CAJ | 학술논문

在物理学中，对光电材料的量子系统晶格模型进行模拟是了解光电材料的量子特性最重要的方法之一。而模拟中的主要任务是计算电子态密度。这需要大规模的计算，因此它通常是在计算机集群、甚至是超级计算机下进行的。而随着GPGPU的发展，利用GPGPU强大的数据处理能力，采用合适的算法能极大地减少计算量。结果显示，与相同算法的CPU实现相比，GPGPU实现计算效率极大地提高了。
재물이학중，대광전재료적양자계통정격모형진행모의시료해광전재료적양자특성최중요적방법지일。이모의중적주요임무시계산전자태밀도。저수요대규모적계산，인차타통상시재계산궤집군、심지시초급계산궤하진행적。이수착GPGPU적발전，이용GPGPU강대적수거처리능력，채용합괄적산법능겁대지감소계산량。결과현시，여상동산법적CPU실현상비，GPGPU실현계산효솔겁대지제고료。
In the field of Physics, it is a significant method that to simulate the lattice model system for optoeleetronic materials. Evaluating the electronic density of energy states is the first and crucial work. However, it requires a great number of computations, thus it is typically performed on cluster computers, even supercomputers. With the development of GPGPU, we can employ some appropriate algorithms and it can reduce computations greatly via using the powerful data preeessing capabilities of GPGPU. Compared with CPU - based implementation, this results present that the speed of the same algorithm implemented on GPGPU could be improved greatly.