2012, Vol.17, No.6

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

As the process technology scales down, multi-core processors cause serious problems such as increased interconnection delay, high power consumption and thermal problems. To solve the problems in 2D multi-core processors, researchers have focused on the 3D multi-core processor architecture. Compared to the 2D multi-core processor, the 3D multi-core processor decreases interconnection delay by reducing wire length significantly, since each core on different layers is connected using vertical through-silicon via(TSV). However, the power density in the 3D multi-core processor is increased dramatically compared to that in the 2D multi-core processor, because multiple cores are stacked vertically. Unfortunately, increased power density causes thermal problems, resulting in high cooling cost, negative impact on the reliability. Therefore, temperature should be considered together with performance in designing 3D multi-core processors. In this work, we analyze the temperature of the cache in quad-core processors varying cache organization. Then, we propose the low-temperature cache organization to overcome the thermal problems. Our evaluation shows that peak temperature of the instruction cache is lower than threshold. The peak temperature of the data cache is higher than threshold when the cache is composed of many ways. According to the results, our proposed cache organization not only efficiently reduces the peak temperature but also reduces the performance degradation for 3D quad-core processors.

Integer programming-based local search(IPbLS) is a kind of local search based on simple hill-climbing search and adopts integer programming for neighbor generation unlike general local search. According to an existing research [1], IPbLS is known as an effective method for the multidimensional knapsack problem(MKP) which has received wide attention in operations research and artificial intelligence area. However, the existing research has a shortcoming that it verified the superiority of IPbLS targeting only largest-scale problems among MKP test problems in the OR-Library. In this paper, I verify the superiority of IPbLS more objectively by applying it to other problems. In addition, unlike the existing IPbLS that combines simple hill-climbing search and integer programming, I propose methods combining other local search algorithms like hill-climbing search, tabu search, simulated annealing with integer programming. Through the experimental results, I confirmed that IPbLS shows comparable or better performance than the best known heuristic search also for mid or small-scale MKP test problems.

In this paper, we suggest a new method of detecting human skin-color regions from three-dimensional static or dynamic stereoscopic images by effectively integrating depth and color features. The suggested method first extracts depth information that represents the distance between a camera and an object from input left and right stereoscopic images through a stereo matching technique. It then performs labeling for pixels with similar depth features and determines the labeled regions having human skin color as actual skin color regions. Our experimental results show that the suggested skin region extraction method outperforms existing skin detection methods in terms of skin-color region extraction accuracy.