2011, Vol.16, No.2

Journal of The Korea Society of Computer and Information 2023 KCI Impact Factor : 0.65

pISSN : 1598-849X / eISSN : 2383-9945
https://journal.kci.go.kr/jksci

NAND type Flash memory has performing much researches for a hard disk substitution due to its low power consumption, cheap prices and a large storage. Especially, the NAND type flash memory is using general buffer systems of a cache memory for improving overall system performance, but this has shown a tendency to emphasize in terms of data. So, our research is to design a high performance instruction NAND type flash memory structure by using a buffer system. The proposed buffer system in a NAND flash memory consists of two parts, i.e., a fully associative temporal buffer for branch instruction and a fully associative spatial buffer for spatial locality. The spatial buffer with a large fetching size turns out to be effective serial instructions, and the temporal buffer with a small fetching size can achieve effective branch instructions. According to the simulation results, we can reduce average miss ratios by around 77% and the average memory access time can achieve a similar performance compared with the 2-way , victim and fully associative buffer with two or four sizes.

GPU computing is emerging in high performance application area since it can easily exploit massive parallelism in a way of cost-effective computing. The power method which finds the eigen vector of a given matrix is widely used in various applications such as PageRank for calculating importance of web pages. In this research we made the power method efficiently parallelized on GPU and also suggested how it can be improved to enhance its performance. The power method mainly consists of matrix-vector product and it can be easily parallelized. However, it should decide the convergence of the eigen vector and need scaling of the vector subsequently. Such operations incur several calls to GPU kernels and data movement between host and GPU memories. We improved the performance of the power method by means of reduced calls to GPU kernels, optimized thread allocation and enhanced decision operation for the convergence.

In this paper, daily life stress monitoring system is proposed. The proposed wireless ECG module, reducing the noise and increasing the size of signal, amplification circuit was designed for. Using HRV(Heart Rate Variability), extracted by measuring R-wave, stress diagnostic algorithms to assess the stress of human emotion were developed. For monitoring the activities, the proposed system is consist of small rectangular size for portable and by simple measurement it is possible to measure at any time. Through experiments, the proposed approach to represent user's stress level can be confirmed. Through that, it can see appropriate structure to obtain R-wave for stress assess as well as high resemblance to the clinical electrocardiogram. In this paper, performed experiments was developed nonrestraint measuring and wearable wireless biometric scanner that is able to monitor the heart's electrical activity of everyday life.Using this, the algorithm system, that is able to assess stress index through time-domain and frequency-domain analysis of the front and the rear of performing stress load protocol, was developed,