基于OpenCL并行流动影响三维共晶生长多相场模拟

基于KKSO三维多元合金共晶多相场模型,研究了OpenCL+GPU软硬件体系结构的高性能计算方法,以CBr_4-C_2Cl_6为例,分别在AMD和NVIDIA 2种异构平台上通过多进程和多线程的并发执行实现了强迫对流下三维共晶组织的演化过程.结果表明:当计算规模相同时,分别在不同的平台上取得了一定的加速比.对并行算法在一定程度上进行优化,与CPU平台上的串行算法相比优化后的并行算法在异构平台上分别达到了20.2倍和23.6倍的加速比,大大提高了计算效率.同时,以其强大的浮点计算能力获取较为准确的模拟结果,达到计算效率和可移植性的双重需求,解决了传统求解相场模型存在的计算量大、效率低、限于定性研究等问题.     

Multi-GPU加速的二元合金定向凝固三维相场模型

基于三维相场模型,使用MPI+CUDA异构协同并行技术,在GPU集群上建立三维合金定向凝固的MultiGPU计算模型,实现了Al-Cu二元合金三维定向凝固的模拟.再现了Al-Cu二元合金三维定向凝固的过程,以及不同取向晶粒间的竞争生长现象.通过与传统CPU串行计算模型相比较,验证了Multi-GPU计算模型的计算效率和加速效果.实现了二元合金定向凝固的加速模拟计算,其加速比最大可达57.7.     

基于OpenCL的图像灰度化并行算法研究

随着图像数据量的增加,传统单核处理器或多处理器结构的计算方式已无法满足图像灰度化实时处理需求.该文利用图像处理器(GPU)在异构并行计算的优势,提出了基于开放式计算语言(OpenCL)的图像灰度化并行算法.通过分析加权平均图像灰度化数据处理的并行性,对任务进行了层次化分解,设计了2级并行的并行算法并映射到“CPU+GPU”异构计算平台上.实验结果显示:图像灰度化并行算法在OpenCL架构下NVIDIA GPU计算平台上相比串行算法、多核CPU并行算法和CUDA并行算法的性能分别获得了27.04倍、4.96倍和1.21倍的加速比.该文提出的并行优化方法的有效性和性能可移植性得到了验证.     

压缩感知A*OMP重构算法的并行化与GPU加速实现

针对压缩感知系统实时应用的需要,探讨了A*OMP算法的并行设计及基于GPU的加速方法.将耗时长的矩阵逆运算转化为可并行的矩阵/向量操作,并结合算法本身的关联特性,进一步采用迭代法实现以降低其计算复杂度.利用GPU高效的并行运算能力,将算法中可并行的矩阵/向量计算映射到GPU上并行执行,在面向Matlab的Jacket软件平台上对整体串行算法进行了并行化的设计与实现.在NVIDIA Tesla K20Xm GPU和Intel(R)E5-2650 CPU上进行了测试,实验结果表明:对比CPU平台的串行实现,基于GPU的A*OMP算法整体上可获得约40倍的加速,实现了在保持系统较高重构质量的同时能有效降低计算时间,较好地满足了系统实时性的需要.     

Co-OLAP:CPU&GPU混合平台上面向星形模型基准的协同OLAP

当前GPU(图形处理器),即使是中端服务器配置的中端GPU也拥有强大的并行计算能力.不同于近期的研究成果,中端服务器可能配置有几块高端CPU和一块中端GPU,GPU能够提供额外的计算能力而不是提供比CPU更加强大的计算能力.本文以中端工作站上的Co-OLAP(协同OLAP)为中心,描述如何使中端GPU与强大的CPU协同以及如何在计算均衡的异构平台上分布数据和计算以使Co-OLAP模型简单而高效.根据实际的配置,基于内存容量,GPU显存容量,数据集模式和订制的AIR(数组地址引用)算法提出了最大高性能数据分布模型.Co-OLAP模型将数据划分为驻留于内存和GPU显存的数据集,OLAP计算也划分为CPU和GPU端的自适应计算负载来最小化CPU和GPU内存之间的数据传输代价.实验结果显示,在SF=20的SSB(星形模型基准)测试中,两块至强六核处理器的性能略优于一块NVIDA Quadra 5 000GPU(352个cuda核心)的处理性能,Co-OLAP模型可以将负载均衡分布在异构计算平台并使每个平台简单而高效.     

Co-OLAP:CPU&GPU混合平台上面向星形模型基准的协同OLAP（英文）

当前GPU(图形处理器),即使是中端服务器配置的中端GPU也拥有强大的并行计算能力.不同于近期的研究成果,中端服务器可能配置有几块高端CPU和一块中端GPU,GPU能够提供额外的计算能力而不是提供比CPU更加强大的计算能力.本文以中端工作站上的CoOLAP(协同OLAP)为中心,描述如何使中端GPU与强大的CPU协同以及如何在计算均衡的异构平台上分布数据和计算以使Co-OLAP模型简单而高效.根据实际的配置,基于内存容量,GPU显存容量,数据集模式和订制的AIR(数组地址引用)算法提出了最大高性能数据分布模型.CoOLAP模型将数据划分为驻留于内存和GPU显存的数据集,OLAP计算也划分为CPU和GPU端的自适应计算负载来最小化CPU和GPU内存之间的数据传输代价.实验结果显示,在SF=20的SSB(星形模型基准)测试中,两块至强六核处理器的性能略优于一块NVIDA Quadra 5 000GPU(352个cuda核心)的处理性能,Co-OLAP模型可以将负载均衡分布在异构计算平台并使每个平台简单而高效.     

面向CPU+GPU异构计算的SIFT

依据图形处理器(GPU)计算特点和任务划分的特点,提出主从模型的CPU+GPU异构计算的处理模式.通过分析和定义问题中的并行化数据结构,描述计算任务到统一计算设备架构(CUDA)的映射机制,把问题或算法划分成多个子任务,并对划分的子任务给出合理的调度算法.结果表明,在GeForce GTX 285上实现的尺度不变特征变换(SIFT)并行算法相比CPU上的串行算法速度提升了近30倍.     

CPU+GPU异构并行的矩阵转置算法研究

针对当前算法优化研究一般局限于单一硬件平台、很难实现在不同平台上高效运行的问题,利用图形处理器(GPU)提出了基于开放式计算语言(OpenCL)的矩阵转置并行算法.通过矩阵子块粗粒度并行、矩阵元素细粒度并行、工作项与数据的空间映射和本地存储器优化方法的应用,使矩阵转置算法在GPU计算平台上的性能提高了12倍.实验结果表明,与基于CPU的串行算法、基于开放多处理(OpenMP)并行算法和基于统一计算设备架构(CUDA)并行算法性能相比,矩阵转置并行算法在OpenCL架构下NVIDIA GPU计算平台上分别获得了12.26,2.23和1.50的加速比.该算法不仅性能高,而且实现了在不同计算平台间的性能移植.     

基于GPU的对称正定稀疏矩阵复线性方程组迭代算法

提出一种基于图形处理器（GPU）的对称正定稀疏矩阵复线性方程组迭代算法. 首先, 采用基于GPU的共轭梯度法和双共轭梯度法, 实现GPU上的矩阵向量乘操作, 并充分优化相应的算法步骤; 其次, 实现基于GPU的对角元预处理、 不完全Cholesky分解和对称超松弛3种预处理方法, 提出一种基于GPU的求解三角方程组并行算法; 最后, 实验分析各种预处理方法的优劣. 实验结果表明, 该算法较CPU串行迭代算法与经典的直接法速度提升较大, 最高可达到76倍的加速比.     

基于GPU的PCA人脸识别系统设计

针对实际人脸识别系统需要满足实时性的应用需要,探讨了在图形处理器(GPU)硬件架构基础上的基于主成分分析(PCA)人脸识别系统设计与实现.结合统一计算设备架构(CUDA)的计算平台,通过将算法中耗时长、适合并行的部分过程映射到GPU上并行执行改进系统的加速实现.实验结果表明:相对于基于CPU平台的串行实现,基于GPU的实现在整体上能够获得约5倍的加速,而两个执行并行的模块能分别获得最大20倍和30倍的加速.     

Markedness and its Interpretation in Language Use

Language markedness is a common phenomenon in languages, and is reflected from hearing, vision and sense, i.e. the variation in the three aspects such as phonology, morphology and semantics. This paper focuses on the interpretation of markedness in language use following the three perspectives, i.e. pragmatic interpretation, psychological interpretation and cognitive interpretation, with an aim to define the function of markedness.     

Characterization of Ordovician carbonate reservoirs, southeastern Saskatchewan, Canada

The discovery of the prolific Ordovician Red River reservoirs in 1995 in southeastern Saskatchewan was the catalyst for extensive exploration activity which resulted in the discovery of more than 15 new Red River pools. The best yields of Red River production to date have been from dolomite reservoirs. Understanding the processes of dolomitization is, therefore, crucial for the prediction of the connectivity, spatial distribution and heterogeneity of dolomite reservoirs.The Red River reservoirs in the Midale area consist of 3～4 thin dolomitized zones, with a total thickness of about 20 m, which occur at the top of the Yeoman Formation. Two types of replacement dolomite were recognized in the Red River reservoir: dolomitized burrow infills and dolomitized host matrix. The spatial distribution of dolomite suggests that burrowing organisms played an important role in facilitating the fluid flow in the backfilled sediments. This resulted in penecontemporaneous dolomitization of burrow infills by normal seawater. The dolomite in the host matrix is interpreted as having occurred at shallow burial by evaporitic seawater during precipitation of Lake Almar anhydrite that immediately overlies the Yeoman Formation. However, the low δ18O values of dolomited burrow infills (-5.9‰～ -7.8‰, PDB) and matrix dolomites (-6.6‰～ -8.1‰, avg. -7.4‰ PDB) compared to the estimated values for the late Ordovician marine dolomite could be attributed to modification and alteration of dolomite at higher temperatures during deeper burial, which could also be responsible for its 87Sr/86Sr ratios (0.7084～0.7088) that are higher than suggested for the late Ordovician seawaters (0.7078～0.7080). The trace amounts of saddle dolomite cement in the Red River carbonates are probably related to "cannibalization" of earlier replacement dolomite during the chemical compaction.     

低渗透非均质砂岩油藏启动压力梯度研究

理论推导与室内实验相结合,建立了低渗透非均质砂岩油藏启动压力梯度确定方法。首先借助油藏流场与电场相似的原理,推导了非均质砂岩油藏启动压力梯度计算公式。其次基于稳定流实验方法,建立了非均质砂岩油藏启动压力梯度测试方法。结果表明:低渗透非均质砂岩油藏的启动压力梯度确定遵循两个等效原则。平面非均质油藏的启动压力梯度等于各级渗透率段的启动压力梯度关于长度的加权平均;纵向非均质油藏的启动压力梯度等于各渗透率层的启动压力梯度关于渗透率与渗流面积乘积的加权平均。研究成果可用于有效指导低渗透非均质砂岩油藏的合理井距确定,促进该类油藏的高效开发。     

On Tragic Consciousness In The Works By Ernest Hemingway

As an American modern novelist who were famous in the literary world, Hemingway was not a person who always followed the trend but a sharp observer. At the same time, he was a tragedy maestro, he paid great attention on existence, fate and end-result. The dramatis personae's tragedy of his works was an extreme limit by all means tragedy on the meaning of fearless challenge that failed. The beauty of tragedy was not produced on the destruction of life, but now this kind of value was in the impact activity. They performed for the reader about the tragedy on challenging for the limit and the death.     

A computer generator for randomly layered structures

AcomputergeneratorforrandomlylayeredstructuresYUJia shun1,2,HEZhen hua2(1.TheInstituteofGeologicalandNuclearSciences,NewZealand;2.StateKeyLaboratoryofOilandGasReservoirGeologyandExploitation,ChengduUniversityofTechnology,China)Abstract:Analgorithmisintrod…     

An Index mechanism for multi-scale view in spatial databases

There are numerous geometric objects stored in the spatial databases. An importance function in a spatial database is that users can browse the geometric objects as a map efficiently. Thus the spatial database should display the geometric objects users concern about swiftly onto the display window. This process includes two operations:retrieve data from database and then draw them onto screen. Accordingly, to improve the efficiency, we should try to reduce time of both retrieving object and displaying them. The former can be achieved with the aid of spatial index such as R-tree, the latter require to simplify the objects. Simplification means that objects are shown with sufficient but not with unnecessary detail which depend on the scale of browse. So the major problem is how to retrieve data at different detail level efficiently. This paper introduces the implementation of a multi-scale index in the spatial database SISP (Spatial Information Shared Platform) which is generalized from R-tree. The difference between the generalization and the R-tree lies on two facets: One is that every node and geometric object in the generalization is assigned with a importance value which denote the importance of them, and every vertex in the objects are assigned with a importance value,too. The importance value can be use to decide which data should be retrieve from disk in a query. The other difference is that geometric objects in the generalization are divided into one or more sub-blocks, and vertexes are total ordered by their importance value. With the help of the generalized R-tree, one can easily retrieve data at different detail levels.Some experiments are performed on real-life data to evaluate the performance of solutions that separately use normal spatial index and multi-scale spatial index. The results show that the solution using multi-scale index in SISP is satisfying.     

Achieving Unusual States of Matter Under High Pressure

正The periodicity of the elements and the non-reactivity of the inner-shell electrons are two related principles of chemistry,rooted in the atomic shell structure.Within compounds,Group I elements,for example,invariably assume the+1 oxidation state,and their chemical properties differ completely from those of the p-block elements.These general rules govern our understanding of chemical structures and reactions.Using first principles calcula-     

Exchange-Correlation and Electronic Excitation Energies from Pairing Matrix Fluctuations

We have developed an adiabatic connection to formulate the ground-state exchange-correlation energy in terms of pairing matrix linear fluctuations.This formulation of the exchange-correlation energy opens a new channel for density functional approximations based on the many-body perturbation theory.We illustrate the potential of such approaches with an approximation based on the particle-particle Random Phase Approximation(pp-RPA).This re-     

Density Functional Theory for the Response of Periodic Systems to Electric Fields Based on the Vector Potential Approach

正The electronic and nuclear(structural/vibrational)response of 1D-3D nanoscale systems to electric fields gives rise to a host of optical,mechanical,spectral,etc.properties that are of high theoretical and applied interest.Due to the computational difficulty of treating such large systems it is convenient to model them as infinite and periodic(at least,in first approximation).The fundamental theoretical/computational problem in doing so is that     

On the Thermodynamic Limit for Responses to Static Electromagnetic Fields

For molecular systems,the quantum-mechanical treatment of their responses to static electromagnetic fields usually employs a scalar-potential treatment of the electric field and a vector-potential treatment of the magnetic field.Although the potential for each field separately is associated with the choice of an(unphysical)origin,the precise choice of the origin for the electrostatic field has little consequences for the results.This is different for the