VolQD: direct volume rendering of multi-million atom quantum dot simulations

IEEE Visualization 2003(2005)

引用 32|浏览9
暂无评分
摘要
In this work we present a hardware-accelerated direct volume rendering system for visualizing multivariate wave functions in semiconducting quantum dot (QD) simulations. The simulation data contains the probability density values of multiple electron orbitals for up to tens of millions of atoms, computed by the NEMO3-D quantum device simulator software run on large-scale cluster architectures. These atoms form two interpenetrating crystalline face centered cubic lattices (FCC), where each FCC cell comprises the eight corners of a cubic cell and six additional face centers. We have developed compact representation techniques for the FCC lattice within PC graphics hardware texture memory, hardware-accelerated linear and cubic reconstruction schemes, and new multi-field rendering techniques utilizing logarithmic scale transfer functions. Our system also enables the user to drill down through the simulation data and execute statistical queries using general-purpose computing on the GPU (GPGPU).
更多
查看译文
关键词
crystal structure,recon- struction filter,statistical queries,face-centered cubic lattice,general-purpose computing,semiconductor quantum dots,wave functions,logarithmic scale transfer function,physics computing,transfer functions,programmable graphics hardware,hardware-accelerated direct volume rendering system,pc graphics hardware texture memory,volume rendering,cubic reconstruction scheme,quantum dots,cluster architecture,pro- grammable graphics hardware,rendering (computer graphics),image reconstruction,face centered cubic lattices,quantum computing,data visualisation,volume visualization,multivariate wave function visualiziation,nemo3-d quantum device simulator software,atomistic simulation,semiconductor quantum dots simulation,image texture,quantum dot,transfer function,face centered cubic,graphics hardware,hardware accelerator,probability density
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要