Parallel Seismic Modeling Based on OpenMP+AVX and Optimization Strategy

This paper describes parallel simulation of the memory/computation-intensive acoustic wave equation with CPU template buffer optimization. Considering the 8-core CPU shared storage platform as an example,we obtain a one-time speed-up ratio of 6.7× compared with the serial program by using a coarse-grained OpenMP parallel scheme. Then,data is vectorized on the template buffer using the single instruction-multiple data(SIMD) technique to further exploit the computing potential of the CPUs. We apply an 8-channel parallel vector to simulate seismic wavefields with the 256-bit advanced vector extensions(AVX) instruction set. This increases the computing bandwidth,thus eliminating a significant volume of the computing instructions and obtaining a secondary speed-up ratio of 3–7×. In addition,we use 32-byte data alignment,shortest data direction vectorization,and loop tiling optimization algorithm to achieve faster program execution. Finally,we analyze the factors affecting the secondary speed-up of AVX through three-dimensional modeling experiments with the salt model.The results indicate that the memory,cache,and register can better cooperate with each other and the speed-up is increased by optimizing the AVX algorithm.

锡基钙钛矿太阳电池光吸收材料

钙钛矿太阳电池以其优异的光吸收特性、载流子传输能力以及简单的制备工艺,成为太阳电池领域研究的热点。高效、无污染、低成本一直是太阳电池领域追求的目标。然而,传统钙钛矿太阳电池由于其光吸收材料中含重金属元素铅,对环境有较大影响,从而限制了此类钙钛矿太阳电池的进一步商业化应用。基于此,科学家们都在致力于寻找新的无铅钙钛矿材料。在众多无铅钙钛矿材料中,锡基钙钛矿材料由于其相对较小的毒性、合适的带隙以及相应器件具有较高的能量转换效率等优点,成为最有希望应用于钙钛矿太阳电池的替代材料。然而,锡基钙钛矿太阳电池也存在一些弱点,其能量转换效率和器件稳定性相较于铅基钙钛矿太阳电池仍然存在很大差距,器件制备过程中对空气十分敏感。为了更好地解决这些问题,对锡基钙钛矿材料及器件性能的各种影响因素进行系统地研究势在必行。文章分类介绍了各类锡基钙钛矿材料及其在太阳电池中的应用,包括有机-无机杂化锡基钙钛矿材料,锡铅混合钙钛矿材料和全无机锡基钙钛矿材料,综述了锡基钙钛矿材料及其相应器件性能的最新研究进展,并且讨论了影响器件性能的各项因素,最后对锡基钙钛矿太阳电池未来的发展做出了展望。