• The Journal of the Convergence on Culture Technology
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• v.3 no.4
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• pp.171-175
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• 2017

Recently, Training of the convolutional neural network (CNN) entails many iterative computations. Therefore, a method of accelerating the training speed through parallel processing using the hardware specifications of GPGPU is actively researched. In this paper, the operations of the feature extraction unit and the classification unit are divided into blocks and threads of GPGPU and processed in parallel. Convolution and Pooling operations of the feature extraction unit are processed in parallel at once without sequentially processing. As a result, proposed method improved the training time about 314%.

• The Journal of Society for e-Business Studies
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• v.13 no.4
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• pp.161-171
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• 2008

The most important reason for increasing web traffic and overloaded web servers is a dramatic growth of web users which leads to a great dissatisfaction of each individual user. For overcoming this situation, studies for an acceleration of web content have been conducted actively. We use web caching technology for reducing the load of the web system and traffic in the network. In this paper, we proposed a new web caching technology with the related web object which based on the unit of web processing and characteristics of the web object. Also we verified the availability of the proposed system with comparison and experiments.,

• Journal of the Korean Society of Radiology
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• v.17 no.5
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• pp.633-640
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• 2023

With the recent development of static and dynamic modulated brachytherapy methods in brachytherapy, which use radiation shielding to modulate the dose distribution to deliver the dose, the amount of parameters and data required for dose calculation in inverse treatment planning and treatment plan optimization algorithms suitable for new directional beam intensity modulated brachytherapy is increasing. Although intensity-modulated brachytherapy enables accurate dose delivery of radiation, the increased amount of parameters and data increases the elapsed time required for dose calculation. In this study, a GPU-based CUDA-accelerated dose calculation algorithm was constructed to reduce the increase in dose calculation elapsed time. The acceleration of the calculation process was achieved by parallelizing the calculation of the system matrix of the volume of interest and the dose calculation. The developed algorithms were all performed in the same computing environment with an Intel (3.7 GHz, 6-core) CPU and a single NVIDIA GTX 1080ti graphics card, and the dose calculation time was evaluated by measuring only the dose calculation time, excluding the additional time required for loading data from disk and preprocessing operations. The results showed that the accelerated algorithm reduced the dose calculation time by about 30 times compared to the CPU-only calculation. The accelerated dose calculation algorithm can be expected to speed up treatment planning when new treatment plans need to be created to account for daily variations in applicator movement, such as in adaptive radiotherapy, or when dose calculation needs to account for changing parameters, such as in dynamically modulated brachytherapy.

• KAPE Magazine
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• s.147
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• pp.2-3
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• 2008

• Journal of Korean Electronics
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• v.30 no.2
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• pp.4-4
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• 2010

• The Korea Swine Journal
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• v.8 no.3 s.79
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• pp.146-149
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• 1986

• Journal of Korean Electronics
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• v.3 no.2
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• pp.111-113
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• 1983

• KOREAN POULTRY JOURNAL
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• v.40 no.4 s.462
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• pp.175-175
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• 2008

• Journal of Korea Fair Competition Federation
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• no.153
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• pp.6-17
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• 2010

• 프린팅코리아
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• v.12 no.7
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• pp.126-127
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• 2013

워크플로의 잠재력을 찾아내고자 하는 노력이 가속화되고 있다. 이제 워크플로는 생산공정을 시뮬레이션하는 것에 그치지 않고 다양한 경영정보를 링크해 경영의 수준을 높이는 것이 가능한 수준에 이르렀다.