Network publishing system based on cluster computing technology

The Implementation of Hybrid Parallel Computation for Complex and Fine Reservoir Model Using Cluster Technology

10.29118/ipa21-e-53 ◽

2021 ◽

Author(s):

B. Darmawan

Keyword(s):

Modeling And Simulation ◽

Message Passing Interface ◽

Cluster Computing ◽

Performance Test ◽

Hybrid Approach ◽

Reservoir Modeling ◽

Computing Technology ◽

Reservoir Model ◽

Cluster Technology ◽

Simulation Time

Pertamina EP plays an important role in maintaining the oil production supply for national energy stability. Thus, they bear a great responsibility to accelerate all the development plans and execute them in timely manner. However, there is big challenge in the realization of those plans since they are not fully equipped with the advance computing technology to boost the reservoir modeling and simulation phase. Therefore, the effort on finalizing and executing of 33 Plan of development (POD) projects within 5 years was looked like a never-ending project. To face the challenge, Pertamina EP evaluated the possibility to create a cluster technology that can accommodate high intensity of simulation numbers and high load of simulation process. The evaluation process covers: compiling, sorting and selecting the analog reservoir model (highest grid number and longest simulation time), benchmarking and performance test to get the most optimum cluster configuration. Supercomputer was then procured and set based on the optimized model, then completed by implementing the test on three most extreme POD models. This paper described the success story and innovation of a complex simulation and finer scale reservoir model using the hybrid parallel-computing technology with a set of 8 nodes high performing computer. Three models were tested with satisfying results. This paper discusses the parallel scalability of complex computing systems of multi-CPU clusters. Multi-CPU distributed memory computing system is proven to be able to improve and accelerate the reservoir modeling and simulation time, when it is used in combination with a new so called “hybrid” approach. In this approach, the common Message Passing Interface (MPI) synchronization between the cluster nodes is being interleaved with a shared memory system thread-based synchronization at the node level. The model with the longest simulation time has been accelerated by magnitude of 60%. The most exhausted model with highest number of simulation steps has been accelerated by magnitude of 80%. The model with the greatest number of grid (21.7 million active grids) has finally finished its simulation just in 27 minutes where previously was impossible to have it open and run. The successful study case is then followed by the implementation of the cluster computing technology for two pilot POD projects which led to the very good result. With this improvement, Pertamina EP can finally perform the probabilistic simulation as recommended by SKKMIGAS in PTK Rev-2/2018. It is now possible to run all 33 structures of multiple reservoir realizations for each POD.

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Preface to Special Issue on Large-scale Numerical Computing Technology for Electromagnetic Field Analysis

IEEJ Transactions on Power and Energy ◽

10.1541/ieejpes.139.636 ◽

2019 ◽

Vol 139 (11) ◽

pp. 636-636

Author(s):

Fumiaki Ikeda ◽

Daigo Yonetsu ◽

Takeshi Mifune ◽

Kengo Sugahara

Keyword(s):

Electromagnetic Field ◽

Large Scale ◽

Field Analysis ◽

Special Issue ◽

Computing Technology ◽

Numerical Computing

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MACHINE LEARNING FOR SOFTWARE

International Conference on Technics Technologies and Education ◽

10.15547/ictte.2019.04.061 ◽

2019 ◽

pp. 251-255

Author(s):

Shafagat Mahmudova

Keyword(s):

Machine Learning ◽

Neural Networks ◽

Soft Computing ◽

Computing Technology

The study machine learning for software based on Soft Computing technology. It analyzes Soft Computing components. Their use in software, their advantages and challenges are studied. Machine learning and its features are highlighted. The functions and features of neural networks are clarified, and recommendations were given.

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DATA INFORMATION SECURITY OF COMMUNICATION NETWORK BASED ON EDGE COMPUTING TECHNOLOGY AND BP NEURAL NETWORK

Telecommunications and Radio Engineering ◽

10.1615/telecomradeng.v78.i20.60 ◽

2019 ◽

Vol 78 (20) ◽

pp. 1837-1845

Author(s):

Xi. Liu

Keyword(s):

Neural Network ◽

Communication Network ◽

Information Security ◽

Bp Neural Network ◽

Edge Computing ◽

Computing Technology

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A Review Paper on Cloud Computing

International Journal of Advanced Research in Computer Science and Software Engineering ◽

10.23956/ijarcsse.v8i6.711 ◽

2018 ◽

Vol 8 (6) ◽

pp. 17 ◽

Cited By ~ 7

Author(s):

Priyanshu Srivastava ◽

Rizwan Khan

Keyword(s):

Cloud Computing ◽

Grid Computing ◽

Review Paper ◽

Computing Technology ◽

Internet Infrastructure ◽

Before And After ◽

The Face

Today is the era of Cloud Computing Technology in IT Industries. Cloud computing which is based on Internet has the most powerful architecture of computation. It reckons in of a compilation of integrated and networked hardware, software and internet infrastructure. It has various avails atop grid computing and other computing. In this paper, I have given a brief of evaluation of cloud computing by reviewing more than 30 articles on cloud computing. The outcome of this review signalizes the face of the IT industries before and after the cloud computing.

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