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Utilizing the Gaode Open API for Evaluating Fire- Fighting Facility Planning

Utilizing the Gaode Open API for Evaluating Fire- Fighting F...

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Cloud Computing, Big Data applications and Software Engineering (CBASE), international conference on

作者： Bing Han Junjun Fan Jing Wang Yunfei Ding College of Horticulture Jinling Institute of Technology Nanjing China School of Government Nanjing University Nanjing China

ISBN: (数字)9798331506582

ISBN: (纸本)9798331506599

Big data has been widely used in urban planning and architecture in recent years. However, data collecting techniques limit its broader use. As a result, a lot of work has been done to precisely identify and address urban problems through the mining of legally accessible open-source internet data, which has progressively gained popularity among urban scholars. In light of this, using Nanjing as an example, this study uses the Gaode OPEN API to build urban real-time traffic circles and assess the layout of firefighting facilities. In order to extract the average vehicle speed of all roads within a certain time frame and to automatically collect real-time traffic data in the study region, a batch processing model is first developed based on the Gaode OPEN API. It was discovered that the speed causes Nanjing City to be divided into multiple different zones. After that, a case study is carried out to build an urban real-time traffic circle based on the current firefighting facilities using the Python programming language and Arcgis software. After further analysis, it is found that the current planning for firefighting facilities exhibits a notable regional difference between the urban centre and the suburbs. Traffic speed, station density, and road network density all influence the service coverage area of fire stations. This study offers a comprehensive approach for gathering and analysing Gaode data, mining its spatiotemporal properties, and using it in planning evaluation procedures. This strategy highlights the benefits of streaming data features and distributed big data processing, efficiently uses the real-time nature of big data in emergency facility planning, and is expected to expand ideas for data collection.

关键词： Roads Urban planning distributed databases Real-time systems Software Planning Spatiotemporal phenomena Data mining Software engineering Python

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Progress in parallelizing XOOPIC

Progress in parallelizing XOOPIC

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IEEE international conference on Plasma Science (ICOPS)

作者： P.J. Mardahl J.P. Verboncoeur University of California Berkeley Berkeley CA US

Summary form only given. XOOPIC (object oriented particle in cell code for X11-based Unix workstations) is presently a serial 2d 3v particle-in-cell plasma simulation. The present effort focuses on using parallel and distributed processing to optimize the simulation for large problems. The benefits include increased capacity for memory intensive problems, and improved performance for processor-intensive problems.

关键词： Object oriented modeling Equations Workstations Concurrent computing Physics computing Plasma simulation Magnetohydrodynamic power generation Plasma applications Plasma confinement Plasma devices

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Informatics Engineering and Information Science, Part III 2011

引用

丛书名： Communications in Computer and Information Science

2011年

作者： Azizah Abd Manaf Shamsul Sahibuddin Rabiah Ahmad Salwani Mohd Daud Eyas El-Qawasmeh

ISBN: (数字)9783642254628

ISBN: (纸本)9783642254611

This 4-Volume-Set, CCIS 0251 - CCIS 0254, constitutes the refereed proceedings of the international conference on Informatics Engineering and Information Science, ICIEIS 2011, held in Kuala Lumpur, Malaysia, in November 2011. The 210 revised full papers presented together with invited papers in the 4 volumes were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on e-learning, information security, software engineering, image processing, algorithms, artificial intelligence and soft computing, e-commerce, data mining, neural networks, social networks, grid computing, biometric technologies, networks, distributed and parallel computing, wireless networks, information and data management, web applications and software systems, multimedia, ad hoc networks, mobile computing, as well as miscellaneous topics in digital information and communications.

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Lit: A high performance massive data computing framework based on CPU/GPU cluster

Lit: A high performance massive data computing framework bas...

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IEEE international conference on Cluster Computing

作者： Yanlong Zhai Emmanuel Mbarushimana Wei Li Jing Zhang Ying Guo Beijing Engineering Research Center of Massive Language Information Processing Beijing Institute of Technology Beijing China Science and Technology on Complex Systems Simulation Laboratory Beijing China

Big data processing is receiving significant amount of interest as an important technology to reveal the information behind the data, such as trends, characteristics, etc. MapReduce is considered as the most efficient distributed parallel data processing framework. However, some high-end applications, especially some scientific analyses have both data-intensive and computation-intensive features. Current big data processing techniques like Hadoop are not designed for computation-intensive applications, thus have insufficient computation power. In this paper, we presented Lit, a high performance massive data computing framework based on CPU/GPU cluster. Lit integrated GPU with Hadoop to improve the computational power of each node in the cluster. Since the architecture and programming model of GPU is different from CPU, Lit provided an annotation based approach to automatically generate CUDA codes from Hadoop codes. Lit hided the complexity of programming on CPU/GPU cluster by providing extended compiler and optimizer. To utilize the simplified programming, scalability and fault tolerance benefits of Hadoop and combine them with the high performance computation power of GPU, Lit extended the Hadoop by applying a GPUClassloader to detect the GPU, generate and compile CUDA codes, and invoke the shared library. Our experimental results show that Lit can achieve an average speedup of 1x to 3x on three typical applications over Hadoop.

关键词： Graphics processing units Computational modeling Handheld computers Data models Load modeling Semantics

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Short Paper: Evaluation of stdpar Compilers on a Kernel Matrix Assembly and a BLAS Level 3 SYMM Kernel

Short Paper: Evaluation of stdpar Compilers on a Kernel Matr...

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international Symposium on parallel and distributed Computing

作者： Marcel Breyer Alexander Van Craen Dirk Pflüger IPVS University of Stuttgart Stuttgart Germany

ISBN: (数字)9798350369199

ISBN: (纸本)9798350369205

The introduction of stdpar in C++ introduces parallel algorithms into the standard library, which allows developers to easily harness the power of parallelism in their applications, leading to potential performance improvements, scalability, increased productivity, and improved reproducibility in scientific computing tasks. At least theoretically, as its performance depends on the compiler in use. In this paper, we examine the usability of stdpar and demonstrate the significant differences between different stdpar compilers. To this end, we study a kernel matrix assembly algorithm and a BLAS level 3 SYMM function, both implemented in the parallel Least Squares Support Vector Machine (PLSSVM) library. The same code is compiled with an NVIDIA nvc++, gcc, Intel oneAPI icpx, and AdaptiveCpp compiler. We analyzed the code on an NVIDIA A30 GPU, an AMD MI210 GPU, and a dual-socket AMD EPYC 9274F CPU machine. First, we report surprisingly large runtime differences between the different stdpar compilers: up to 11 percent on the NVIDIA A30 GPU and even up to 335% on two AMD EPYC 9274F. Second, we show how stdpar enables energy reduction by a factor of up to 20.7 with the very same implementation by utilizing different hardware *** code, utility scripts, and documentation are all available on GitHub: https://***/SC-SGS/PLSSVM

关键词： Codes Runtime Graphics processing units C++ languages Hardware Libraries Kernel Usability Standards Assembly

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Breaking the barriers: two models for MPI programming

Breaking the barriers: two models for MPI programming

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international conference on parallel Architecture and Compilation Techniques (PACT)

作者： J. Roda C. Rodriguez D.G. Morales F. Almeida P. Pulido D. Dorta Dpto. Estadistica I.O. y Computacion Univ. de La Laguna Tenerife Spain

The asynchronous nature of many MPI/PVM programs does not fit the BSP model. The barrier synchronization imposed by the model restricts the range of available algorithms and their performance. Through the suppression of barriers and the generalization of the concept of superstep we propose two new models, the BSP-like and the BSP Without Barriers (BSPWB) models. While the BSP-like extends the BSP* model to programs written using collective operations, the more general BSPWB model admits the MPI/PVM parallel asynchronous programming style. As LogP, the model encourages locality but it is simpler to use. The parameters of the models and their quality are evaluated on a distributed shared memory machine, the Origin 2000 and on a distributed memory machine, the CRAY T3E. The dependence of the time spent in an h-relation is stronger in the communication pattern than in the number of processors. The total variation of the h-relation time in both the patterns and processor numbers is smaller than sixty nanoseconds. To illustrate the proposed models, two different applications are considered: a parallel Sort using Regular Sampling (PSRS) and a parallel Dynamic Programming Algorithm solving the Single Resource Allocation Problem (SRAP). The PSRS is a synchronous algorithm with a rich set of collective communication patterns and coarse grain communications. On the opposite extreme, the SRAP is a fine grain communication algorithm using permutation patterns. The computational results prove the accuracy of the models. The prediction of the communication times is robust even for the SRAP, where communication is dominated by small messages.

关键词： Costs parallel processing parallel programming Tellurium Sampling methods Dynamic programming Resource management Computer networks Concurrent computing Computational modeling

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A new distributed approximation algorithm for constructing minimum connected dominating set in wireless ad hoc networks 04

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Proceedings of the Second international conference on parallel and distributed processing and applications

作者： Bo Gao Huiye Ma Yuhang Yang Dept. of Electronic Engineering Shanghai Jiao Tong University Shanghai China Dept. of Computer Science and Engineering Chinese University of Hong Kong

ISBN: (纸本)9783540241287

In this paper, we present a new distributed approximation algorithm that constructs a minimum connected dominating set (MCDS) for wireless ad hoc networks based on a maximal independent set (MIS). Our algorithm, which is fully localized, has a constant approximation ratio, and O(n) time and O(n) message complexity. In this algorithm each node only requires the knowledge of its one-hop neighbors and there is only one shortest path connecting two dominators that are at most three hops away. Compared with other MCDS approximation algorithms, our algorithm shows better efficiency and performance than them.

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InfoBus repeater: a secure and distributed publish/subscribe middleware

InfoBus repeater: a secure and distributed publish/subscribe...

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international conference on parallel processing Workshops (ICPPW)

作者： N. Uramoto H. Maruyama IBM Research Tokyo Research Laboratory Yamato Kanagawa Japan

InfoBus repeater is a Java middleware for publish and subscribe communication. The design goal of InfoBus repeater is threefold: (1) to use an industry-standard pub/sub API, (2) to achieve salability through IP multicast technology, and (3) to provide public-key based security. This paper describes the architecture of InfoBus repeater and discusses its use in application programming. Two examples of an application called distributed eSuite are introduced in this paper.

关键词： Repeaters Middleware Java Security Multicast protocols Electrical capacitance tomography XML Laboratories Sockets Vehicles

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Deadlock-Free Adaptive Routing Based on the Repetitive Turn Model for 3D Network-on-Chip

Deadlock-Free Adaptive Routing Based on the Repetitive Turn ...

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IEEE international conference on Big Data and Cloud Computing (BdCloud)

作者： Yuan Cai Dong Xiang Xiang Ji School of Software Tsinghua University Beijing China

ISBN: (纸本)9781728111421;9781728111414

In this paper, we propose a new 3D Network-on-Chip(NoC) routing algorithm for vertically connected 2D mesh topology. There are many metrics to comment an efficient routing algorithm including high performance and cost-effective. However, existing 3D routing algorithms are unable to meet all these needs. We extend the high-performance 2D repetitive turn model(RTM) to a 3D scenario by applying their rules in 2D in addition to the new rules with respect to vertical turns to this end. The routing algorithms based on the 3D repetitive turn model have repetitive prohibited turns across the horizontal row, horizontal column and vertical direction without virtual channels. The simulation results demonstrate that the new 3D repetitive turn model approach could achieve lower latency and throughput improvement as compared to previous approaches which requires no virtual channel under uniform and non-uniform traffic pattern.

关键词： Routing Three-dimensional displays Two dimensional displays Solid modeling Adaptation models Network topology Topology

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X-Ray Computed Tomography Applied to Objects of Cultural Heritage: Porting and Testing the Filtered Back-Projection Reconstruction Algorithm on Low Power Systems-on-Chip

X-Ray Computed Tomography Applied to Objects of Cultural Her...

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Euromicro conference on parallel, distributed and Network-Based processing

作者： Elena Corni Lucia Morganti Maria Pia Morigi Rosa Brancaccio Matteo Bettuzzi Giuseppe Levi Eva Peccenini Daniele Cesini Andrea Ferraro Department of Physics and Astronomy University of Bologna Bologna Italy Bologna Section Italian Institute for Nuclear Physics (INFN) Bologna Italy Enrico Fermi Center for Study and Research Roma Italy CNAF Section Italian Institute for Nuclear Physics (INFN) Bologna Italy

The embedded and high-performance computing (HPC) sectors, that in the past were completely separated, are now somehow converging under the pressure of two driving forces: the release of less power consuming server processors and the increased performance of the new low power Systems-on-Chip (SoCs) developed to meet the requirements of the demanding mobile market. This convergence allows the porting to low power embedded architectures of applications that were originally confined to traditional HPC systems. In this paper, we present our experience of porting the Filtered Back-projection Algorithm to a low power, low cost system-on-chip, the NVIDIA Tegra K1, which is based on a quad core ARM CPU and on a NVIDIA Kepler GPU. This Filtered Back-projection Algorithm is heavily used in 3D Tomography reconstruction software. The porting has been done exploiting various programming languages (i.e. OpenMP, CUDA) and multiple versions of the application have been developed to exploit both the SoC CPU and GPU. The performances have been measured in terms of 2D slices (of a 3D volume) reconstructed per time unit and per energy unit. The results obtained with all the developed versions are reported and compared with those obtained on a typical x86 HPC node accelerated with a recent NVIDIA GPU. The best performances are achieved combining the OpenMP version and the CUDA version of the algorithm. In particular, we discovered that only three Jetson TK1 boards, equipped with Giga Ethernet interconnections, allow to reconstruct as many images per time unit as a traditional server, using one order of magnitude less energy. The results of this work can be applied for instance to the construction of an energy-efficient computing system of a portable tomographic apparatus.

关键词： Graphics processing units Image reconstruction Computer architecture Filtering algorithms Computed tomography Radiography

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