Parallel Computation of Fourier Transform on Distributed Memory Computer System

Multicomputer systems(distributed memory computer systems) are becoming more and more popular and will be wildly used in scientific researches. In this paper, we present a parallel algorithm of Fourier Transform of a vector of complex numbers on multicomputer system and give its computing times and its speedup in parallel environment supported by EXPRESS system on the multicomputer system which consists of four SGI workstations. Our analysis shows that the results is ideal and this scheme is suitable to multicomputer systems.

Edge Intelligence with Distributed Processing of DNNs:A Survey

Withthe rapiddevelopment of deep learning,the size of data sets anddeepneuralnetworks(DNNs)models are also booming.As a result,the intolerable long time for models’training or inference with conventional strategies can not meet the satisfaction of modern tasks gradually.Moreover,devices stay idle in the scenario of edge computing(EC),which presents a waste of resources since they can share the pressure of the busy devices but they do not.To address the problem,the strategy leveraging distributed processing has been applied to load computation tasks from a single processor to a group of devices,which results in the acceleration of training or inference of DNN models and promotes the high utilization of devices in edge computing.Compared with existing papers,this paper presents an enlightening and novel review of applying distributed processing with data and model parallelism to improve deep learning tasks in edge computing.Considering the practicalities,commonly used lightweight models in a distributed system are introduced as well.As the key technique,the parallel strategy will be described in detail.Then some typical applications of distributed processing will be analyzed.Finally,the challenges of distributed processing with edge computing will be described.

Dynamic Distribution Model with Prime Granularity for Parallel Computing

Dynamic distribution model is one of the best schemes for parallel volume rendering. How- ever, in homogeneous cluster system.since the granularity is traditionally identical, all processors communicate almost simultaneously and computation load may lose balance. Due to problems above, a dynamic distribution model with prime granularity for parallel computing is presented. Granularities of each processor are relatively prime, and related theories are introduced. A high parallel performance can be achieved by minimizing network competition and using a load balancing strategy that ensures all processors finish almost simultaneously. Based on Master-Slave-Gleaner ( MSG) scheme, the parallel Splatting Algorithm for volume rendering is used to test the model on IBM Cluster 1350 system. The experimental results show that the model can bring a considerable improvement in performance, including computation efficiency, total execution time, speed, and load balancing.

Parallel Computing Based Solution for Reliability-constrained Distribution Network Planning

The main goal of distribution network(DN)expansion planning is essentially to achieve minimal investment con-strained by specified reliability requirements.The reliability-constrained distribution network planning(RcDNP)problem can be cast as an instance of mixed-integer linear programming(MILP)which involves ultra-heavy computation burden especially for large-scale DNs.In this paper,we propose a parallel computing based solution method for the RcDNP problem.The RcDNP is decomposed into a backbone grid and several lateral grid problems with coordination.Then,a parallelizable augmented Lagrangian algorithm with acceleration method is developed to solve the coordination planning problems.The lateral grid problems are solved in parallel through coordinating with the backbone grid planning problem.Gauss-Seidel iteration is adopted on the subset of the convex hull of the feasible region constructed by decomposition.Under mild conditions,the optimality and convergence of the proposed method are verified.Numerical tests show that the proposed method can significantly reduce the solution time and make the RcDNP applicable for real-worldproblems.

Spatial Management of Distributed Social Systems

The paper describes the use of invented,developed,and tested in different countries of the high-level spatial grasp model and technology capable of solving important problems in large social systems,which may be represented as dynamic,self-evolving and distributed social networks.The approach allows us to find important solutions on a holistic level by spatial navigation and parallel pattern matching of social networks with active self-propagating scenarios represented in a special recursive language.This approach effectively hides inside the distributed and networked language implementation traditional system management routines,often providing hundreds of times shorter and simpler high-level solution code.The paper highlights the demands to efficient simulation of social systems,briefs the technology used,and provides some programming examples for solutions of practical problems.

The Design and Implementation of a Distributed Data Acquisition、Monitoring & Processing System (DDAMAP)

This report presents the design and implementation of a Distributed Data Acquisition、 Monitoring and Processing System (DDAMAP)。It is assumed that operations of a factory are organized into two-levels: client machines at plant-level collect real-time raw data from sensors and measurement instrumentations and transfer them to a central processor over the Ethernets, and the central processor handles tasks of real-time data processing and monitoring. This system utilizes the computation power of Intel T2300 dual-core processor and parallel computations supported by multi-threading techniques. Our experiments show that these techniques can significantly improve the system performance and are viable solutions to real-time high-speed data processing.

基于FPGA的新能源低压直流配电系统暂态实时仿真研究

对新能源低压直流配电系统开展暂态实时仿真研究对优化其运行控制具有重要作用。由于现场可编程门阵列(FPGA)内部集成了大量具有不同功能的电路,FPGA正成为电力系统暂态实时仿真领域主要的计算载体之一。该文面向新能源低压直流配电系统的暂态实时仿真需求,开发了一种基于FPGA的包含小型分布式风力发电、光伏发电以及蓄电池储能单元的新能源低压直流配电系统暂态实时仿真器。首先,研究构建了分布式发电单元和典型控制回路的计算模块,利用FPGA的并行计算特性并结合“算法-结构-有效匹配(AAA)”理念建立了底层模块串并联混合求解结构;然后,在节点分析法的框架下,建立了一种结合矩阵LDU分解和有向无环图(DAG)的电气系统节点电导矩阵并行求解方法;最后,在建立电气系统与控制系统并行求解架构的基础上,开发了一种基于FPGA的新能源低压直流配电系统暂态实时仿真器,通过将其仿真结果与PSCAD/EMTDC离线仿真平台的计算结果进行对比,验证了所开发暂态实时仿真器的有效性和准确性。

高分三号数据分布式自适应负载均衡并行转换算法研究

针对PolSARpro软件自带高分三号数据转换模块无法自适应分布式差异化硬件环境问题,提出了一种按照该软件的数据格式要求进行分布式自适应负载均衡并行转换算法,将高分三号多极化数据快速、精确地进行定标与格式转换,对不同硬件配置环境自适应,能够抗数据偏斜,并且通过KingMap V10.5平台实现了算法并在实际数据中进行测试,试验结果表明性能提升了约12.7倍,验证了算法的可行性、高效性和正确性。

基于GPU加速的分布式水文模型并行计算性能

针对具有物理机制的分布式水文模型对大流域、长序列模拟计算时间长、模拟速度慢的问题,引入基于GPU的并行计算技术,实现分布式水文模型WEP-L(water and energy transfer processes in large river basins)产流过程的并行化。选择鄱阳湖流域为实验区,采用计算能力为8.6的NVIDIA RTX A4000对算法性能进行测试。研究表明:提出的基于GPU的分布式水文模型并行算法具有良好的加速效果,当线程总数越接近划分的子流域个数(计算任务量)时,并行性能越好,在实验流域WEP-L模型子流域单元为8712个时,加速比最大达到2.5左右;随着计算任务量的增加,加速比逐渐增大,当实验流域WEP-L模型子流域单元增加到24897个时,加速比能达到3.5,表明GPU并行算法在大尺度流域分布式水文模型计算中具有良好的发展潜力。

基于正序瞬时功率算法的宽频振荡检测技术

现代电力系统表现出含高比例可再生能源和高比例电力电子设备的“双高”特征,电力系统中不同频率的谐波、间谐波与工频量相互作用,将可能导致宽频振荡,威胁电力系统安全稳定运行。针对无法在三相不平衡状态下实现宽频振荡准确检测的问题,提出了基于FPGA(现场可编程门阵列)和正序瞬时功率算法的宽频振荡检测技术。利用三相正序瞬时功率能滤除三相不平衡分量的原理,确保宽频振荡的检测结果不受三相不平衡的影响。利用FPGA并行计算的特性,大幅提升了宽频振荡检测算法的性能。测试结果表明,该技术能够在发生宽频振荡时准确检测出振荡分量,解决了现有技术存在误判和并行计算能力不足的问题。

Evolutionary Neural Architecture Search and Its Applications in Healthcare

Most of the neural network architectures are based on human experience,which requires a long and tedious trial-and-error process.Neural architecture search(NAS)attempts to detect effective architectures without human intervention.Evolutionary algorithms(EAs)for NAS can find better solutions than human-designed architectures by exploring a large search space for possible architectures.Using multiobjective EAs for NAS,optimal neural architectures that meet various performance criteria can be explored and discovered efficiently.Furthermore,hardware-accelerated NAS methods can improve the efficiency of the NAS.While existing reviews have mainly focused on different strategies to complete NAS,a few studies have explored the use of EAs for NAS.In this paper,we summarize and explore the use of EAs for NAS,as well as large-scale multiobjective optimization strategies and hardware-accelerated NAS methods.NAS performs well in healthcare applications,such as medical image analysis,classification of disease diagnosis,and health monitoring.EAs for NAS can automate the search process and optimize multiple objectives simultaneously in a given healthcare task.Deep neural network has been successfully used in healthcare,but it lacks interpretability.Medical data is highly sensitive,and privacy leaks are frequently reported in the healthcare industry.To solve these problems,in healthcare,we propose an interpretable neuroevolution framework based on federated learning to address search efficiency and privacy protection.Moreover,we also point out future research directions for evolutionary NAS.Overall,for researchers who want to use EAs to optimize NNs in healthcare,we analyze the advantages and disadvantages of doing so to provide detailed guidance,and propose an interpretable privacy-preserving framework for healthcare applications.

基于流计算和大数据平台的实时交通流预测

目前交通流预测实时性差,很难满足在线分析和预测任务的需求,基于此提出一种Flink流计算框架和大数据平台结合的实时交通流预测方法。基于流计算框架实时捕捉和预处理数据,包括采用Flink的transform算子对数据进行校验和处理,将处理后的数据sink到大数据的HDFS文件系统,交由下一步的大数据并行框架进行分析建模与训练,实现基于流计算和大数据平台的实时交通流预测。实验结果表明,Flink能够实时捕捉和预处理交通流数据,把数据准时无误送入分布式文件系统中,在此基础上借助大数据框架下的并行分析和建模优势,在实时性数据分析与预测方面取得了较好的效果。

一种基于HDFS的分布式文件系统MPIFS

传统的MPI(Message Passing Interface)计算特点是数据向计算迁移,对于数据量庞大的计算任务具有先天的不足。文中提出一种支持MPI的分布式文件系统MPIFS的架构及实现。该文件系统基于HDFS(Hadoop Distributed File System),使得MPI在MPIFS上能同时支持计算密集型和数据密集型计算,设置两个类型的批处理词频统计实验,所需数据都分布式存储在MPIFS分布式文件系统中,通过调用系统提供的统一数据接口实现数据访问。1个计算节点在本地计算大小为m的文件,n个计算节点分布式并行计算大小为n×m的文件,两者计算时间相同,MPIFS中文件总量不变,计算节点数量减少,计算时间t变长,可得出MPIFS文件系统架构可行,能够支持MPI实现计算向数据迁移的并行计算。

分布式服务资源自适应弹性伸缩研究综述

分布式服务资源环境下,由于峰值负载的整体占比很小,大量服务资源长期处于低利用率甚至闲置状态。通过实现资源自适应弹性伸缩,在高负载时扩充服务资源以应对高需求,在低负载时将其缩减以降低开销,可显著提升系统能效并降低运作开销。但实际负载通常具有很强的波动性,满足服务质量所需的服务资源持续变化,这给服务资源自适应弹性伸缩带来了巨大挑战。尽管现有的商用分布式平台已普遍具有一定的资源弹性伸缩能力,但它们的自适应能力有限、精准性不佳,存在很大提升空间。为促进该领域的研究与应用发展,就该环境下服务资源自适应弹性伸缩研究进行分类分析与探讨。分析并介绍了相应的研究背景及主要存在于需求评估与资源调整上的挑战;就该领域的国内外相关研究,依据其调整的资源对象分为三类,以此进行分类论述并比较了各研究工作的异同,且就各自的特点与效用进行了分析与总结;总述分析了这些研究工作并概括出一个全面而整体的实现,探讨了业界的应用现状、研究面临的挑战以及未来趋势。

基于Spark的叠加能量寻优反射波剩余静校正算法的工程化实现

叠加能量寻优反射波剩余静校正方法是解决剩余静校正问题的有效方法之一,该方法精度高,但计算量大且需要进行多域数据切换。随着原始数据量的不断增长,其算法实现的高效运行成为主要的应用瓶颈问题。分析了叠加能量寻优反射波剩余静校正方法计算密集、通讯密集的特征,针对算法难以实现并行计算的难点,提出了基于Spark分布式内存计算模型的技术解决方案,实现了海量地震数据弹性分布式数据集的高效流转和多域数据的灵活切换,完成了叠加能量寻优反射波剩余静校正方法的多节点分布式并行计算,提高了大数据情形下方法的适应性和计算效率,提升了其在地震数据处理中的实用化程度。实际生产数据的应用结果表明,基于Spark的叠加能量寻优反射波剩余静校正的软件模块在复杂近地表地震数据的处理中取得了能满足实际生产要求的应用效果,兼具适应性强和计算效率高的特点。

Parallel Implementation of Global Illumination Using PVM

In this paper an attempt of employing network resources to solve a complex and time-consuming problem is presented. The global illumination problem is selected as the study objective. An improved density estimation algorithm is first developed, in which the more inherent concurrency is explored. Then its parallel implementation by using a PVM mechanism and the running performance analysis are provided. The analysis results show the expected speed-up obtained and demonstrate that the PVM has good application prospects for parallel computation in a distributed network.

基于大数据的电力通信通道智能路由推荐策略研究

面对规模庞大、结构复杂的电力通信网,针对通信调度如何根据业务需求准确、合理、高效地安排通信通道,提出了一种基于分布式图并行计算的大数据智能路由推荐方法。该方法根据电力通信网特点构建电力通信网络拓扑模型、建立优选路由指标模型,并采用基于分布式图并行计算框架实现并行路由推荐算法。实验证明,该方法具有快速迭代与收敛的特性,在大型复杂的电力通信网络路由推荐与规划中具有良好的应用前景。

一种面向中长期交易数据安全校核的方法设计

为解决中长期交易安全校核由于规模较大、混合整数变量较多而导致的计算效率偏低问题,设计了一种基于分布式计算的中长期交易安全校核方法。在深入分析该计算方法基本概念与实施要点的基础上,提出了基于粒子群算法的分布式计算方法。通过拆分中长期交易安全校核模型中开停状态的整数变量,即将原有的大规模混合整数规划问题拆分为相互独立的多个子问题,从而实现了原问题的并行计算。在某电网实际数据上构造的算例表明,在确保计算可信度的前提下,分布式计算方法可有效提升中长期交易安全校核的计算效率。且所提方法的计算耗时仅为38 s,显著优于对比方法。

基于MPI、MapReduce和OpenMP混合编程的高分三号数据分布式并行转换算法

高分三号是我国C波段多极化合成孔径雷达卫星,形成三星组网星座。PolSARpro是欧空局支持下的一款SAR影像处理的开源软件。为了便于使用该软件来处理高分三号数据,提出了一种根据PolSARpro软件的数据格式要求进行分布式并行转换算法。该算法内层采用OpenMP按极化方式并行计算,中间层采用MapReduce按景并行处理,外层采用MPI按任务分布式计算,最终实现将高分三号极化数据快速精确转化为复数散射矩阵S2数据格式。通过KingMap V10.0平台实现了算法并在实际数据中进行测试,验证了算法的高效性、可行性和正确性。

基于MPI和MapReduce混合编程的高分三号多模数据分布式并行转换算法

我国高分三号形成三星陆海雷达卫星星座。为了提升PolSARpro极化SAR图像处理的开源软件在高分三号数据转换环节的处理能力,提出了基于OpenMP、MapReduce和MPI并按照PolSARpro软件的数据格式要求进行分布式并行转换处理算法,将不同成像模式下的多极化数据实现快速定标和格式转换,并且通过KingMap V10.0 GIS平台实现了算法并在实际数据中进行测试,验证了算法的高效性、可靠性、易扩展性和正确性。