Multi-GPU accelerated multi-spin Monte Carlo simulations of the 2D Ising model

A Modern Graphics Processing unit (GPU) is able to perform massively parallel scientific computations at low cost. We extend our implementation of the checkerboard algorithm for the two-dimensional Ising model [T. Preis et al., Journal of Chemical Physics 228 (2009) 4468-4477] in order to overcome the memory limitations of a single GPU which enables us to simulate significantly larger systems. Using multi-spin coding techniques, we are able to accelerate simulations on a single GPU by factors up to 35 compared to an optimized single Central Processor Unit (CPU) core implementation which employs multi-spin coding. By combining the Compute Unified Device Architecture (CUDA) with the Message Parsing Interface (MPI) on the CPU level, a single Ising lattice can be updated by a cluster of GPUs in parallel. For large systems, the computation time scales nearly linearly with the number of GPUs used. As proof of concept we reproduce the critical temperature of the 2D Ising model using finite size scaling techniques.     

Missile target automatic recognition from its decoys based on image time-series

As the development of the technology for radar target recognition, missile target automatic recognition has received considerable attention in recent years. Missile target, compared with the plane target, is hard to recognize for its smallness, feebleness and maneuver. In this paper, a new recognition method based on radar image time-series, which can significantly reduce the recognition time and classification error, is proposed. The image time-series are produced by range instantaneous Doppler imaging algorithm firstly, and then cross-range scaling of the images is processed. In particular, the inertia ratio, extracted from the obtained image time-series, is introduced to distinguish the missile from decoys. Furthermore, the effectiveness of this method is demonstrated by application to simulated data and it has been shown that this method has the potential to be used in a number of real-time applications.     

Remote sensing of photosynthetic light-use efficiency across two forested biomes: Spatial scaling

Eddy covariance (EC) measurements have greatly advanced our knowledge of carbon exchange in terrestrial ecosystems. However, appropriate techniques are required to upscale these spatially discrete findings globally. Satellite remote sensing provides unique opportunities in this respect, but remote sensing of the photosynthetic light-use efficiency (ε), one of the key components of Gross Primary Production, is challenging. Some progress has been made in recent years using the photochemical reflectance index, a narrow waveband index centered at 531 and 570 nm. The high sensitivity of this index to various extraneous effects such as canopy structure, and the view observer geometry has so far prevented its use at landscape and global scales. One critical aspect of upscaling PRI is the development of generic algorithms to account for structural differences in vegetation. Building on previous work, this study compares the differences in the PRI: ? relationship between a coastal Douglas-fir forest located on Vancouver Island, British Columbia, and a mature Aspen stand located in central Saskatchewan, Canada. Using continuous, tower-based observations acquired from an automated multi-angular spectro-radiometer (AMSPEC II) installed at each site, we demonstrate that PRI can be used to measure ? throughout the vegetation season at the DF-49 stand (r² = 0.91, p < 0.00) as well as the deciduous site (r² = 0.88, p < 0.00). It is further shown that this PRI signal can be also observed from space at both sites using daily observations from the Moderate Resolution Imaging Spectro-radiometer (MODIS) and a multi-angular implementation of atmospheric correction (MAIAC) (r² = 0.54 DF-49; r² = 0.63 SOA; p < 0.00). By implementing a simple hillshade model derived from airborne light detection and ranging (LiDAR) to approximate canopy shadow fractions (α_s), it is further demonstrated that the differences observed in the relationship between PRI and ε at DF-49 and SOA can be attributed largely to differences in α_s. The findings of this study suggest that algorithms used to separate physiological from extraneous effects in PRI reflectance may be more broadly applicable and portable across these two climatically and structurally different biome types, when the differences in canopy structure are known.     

基于混沌扩频和能量系数差的音频盲水印算法

提出一种基于混沌扩频和能量系数差的小波域数字音频盲水印算法。采用混沌扩频序列对原始水印进行加密,小波算法对原始音频信号进行分解,引入心理声学模型选取适当的阈值,根据高频系数分量和低频系数分量的能量差值与阈值的大小关系,实现对水印信息的嵌入、提取和盲检测。在提取过程中结合线性伸缩恢复的方法消除时间轴上线性伸缩带来的影响。实验结果表明,该算法对多种音频文件的操作和攻击均具有良好的鲁棒性。     

Dynamic slack allocation algorithms for energy minimization on parallel machines

We explore novel algorithms for DVS (Dynamic Voltage Scaling) based energy minimization of DAG (Directed Acyclic Graph) based applications on parallel and distributed machines in dynamic environments. Static DVS algorithms for DAG execution use the estimated execution time. The estimated time in practice is overestimated or underestimated. Therefore, many tasks may be completed earlier or later than expected during the actual execution. For overestimation, the extra available slack can be added to future tasks so that energy requirements can be reduced. For underestimation, the increased time may cause the application to miss the deadline. Slack can be reduced for future tasks to reduce the possibility of not missing the deadline. In this paper, we present novel dynamic scheduling algorithms for reallocating the slack for future tasks to reduce energy and/or satisfy deadline constraints. Experimental results show that our algorithms are comparable to static algorithms applied at runtime in terms of energy minimization and deadline satisfaction, but require considerably smaller computational overhead.     

Global and robust formation-shape stabilization of relative sensing networks

This paper proposes a simple, distributed algorithm that achieves global stabilization of formations for relative sensing networks in arbitrary dimensions with fixed topology. Assuming the network runs an initialization procedure to equally orient all agent reference frames, convergence to the desired formation shape is guaranteed even in partially asynchronous settings. We characterize the algorithm robustness against several sources of errors: link failures, measurement errors, and frame initialization errors. The technical approach combines algebraic graph theory, multidimensional scaling, and distributed linear iterations.     

Landmark MDS ensemble

Landmark multidimensional scaling (LMDS) uses a subset of data (landmark points) to solve classical multidimensional scaling (MDS), where the scalability is increased but the approximation is noise-sensitive. In this paper we present an LMDS ensemble where we use a portion of the input in a piecewise manner to solve classical MDS, combining individual LMDS solutions which operate on different partitions of the input. Ground control points (GCPs) that are shared by partitions considered in the ensemble, allow us to align individual LMDS solutions in a common coordinate system through affine transformations. We incorporate priors into combining multiple LMDS solutions such that the weighted averaging by priors improves the noise-robustness of our method. Our LMDS ensemble is much less noise-sensitive while maintaining the scalability and the speed of LMDS. Experiments on synthetic data (noisy grid) and real-world data (similar image retrieval) confirm the high performance of the proposed LMDS ensemble.     

SMS云网关负载感知弹性伸缩控制算法

SMS短信网关（Short Message Service,SMS）具有并发量大、峰值高、难预测以及消耗资源量大的特点,如何保障系统高效、稳定运行一直是电信运营商致力解决的关键问题之一.本文提出了一种能够通过云计算平台动态资源控制能力,实现负载感知的弹性SMS云网关设计方案及弹性控制算法,提升了SMS短信网关服务质量目标保障效率,以及资源利用率.仿真环境下测试结果显示相比现有算法,弹性控制算法执行效率更高,集群规模随资源利用率抖动性更小.     

结合色彩特征和空域特征的成捆原木轮廓识别

成捆原木检尺自动化不仅能够提高生产效率, 而且是林木资源管理的需要. 通过图像处理得原木检尺直径和统计根数, 这是实现检尺自动化中的重要环节. 由于原木生产作业现场获取的成捆原木图像背景多样, 拍照时自然光照条件不一, 成捆原木轮廓识别需要较多的人工交互. 通过研究成捆原木端面彩色图像中原木的色彩特征, 利用它滤除大量的不相关背景, 留下原木色彩近似的像素点; 并结合拉普拉斯滤波器, 获得原木边缘, 实现成捆原木轮廓的分离, 从而获得原木轮廓.     

Extending metric multidimensional scaling with Bregman divergences

Sum of weighted square distance errors has been a popular way of defining stress function for metric multidimensional scaling (MMDS) like the Sammon mapping. In this paper we generalise this popular MMDS with Bregman divergences, as an example we show that the Sammon mapping can be thought of as a truncated Bregman MMDS (BMMDS) and we show that the full BMMDS improves upon the Sammon mapping on some standard data sets and investigate the reasons underlying this improvement. We then extend a well known family of MMDS, that deploy a strategy of focusing on small distances, with BMMDS and investigate limitations of the strategy empirically. Then an opposite strategy is introduced to create another family of BMMDS that gives increasing mapping quality. A data preprocessing method and a distance matrix preprocessing are introduced.