Performance Evaluation of a Multi-Zone Application in Different OpenMP Approaches

We describe a performance study of a multi-zone application benchmark implemented in several OpenMP approaches that exploit multi-level parallelism and deal with unbalanced workload. The multi-zone application was derived from the well-known NAS Parallel Benchmarks (NPB) suite that involves flow solvers on collections of loosely coupled discretization meshes. Parallel versions of this application have been developed using the Subteam concept and Workqueuing model as extensions to the current OpenMP. We examine the performance impact of these extensions to OpenMP and compare with hybrid and nested OpenMP approaches on several large parallel systems.     

量子Haar小波变换算法设计及应用

设计了基于通用量子语言Q_language的量子Haar小波变换算法,该算法对于小波变换的应用和量子算法的完善具有重要的意义.分析了3个量子位Haar小波变换过程,给出了量子Haar小波变换算法的Q_language语言描述,并分析得出其时间和空间复杂度,然后给出了实现量子Haar小渡变换应用方法.     

基于并列选择遗传算法的多机器人协作探测

多机器人系统在执行探测任务时,存在多个机器人同时选择相同探测区域而造成碰撞几率增加和探测效率降低的问题.在原有并列选择遗传算法的基础上,提出了一种改进的遗传算法.仿真和实验结果表明,将该算法应用于多机器人协作区域探测,可以减小机器人之间的碰撞几率,提高多机器人系统的探测效率.     

一种量子神经网络模型学习算法及应用

提出一种量子神经网络模型及学习算法. 首先基于生物神经元信息处理机制和量子计算原理构造出一种量子神经元, 该神经元由加权、聚合、活化、激励四部分组成. 然后由量子神经元构造出三层量子神经网络模型, 其输入和输出为实值向量, 权值和活性值为量子比特. 基于梯度下降法构造了该模型的超线性收敛学习算法. 通过模式识别和函数逼近两种仿真结果表明该模型及算法是有效的.     

正己烷裂解反应自由基模型的理论研究

采用量子化学法研究了模型化合物正己烷裂解过程,并计算其动力学参数。依据自由基理论,建立由216个基元反应组成的正己烷裂解反应自由基模型,用CBS-QB3法计算链引发和终止反应动力学参数,用MPW1B95/6-311+G(2d,2p)法计算链增长反应动力学参数。根据动力学参数计算结果,忽略相对不重要的反应,将模型简化为160个基元反应。模拟计算表明,在相同的裂解条件下,简化模型模拟结果与完整模型模拟结果一致,各组分相差不大于0.1%wt;建立的动力学模型对主要产物收率预测较好,与实验值相差小于0.7%wt,可正确地预测正己烷裂解产物的组成和各组分含量沿反应管长度的分布,为进一步研究复杂的烃裂解过程提供了基础。     

An approach to the parallel solution of a high-dimensional basic flow problem

The body of mathematics of modified systems of algorithmic algebras (SAA-M) is used to formalize the Edmonds–Karp algorithm of finding the maximum flow in a network. With allowance made for the distributed system features that are usually used for solving complicated problems, optimization criteria are formulated and used to obtain parallel SAA-M-schemes. Translated from Kibernetika i Sistemnyi Analiz, No. 2, pp. 146–152, March–April 2009.     

On the Black-Box Complexity of Sperner’s Lemma

We present several results on the complexity of various forms of Sperner’s Lemma in the black-box model of computing. We give a deterministic algorithm for Sperner problems over pseudo-manifolds of arbitrary dimension. The query complexity of our algorithm is linear in the separation number of the skeleton graph of the manifold and the size of its boundary. As a corollary we get an deterministic query algorithm for the black-box version of the problem 2D-SPERNER, a well studied member of Papadimitriou’s complexity class PPAD. This upper bound matches the deterministic lower bound of Crescenzi and Silvestri. The tightness of this bound was not known before. In another result we prove for the same problem an lower bound for its probabilistic, and an lower bound for its quantum query complexity, showing that all these measures are polynomially related. Research supported by the European Commission IST Integrated Project Qubit Application (QAP) 015848, the OTKA grants T42559 and T46234, and by the ANR Blanc AlgoQP grant of the French Research Ministry.     

Observer-invariant histopathology using genetics-based machine learning

Prostate cancer accounts for one-third of noncutaneous cancers diagnosed in US men and is a leading cause of cancer-related death. Advances in Fourier transform infrared spectroscopic imaging now provide very large data sets describing both the structural and local chemical properties of cells within prostate tissue. Uniting spectroscopic imaging data and computer-aided diagnoses (CADx), our long term goal is to provide a new approach to pathology by automating the recognition of cancer in complex tissue. The first step toward the creation of such CADx tools requires mechanisms for automatically learning to classify tissue types—a key step on the diagnosis process. Here we demonstrate that genetics-based machine learning (GBML) can be used to approach such a problem. However, to efficiently analyze this problem there is a need to develop efficient and scalable GBML implementations that are able to process very large data sets. In this paper, we propose and validate an efficient GBML technique——based on an incremental genetics-based rule learner. exploits massive parallelisms via the message passing interface (MPI) and efficient rule-matching using hardware-implemented operations. Results demonstrate that is capable of performing prostate tissue classification efficiently, making a compelling case for using GBML implementations as efficient and powerful tools for biomedical image processing.     

抗量子计算公钥密码需求分析与技术路线

本文对国外量子计算机研究进展情况进行了分析,并针对量子计算机对于信息安全的挑战,讨论了国内下一代公钥密码技术的需求、发展思路和技术路线。     

小像元量子阱FPA抗光学串音的FDTD仿真

采用光栅耦合结构的焦平面阵列(Focal Plane Array,FPA)在工艺上难以制备,反射耦合结构较为容易。为探究反射耦合结构是否可以在小尺寸范围内替代光栅耦合结构,文章使用FDTD电磁场仿真软件MEEP构建了光栅耦合结构和反射结构GaAs/AlGaAs量子阱红外焦平面阵列三像元模。通过对器件内部光学串音进行仿真,验证了在逼近衍射极限时,采用全内反射结构的FPA在5~7μm和8.5~10μm之间的抗串音效果强于光栅耦合结构,而在6.5~8.5μm和10~12μm之间,光栅耦合结构的抗串音效果更好,在12~15μm范围内,两种结构的抗串音能力相当。针对15μm中心距全内反射结构量子阱FPA,探究了反射角度、刻蚀深度和量子阱周期对其串音的影响。