ID 原文 译文
2713 随着互联网和云计算技术的迅猛发展，现有动态随机存储器(Dynamic Random Access Memory，DRAM)已无法满足一些实时系统对性能、能耗的需求。 With the rapid development of internet and cloud computing technology, the existing dynamic random accessmemory (DRAM)have been unable to meet the requirements of performance and energy consumption of some real time sys-tems.
2714 新型非易失存储器(Non-Volatile Memory，NVM)的出现为计算机存储体系的发展带来了新的契机。 The emergence of non-volatile memory (NVM)have shown great potential for the development of the computer storage architecture.
2715 本文针对 NVM 和 DRAM 混合内存系统架构，提出一种高效的混合内存页面管理机制。 This paper proposes a kind of efficient memory page management mechanism based on the hybrid NVM andDRAM memory architecture.
2716 该机制针对内存介质写特性的不同，将具有不同访问特征的数据页保存在合适的内存空间中，以减少系统的迁移操作次数，从而提升系统性能。 The main idea of this mechanism is to save the data pages with different access characteristics in the appropriate memory space according to the characteristics of different memory media, to reduce the number of system mi-gration operations and improve the system performance.
2717 同时该机制使用一种两路链表使得 NVM 介质的写操作分布更加均匀，以提升使用寿命。 At the same time, the mechanism uses an efficient wear-leveling algo-rithm to improve NVM＇s lifetime.
2718 最后，本文在Linux 内核中对所提机制进行仿真实验。并与现有内存管理机制进行对比，实验结果证明了所提方法的有效性。 Finally, the experimental results show that the proposed method is effective.
2719 区域分解方法是近来发展迅速的有限元求解方法之一。 DDM (Domain Decomposition Method)is one of the most quickly developed methods in recent years.
2720 基于有限元区域分解方法以及多重网格的思想，我们研究了自适应求解以及离散扫频快速算法，并采用自主研发的高性能计算并行框架，将基于区域分解的大规模并行有限元快速算法进行了实现，并行规模能够扩展到数万 CPU 核。 We investigate the fast solving techniques of adaptive refinement and discrete frequency sweep based on DDM. Besides, an in-house developed infrastructure is used to implement the proposed algorithms, which is able to scale to tens of thousands of CPU cores.
2721 我们在文中将展示程序的核心架构，以及如何采用多重网格算法的思想实现有效的粗网格校正技术，从而实现有限元线性系统的多次快速求解，加速自适应求解和离散扫频。 We demonstrate the architecture and main features of the program. Then, the DDM, p-adaptive strategy and fast frequency sweep techniques are discussed as well to show how to solve the finite element linear systems quickly.
2722 最后，对算法进行了准确性验证以及大规模并行测试。 Several nu-merical examples are presented to demonstrate its accuracy, parallel efficiency and capability in electromagnetic applications.