frontier require high computational power. To utilize GPU cluster and the resource of super computers with various types of accelerator, we implement a software framework for partial wave analysis using OpenAcc, OpenAccPWA. OpenAccPWA provides convenient approaches for exposing parallelism in the code and excellent support for the large amount of existing CPU-based codes of partial wave amplitudes. It can avoid heavy workload of code migration from CPU to GPU. This proceeding will briefly introduce the software framework and performance of OpenAccPWA.

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21

Alshahrani, Saeed, Waleed Al Shehri, Jameel Almalki, Ahmed M. Alghamdi, and Abdullah M. Alammari. "Accelerating Spark-Based Applications with MPI and OpenACC." Complexity 2021 (July 21, 2021): 1–17. http://dx.doi.org/10.1155/2021/9943289.

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The amount of data produced in scientific and commercial fields is growing dramatically. Correspondingly, big data technologies, such as Hadoop and Spark, have emerged to tackle the challenges of collecting, processing, and storing such large-scale data. Unfortunately, big data applications usually have performance issues and do not fully exploit a hardware infrastructure. One reason is that applications are developed using high-level programming languages that do not provide low-level system control in terms of performance of highly parallel programming models like message passing interface (MPI). Moreover, big data is considered a barrier of parallel programming models or accelerators (e.g., CUDA and OpenCL). Therefore, the aim of this study is to investigate how the performance of big data applications can be enhanced without sacrificing the power consumption of a hardware infrastructure. A Hybrid Spark MPI OpenACC (HSMO) system is proposed for integrating Spark as a big data programming model, with MPI and OpenACC as parallel programming models. Such integration brings together the advantages of each programming model and provides greater effectiveness. To enhance performance without sacrificing power consumption, the integration approach needs to exploit the hardware infrastructure in an intelligent manner. For achieving this performance enhancement, a mapping technique is proposed that is built based on the application’s virtual topology as well as the physical topology of the undelaying resources. To the best of our knowledge, there is no existing method in big data applications related to utilizing graphics processing units (GPUs), which are now an essential part of high-performance computing (HPC) as a powerful resource for fast computation.

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Lashgar, Ahmad, and Amirali Baniasadi. "Employing Software-Managed Caches in OpenACC." ACM Transactions on Modeling and Performance Evaluation of Computing Systems 1, no. 1 (March 31, 2016): 1–34. http://dx.doi.org/10.1145/2798724.

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Montazerolghaem, Ahmadreza, Mohammad Hossein Yaghmaee Moghaddam, and Alberto Leon-Garcia. "OpenAMI: Software-Defined AMI Load Balancing." IEEE Internet of Things Journal 5, no. 1 (February 2018): 206–18. http://dx.doi.org/10.1109/jiot.2017.2778006.

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Reyes, Ruymán, Iván López, Juan J. Fumero, and Francisco de Sande. "A preliminary evaluation of OpenACC implementations." Journal of Supercomputing 65, no. 3 (January 31, 2013): 1063–75. http://dx.doi.org/10.1007/s11227-012-0853-z.

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Li, Xuechao, and Po-Chou Shih. "An Early Performance Comparison of CUDA and OpenACC." MATEC Web of Conferences 208 (2018): 05002. http://dx.doi.org/10.1051/matecconf/201820805002.

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This paper presents a performance comparison between CUDA and OpenACC. The performance analysis focuses on programming models and underlying compilers. In addition, we proposed a Performance Ratio of Data Sensitivity (PRoDS) metric to objectively compare traditional subjective performances: how sensitive OpenACC and CUDA implementations are to change in data size. The results show that in terms of kernel running time, the OpenACC performance is lower than the CUDA performance because PGI compiler needs to translate OpenACC kernels into object code while CUDA codes can be directly run. Besides, OpenACC programs are more sensitive to data changes than the equivalent CUDA programs with optimizations, but CUDA is more sensitive to data changes than OpenACC if there are no optimizations. Overall we found that OpenACC is a reliable programming model and a good alternative to CUDA for accelerator devices.

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Padillo Saoud, Abdenour. "Reseña de Open Islamicate Texts Initiative (OpenITI)." Revista de Humanidades Digitales 4 (November 1, 2019): 187. http://dx.doi.org/10.5944/rhd.vol.4.2019.24167.

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En este texto se reseña una de las principales iniciativas en Humanidades Digitales relacionadas con los estudios islámicos clásicos. OpenITI consiste en un corpus de textos islámicos pre-modernos que pretende establecer la infraestructura tecnológica necesaria para incorporar las nuevas formas de análisis y tratamiento computacional de la información a los estudios islámicos.

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KANG, Pilsung. "OpenACC Parallelization of Stochastic Simulations on GPUs." IEICE Transactions on Information and Systems E102.D, no. 8 (August 1, 2019): 1565–68. http://dx.doi.org/10.1587/transinf.2019edl8032.

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28

Jiang, Shaohua, Liping Jiang, Yunwei Han, Zheng Wu, and Na Wang. "OpenBIM: An Enabling Solution for Information Interoperability." Applied Sciences 9, no. 24 (December 8, 2019): 5358. http://dx.doi.org/10.3390/app9245358.

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The expansion of scale and the increase of complexity of construction projects puts higher requirements on the level of collaboration among different stakeholders. How to realize better information interoperability among multiple disciplines and different software platforms becomes a key problem in the collaborative process. openBIM (building information model), as a common approach of information exchange, can meet the needs of information interaction among different software well and improve the efficiency and accuracy of collaboration. To the best of our knowledge, there is currently no comprehensive survey of openBIM approach in the context of the AEC (Architecture, Engineering & Construction) industry, this paper fills the gap and presents a literature review of openBIM. In this paper, the openBIM related standards, software platforms, and tools enabling information interoperability are introduced and analyzed comprehensively based on related websites and literature. Furthermore, engineering information interoperability research supported by openBIM is analyzed from the perspectives of information representation, information query, information exchange, information extension, and information integration. Finally, research gaps and future directions are presented based on the analysis of existing research. The systematic analysis of the theory and practice of openBIM in this paper can provide support for its further research and application.

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29

Peng, Cong, Prashant Goswami, and Guohua Bai. "Fuzzy Matching of OpenAPI Described REST Services." Procedia Computer Science 126 (2018): 1313–22. http://dx.doi.org/10.1016/j.procs.2018.08.081.

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30

Pereira, Alyson D., Rodrigo C. O. Rocha, Márcio Castro, Luís F. W. Góes, and Mario A. R. Dantas. "Enabling efficient stencil code generation in OpenACC." Procedia Computer Science 108 (2017): 2333–37. http://dx.doi.org/10.1016/j.procs.2017.05.155.

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31

Majumdar, Pushan. "Lattice QCD simulations using the OpenACC platform." Journal of Physics: Conference Series 759 (October 2016): 012070. http://dx.doi.org/10.1088/1742-6596/759/1/012070.

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32

Bonati, Claudio, Enrico Calore, Simone Coscetti, Massimo D’Elia, Michele Mesiti, Francesco Negro, Sebastiano Fabio Schifano, Giorgio Silvi, and Raffaele Tripiccione. "Portable LQCD Monte Carlo code using OpenACC." EPJ Web of Conferences 175 (2018): 09008. http://dx.doi.org/10.1051/epjconf/201817509008.

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Varying from multi-core CPU processors to many-core GPUs, the present scenario of HPC architectures is extremely heterogeneous. In this context, code portability is increasingly important for easy maintainability of applications; this is relevant in scientific computing where code changes are numerous and frequent. In this talk we present the design and optimization of a state-of-the-art production level LQCD Monte Carlo application, using the OpenACC directives model. OpenACC aims to abstract parallel programming to a descriptive level, where programmers do not need to specify the mapping of the code on the target machine. We describe the OpenACC implementation and show that the same code is able to target different architectures, including state-of-the-art CPUs and GPUs.

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Alghamdi, Ahmed Mohammed, and Fathy Elbouraey Eassa. "OpenACC Errors Classification and Static Detection Techniques." IEEE Access 7 (2019): 113235–53. http://dx.doi.org/10.1109/access.2019.2935498.

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34

Hewitt, Sam, Lee Margetts, Alistair Revell, Pankaj Pankaj, and Francesc Levrero-Florencio. "OpenFPCI: A parallel fluid–structure interaction framework." Computer Physics Communications 244 (November 2019): 469–82. http://dx.doi.org/10.1016/j.cpc.2019.05.016.

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Santos, A., F. Almeida, V. Blanco, and J. C. Castillo. "Web services based scheduling in OpenCF." Journal of Supercomputing 58, no. 2 (November 7, 2009): 168–76. http://dx.doi.org/10.1007/s11227-009-0352-z.

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Kang, Zhijiang, Ze Deng, Wei Han, and Dongmei Zhang. "Parallel Reservoir Simulation with OpenACC and Domain Decomposition." Algorithms 11, no. 12 (December 18, 2018): 213. http://dx.doi.org/10.3390/a11120213.

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Parallel reservoir simulation is an important approach to solving real-time reservoir management problems. Recently, there is a new trend of using a graphics processing unit (GPU) to parallelize the reservoir simulations. Current GPU-aided reservoir simulations focus on compute unified device architecture (CUDA). Nevertheless, CUDA is not functionally portable across devices and incurs high amount of code. Meanwhile, domain decomposition is not well used for GPU-based reservoir simulations. In order to address the problems, we propose a parallel method with OpenACC to accelerate serial code and reduce the time and effort during porting an application to GPU. Furthermore, the GPU-aided domain decomposition is developed to accelerate the efficiency of reservoir simulation. The experimental results indicate that (1) the proposed GPU-aided approach can outperform the CPU-based one up to about two times, meanwhile with the help of OpenACC, the workload of the transplant code was reduced significantly by about 22 percent of the source code, (2) the domain decomposition method can further improve the execution efficiency up to 1.7×. The proposed parallel reservoir simulation method is a efficient tool to accelerate reservoir simulation.

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O'Keeffe, Shawn E. "OpenBIM Framework for a Collaborative Historic Preservation System." International Journal of 3-D Information Modeling 5, no. 4 (October 2016): 1–11. http://dx.doi.org/10.4018/ij3dim.2016100101.

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The authors have developed a novel system framework for a historic preservation system utilising open standards and open source tools. The framework enables the integration of open standard 3D models and GIS in a virtual environment (VE). It also allows the storage and harvesting of data via an open source web-based central repository. The framework is designed for bi-directional interoperability when utilised for monument tracking, preservation, conservation, re-excavation, etc. To date, no such system framework exists for the development and management of historic monuments using open standards e57 for terrestrial laser scanning (TLS) data, the industry foundation classes (IFC) for 3D semantic rich models, and CityGML for integrating IFC and GIS in a VE. The web-based VE is accessed from the BimServer and envisaged for monitoring monument erosion, movement, and damage to monuments by human activity or nature, collaboration between different industry actors to share knowledge, experience, and expertise globally, etc.

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Yee, Jaeyong, and Mira Park. "Parallel GWAS Calculation Compared with OpenMP and OpenACC." Korean Data Analysis Society 19, no. 6 (December 31, 2017): 2853–62. http://dx.doi.org/10.37727/jkdas.2017.19.6.2853.

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Kešelj, Sergej. "INTERPRETER REST API SERVISA BAZIRAN NA OPENAPI SPECIFIKACIJI." Zbornik radova Fakulteta tehničkih nauka u Novom Sadu 34, no. 06 (May 24, 2019): 1064–67. http://dx.doi.org/10.24867/03be11keselj.

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Ramakrishnan, Chandrasekhar, Andrej Bieri, Nora Sauter, Sophie Roizard, Philippe Ringler, Shirley A. Müller, Kenneth N. Goldie, et al. "openBEB: open biological experiment browser for correlative measurements." BMC Bioinformatics 15, no. 1 (2014): 84. http://dx.doi.org/10.1186/1471-2105-15-84.

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Eassa, Fathy Elbouraey, Ahmed Mohammed Alghamdi, Seif Haridi, Maher Ali Khemakhem, Abdullah S. Al-Malaise Al-Ghamdi, and Eesa A. Alsolami. "ACC_TEST: Hybrid Testing Approach for OpenACC-Based Programs." IEEE Access 8 (2020): 80358–68. http://dx.doi.org/10.1109/access.2020.2991009.

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Markidis, Stefano, Jing Gong, Michael Schliephake, Erwin Laure, Alistair Hart, David Henty, Katherine Heisey, and Paul Fischer. "OpenACC acceleration of the Nek5000 spectral element code." International Journal of High Performance Computing Applications 29, no. 3 (March 30, 2015): 311–19. http://dx.doi.org/10.1177/1094342015576846.

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Bock, Bernhard, and Eberhard Michaelis. "Building Information Modeling in der Abwasserableitung mit openBIM." Wasser und Abfall 21, no. 5 (May 2019): 36–42. http://dx.doi.org/10.1007/s35152-019-0042-y.

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Dodge, Catherine, Cynthia Irvine, and Thuy Nguyen. "A study of initialization in Linux and OpenBSD." ACM SIGOPS Operating Systems Review 39, no. 2 (April 2005): 79–93. http://dx.doi.org/10.1145/1055218.1055226.

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Zhao, Jonathan, Márk Lakatos-Tóth, Matthew Westerham, Zhikang Zhang, Avi Moskoff, and Fengbo Ren. "OpenICS: Open image compressive sensing toolbox and benchmark." Software Impacts 9 (August 2021): 100081. http://dx.doi.org/10.1016/j.simpa.2021.100081.

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Guan, Z., J. Sun, Z. Wang, Y. Geng, and W. Xu. "Development of an Open Metadata Schema for Prospective Clinical Research (openPCR) in China." Methods of Information in Medicine 53, no. 01 (2014): 39–46. http://dx.doi.org/10.3414/me13-01-0008.

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SummaryObjectives: In China, deployment of electronic data capture (EDC) and clinical data management system (CDMS) for clinical research (CR) is in its very early stage, and about 90% of clinical studies collected and submitted clinical data manually. This work aims to build an open metadata schema for Prospective Clinical Research (openPCR) in China based on openEHR archetypes, in order to help Chinese researchers easily create specific data entry templates for registration, study design and clinical data collection.Methods: Singapore Framework for Dublin Core Application Profiles (DCAP) is used to develop openPCR and four steps such as defining the core functional requirements and deducing the core metadata items, developing archetype models, defining metadata terms and creating archetype records, and finally developing implementation syntax are followed.Results: The core functional requirements are divided into three categories: requirements for research registration, requirements for trial design, and requirements for case report form (CRF). 74 metadata items are identified and their Chinese authority names are created. The minimum metadata set of openPCR includes 3 documents, 6 sections, 26 top level data groups, 32 lower data groups and 74 data elements. The top level container in openPCR is composed of public document, internal document and clinical document archetypes. A hierarchical structure of openPCR is established according to Data Structure of Electronic Health Record Architecture and Data Stand -ard of China (Chinese EHR Standard). Meta-data attributes are grouped into six parts: identification, definition, representation, relation, usage guides, and administration.Discussions and Conclusion: OpenPCR is an open metadata schema based on research registration standards, standards of the Clinical Data Interchange Standards Consortium (CDISC) and Chinese healthcare related stand -ards, and is to be publicly available throughout China. It considers future integration of EHR and CR by adopting data structure and data terms in Chinese EHR Standard. Archetypes in openPCR are modularity models and can be separated, recombined, and reused. The authors recommend that the method to develop openPCR can be referenced by other countries when designing metadata schema of clinical research. In the next steps, openPCR should be used in a number of CR projects to test its applicability and to continuously improve its coverage. Besides, metadata schema for research protocol can be developed to structurize and standardize protocol, and syntactical interoperability of openPCR with other related standards can be considered.

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Mohammadi, Sajad, Hamidreza Karami, Mohammad Azadifar, and Farhad Rachidi. "On the Efficiency of OpenACC-aided GPU-Based FDTD Approach: Application to Lightning Electromagnetic Fields." Applied Sciences 10, no. 7 (March 30, 2020): 2359. http://dx.doi.org/10.3390/app10072359.

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An open accelerator (OpenACC)-aided graphics processing unit (GPU)-based finite difference time domain (FDTD) method is presented for the first time for the 3D evaluation of lightning radiated electromagnetic fields along a complex terrain with arbitrary topography. The OpenACC directive-based programming model is used to enhance the computational performance, and the results are compared with those obtained by using a CPU-based model. It is shown that OpenACC GPUs can provide very accurate results, and they are more than 20 times faster than CPUs. The presented results support the use of OpenACC not only in relation to lightning electromagnetics problems, but also to large-scale realistic electromagnetic compatibility (EMC) applications in which computation time efficiency is a critical factor.

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Lee, Joo Hwan, Nimit Nigania, Hyesoon Kim, Kaushik Patel, and Hyojong Kim. "OpenCL Performance Evaluation on Modern Multicore CPUs." Scientific Programming 2015 (2015): 1–20. http://dx.doi.org/10.1155/2015/859491.

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Utilizing heterogeneous platforms for computation has become a general trend, making the portability issue important. OpenCL (Open Computing Language) serves this purpose by enabling portable execution on heterogeneous architectures. However, unpredictable performance variation on different platforms has become a burden for programmers who write OpenCL applications. This is especially true for conventional multicore CPUs, since the performance of general OpenCL applications on CPUs lags behind the performance of their counterparts written in the conventional parallel programming model for CPUs. In this paper, we evaluate the performance of OpenCL applications on out-of-order multicore CPUs from the architectural perspective. We evaluate OpenCL applications on various aspects, including API overhead, scheduling overhead, instruction-level parallelism, address space, data location, data locality, and vectorization, comparing OpenCL to conventional parallel programming models for CPUs. Our evaluation indicates unique performance characteristics of OpenCL applications and also provides insight into the optimization metrics for better performance on CPUs.

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Şimşek, Buğra, and Nursel Akçam. "Heterogenous Computing on Iris Matching with OpenCL." Applied Mechanics and Materials 850 (August 2016): 129–35. http://dx.doi.org/10.4028/www.scientific.net/amm.850.129.

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This study presents parallelization of Hamming Distance algorithm, which is used for iris comparison on iris recognition systems, for heterogeneous systems that can be included Central Processing Units (CPUs), Graphics Processing Units (GPUs), Digital Signal Processing (DSP) boards, Field Programmable Gate Array (FPGA) and some other mobile platforms with OpenCL. OpenCL allows to run same code on CPUs, GPUs, FPGAs and DSP boards. Heterogeneous computing refers to systems include different kind of devices (CPUs, GPUs, FPGAs and other accelerators). Heterogeneous computing gains performance or reduces power for suitable algorithms on these OpenCL supported devices. In this study, Hamming Distance algorithm has been coded with C++ as a sequential code and has been parallelized a designated method by us with OpenCL. Our OpenCL code has been executed on Nvidia GT430 GPU and Intel Xeon 5650 processor. The OpenCL code implementation demonstrates that speed up to 87 times with parallelization. Also our study differs from other studies, which accelerate iris matching, with regard to ensure heterogeneous computing by using OpenCL.

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Stojanovic, Natalija, and Dragan Stojanovic. "Parallelizing Multiple Flow Accumulation Algorithm using CUDA and OpenACC." ISPRS International Journal of Geo-Information 8, no. 9 (September 3, 2019): 386. http://dx.doi.org/10.3390/ijgi8090386.

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Watershed analysis, as a fundamental component of digital terrain analysis, is based on the Digital Elevation Model (DEM), which is a grid (raster) model of the Earth surface and topography. Watershed analysis consists of computationally and data intensive computing algorithms that need to be implemented by leveraging parallel and high-performance computing methods and techniques. In this paper, the Multiple Flow Direction (MFD) algorithm for watershed analysis is implemented and evaluated on multi-core Central Processing Units (CPU) and many-core Graphics Processing Units (GPU), which provides significant improvements in performance and energy usage. The implementation is based on NVIDIA CUDA (Compute Unified Device Architecture) implementation for GPU, as well as on OpenACC (Open ACCelerators), a parallel programming model, and a standard for parallel computing. Both phases of the MFD algorithm (i) iterative DEM preprocessing and (ii) iterative MFD algorithm, are parallelized and run over multi-core CPU and GPU. The evaluation of the proposed solutions is performed with respect to the execution time, energy consumption, and programming effort for algorithm parallelization for different sizes of input data. An experimental evaluation has shown not only the advantage of using OpenACC programming over CUDA programming in implementing the watershed analysis on a GPU in terms of performance, energy consumption, and programming effort, but also significant benefits in implementing it on the multi-core CPU.

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