• International Journal of Advanced Culture Technology
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• v.4 no.4
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• pp.57-63
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• 2016

In this paper, we propose the optimized binarization in the GP-GPU. Because the binarinztion is esily paralledlized, we propose two ways of binary operations that utilize GP-GPU. The first method was to divide data load, subtraction and conversion, data store. The second method was processed collectibely. The second method was 2.52 times faster than the first method. After synthesizing the GP-GPU to the FPGA, the GP-GPU on the binarization were compared with the binarization on the ODROID XU. The binarization on the GP-GPU was 1.89 times faster than the binarization on the ODROID XU.

• Journal of IKEEE
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• v.21 no.1
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• pp.92-95
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• 2017

In this paper, we proposed a way to improve function of small scale GP-GPU. Instead of using superscalar which increase scheduling-complexity, we suggested the application of simple core to maximize GP-GPU performance. Our studies also demonstrated that simplified Stream Processor is one of the way to achieve functional improvement in GP-GPU. In addition, we found that developing of optimal thread-assigning method in Warp Scheduler for specific application improves functional performance of GP-GPU. For examination of GP-GPU functional performance, we suggested the thread-assigning way which coordinated with Deep-Learning system; a part of Neural Network. As a result, we found that functional index in algorithm of Neural Network was increased to 90%, 98% compared with Intel CPU and ARM cortex-A15 4 core respectively.

• Journal of the Korea Society of Computer and Information
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• v.28 no.2
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• pp.1-7
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• 2023

In this paper, we propose a base address candidate selection method using the $gp register and page granularity as a way to build a static analysis environment for firmware based on MIPS architecture. As a way to shorten the base address search time, which is a disadvantage of the base address candidate selection method through inductive reasoning in existing studies, this study proposes a method to perform page-level search based on the $gp register in the existing base address candidate selection method as a reference point for search. Then, based on the proposed method, a base address search tool is implemented and a static analysis environment is constructed to prove the validity of the target tool. The results show that the proposed method is faster than the existing candidate selection method through inductive reasoning.

• Communications for Statistical Applications and Methods
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• v.16 no.3
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• pp.463-477
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• 2009

Parameter estimation methods such as maximum likelihood estimation method, probability weighted moments method, regression method have been popularly applied to various extreme value models in numerous literature. Among three methods above, the performance of regression method has not been rigorously investigated yet. In this paper the regression method is compared with the other methods via Monte Carlo simulation studies for estimation of parameters of the Generalized Extreme Value(GEV) distribution and the Generalized Pareto(GP) distribution. Our simulation results indicate that the regression method tends to outperform other methods under small samples by providing smaller biases and root mean square errors for estimation of location parameter of the GEV model. For the scale parameter estimation of the GP model under small samples, the regression method tends to report smaller biases than the other methods. The regression method tends to be superior to other methods for the shape parameter estimation of the GEV model and GP model when the shape parameter is -0.4 under small and moderately large samples.

• Journal of Pharmaceutical Investigation
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• v.14 no.2
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• pp.86-91
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• 1984

A ginseng preparation (GP) consisting of ginseng ex., lycium fructus ex., four kinds of vitamines and caffein was evaluated for acute toxicity and general pharmacology. Average lethal doses $(LD_{50})$ of GP in male mice were 2,988mg/kg (i.p.) and more than 3g/kg (p.o.). In dosage of 300 and 900mg/kg (p.o.) showed no analgesic activity in both tests of the writhing method induced by acetic acid and of tail pressure method and no effect on the pentetrazole-induced convulsion. However, it appeared to have a hypothermic action only in dose of 900mg/kg. The duration of hypnosis induced by hexobarbital sodium in mice was shortened by GP, being probably due to caffein. GP Produced no marked contraction of isolated ileum and uterus in high concentrations of up to $1{\pm}10^{-3}g/ml$. These results suggested that GP did not show any considerable central nervous depressant activity and exhibited very weak actue toxicity in mice.

• Journal of Information Technology Application
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• v.3 no.3
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• pp.1-24
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• 2001

This paper introduces the genetic programming algorithm(GP), which can approximate highly nonlinear functions, as a tool for the modeling of response surfaces. When the response surfaces is approximated, the very small or minimal teaming set should be used, and thus it is almost certain that GP trees will show overfilling that must be avoided at all costs. We present a novel method, calledDDBS(DirectionalDerivative-Based Smoothering), which very effectively eliminates the unwanted behaviors of GP trees such as large peaks, oscillations, and also overfitting. Four illustrative numerical examples are given to demonstrate the performance of the genetic programming algorithm that adopts DDBS.

• Journal of IKEEE
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• v.14 no.2
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• pp.69-75
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• 2010

A 3D graphics pipeline is largely divided into geometry stage and rendering stage. In this paper, we propose a method that accelerates a geometry processing in multi-core GP-GPU, using dual-phase structure. It can be improved by parallel data processing using SIMD of GP-GPU, dual-phase structure and memory prefetch. The proposed architecture improves approximately 19% of performance when it use all the features.

• Journal of Internet Computing and Services
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• v.15 no.2
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• pp.41-47
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• 2014

In this paper, we implemented a CUDA Fortran parallel program to run the CFD_NIMR model on GP-GPU's, which simulates air diffusion on urban terrains. A GP-GPU is graphic processing unit in the form of a PCI card, and a general calculation accelerator to perform a large amount of high speed calculations with low cost and electric power. The GP-GPU gives performance enhancement of speed by 15 times to compare the Nvidia Tesla C1060 GPU with Intel XEON 2.0 GHz CPU. In addition, the program on a GP-GPU shows efficient performance compared to an MPI parallel program on multiple CPU's. It is expected that a proposed programming method on the GP-GPU parallel program can be used for numerical models with a similar structure.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.12
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• pp.1748-1755
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• 2015

A linear regression is widely used for prediction problem, but it is hard to manage an irregular nature of nonlinear system. Although nonlinear regression methods have been adopted, most of them are only fit to low and limited structure problem with small number of independent variables. However, real-world problem, such as weather prediction required complex nonlinear regression with large number of variables. GP(Genetic Programming) based evolutionary nonlinear regression method is an efficient approach to attach the challenging problem. This paper introduces the improvement of an GP based nonlinear regression method using ADF(Automatically Defined Function). It is believed ADFs allow the evolution of modular solutions and, consequently, improve the performance of the GP technique. The suggested ADF based GP nonlinear regression methods are compared with UM, MLR, and previous GP method for 3 days prediction of wind speed using MOS(Model Output Statistics) for partial South Korean regions. The UM and KLAPS data of 2007-2009, 2011-2013 years are used for experimentation.

• Journal of Integrative Natural Science
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• v.4 no.1
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• pp.23-30
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• 2011

Multidrug resistance (MDR) is one of the main obstacles in the chemotherapy of cancer. MDR is associated with the over expression of P-glycoprotein (P-gp), resulting in increased efflux of chemotherapy from cancer cells. Inhibiting P-gp as a method to reverse MDR in cancer patients has been studied extensively, but the results have generally been disappointing. First-generation agents were limited by unacceptable toxicity, whereas second-generation agents had better tolerability but were confounded by unpredictable pharmacokinetic interactions and interactions with other transporter proteins. Third-generation inhibitors have high potency and specificity for P-gp. Furthermore, pharmacokinetic studies to date have shown no appreciable impact on drug metabolism and no clinically significant drug interactions with common chemotherapy agents. Third-generation P-gp inhibitors have shown promise in clinical trials. The continued development of these agents may establish the true therapeutic potential of P-gp-mediated MDR reversal.