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基于GPGPU光电材料的核多项式算法实现

The realization of kernel polynomial algorithm for optoelectronic materials on GPGPU
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摘要 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。 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.
出处 《激光杂志》 CAS CSCD 北大核心 2012年第4期13-14,共2页 Laser Journal
关键词 GPGPU 并行计算架构 核多项式 GPGPU CUDA kernel polynomial
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参考文献12

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