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A QUADRATIC-programming model FOR OPTIMAL DATA DISTRIBUTION

BIT 1981年第3期21卷 294-304页

作者： LAM, CM FUNG, KT School of Computer Science University of Windsor N9B 3P4 Windsor Ontario Canada

In this paper, a quadratic programming model is developed to take into consideration a number of factors that can influence the process of optimal allocation of data among the nodes in a distributed database. The factors include communication costs, translation costs, congestion costs and storage costs. Beale's method is used to solve the resulting quadratic program. Some numerical examples are presented and the potentials of such an approach in the design and analysis of distributed databases are discussed.

关键词： Computational Mathematic programming model Data Distribution Quadratic programming Communication Cost

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A Dynamic programming model of the Coordination between Forest and Socio-economy

A Dynamic Programming Model of the Coordination between Fore...

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International Conference on Applied Mechanics and Mechanical Engineering

作者： Ye, Tao Hangzhou Dianzi Univ Sch Management Hangzhou 310037 Zhejiang Peoples R China

ISBN: (纸本)9780878492459

Based on the illustration of the importance of the coordination between forest and socio-economy, a dynamic programming model aimed at the coordination is created and the basic characters of the functions in the model are discussed. A solution under a simple and ideal situation is studied, which results in the equation of the economic yield when forest coordinates with socio-economy and several other conclusions.

关键词： Dynamic programming model Forest Socio-economy

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ConMR: Concurrent MapReduce programming model for Large Scale Shared-Data Applications

ConMR: Concurrent MapReduce Programming Model for Large Scal...

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42nd Annual International Conference on Parallel Processing (ICPP)

作者： Zhang, Fan Malluhi, Qutaibah M. Elsyed, Tamer M. Carnegie Mellon Univ Qatar Dept Comp Sci Doha Qatar Qatar Univ Dept Comp Sci & Engn Doha Qatar

ISBN: (纸本)9780769551173

The rapid growth of large-data processing has brought in the MapReduce programming model as a widely accepted solution. However, MapReduce limits itself to a one-map-to-one-reduce framework. Meanwhile, it lacks built-in support and optimization when the input datasets are shared among concurrent applications and/or jobs. The performance might be improved when the shared and frequently accessed data is read from local instead of distributed file system. To enhance the performance of big data applications, this paper presents Concurrent MapReduce, a new programming model built on top of MapReduce that deals with large amount of shared data items. Concurrent MapReduce provides support for processing heterogeneous sources of input datasets and offers optimization when the datasets are partially or fully shared. Experimental evaluation has shown an execution runtime speedup of 4X compared to traditional non-concurrent MapReduce implementation with a manageable time overhead.

关键词： Concurrency MapReduce programming model Shared Input Data

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Web-based programming model 6

Web-based programming model

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6th International Conference on modeling, Simulation, and Applied Optimization (ICMSAO)

作者： Anastasiu, Doru Popescu Boroghina, Gabriel Univ Pitesti Fac Math & Comp Sci Pitesti Romania Natl Coll Radu Greceanu Dept Comp Sci Slatina Romania

ISBN: (纸本)9781467366014

In order to use a program written in C++ or in another programming language, a compiler and an development environment are necessary. In this paper we will present a method of using a C++ program from a web page and one of showing the results by using HTML, the ASP. NET framework and the Windows version of GNU GCC compiler -MinGW. The programming model presented in this paper can also be used for other compilers. The described application allows the implementation, test and usage of some algorithms without installing a development environment, using only a browser to connect to the Internet.

关键词： programming model C plus plus program *** HTML compiling interface connection web pages

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An enhanced programming model for internet based cycle stealing

An enhanced programming model for internet based cycle steal...

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International Conference on Parallel and Distributed Processing Techniques and Applications

作者： Kelly, W Roe, P Sumitomo, J Queensland Univ Technol Ctr Informat Technol Innovat St Lucia Qld Australia

ISBN: (纸本)1892512459

Most current cycle stealing systems, especially those designed for the Internet require programmers to adopt the master-worker parallel programming paradigm. The master-worker paradigm is extremely limiting from an abstraction point of view as it requires a single master thread to expose all of the parallelism that the application hopes to exploit. In this paper we describe how we have extended our Internet cycle stealing system G2, to support more general parallel programming paradigms in which any task can create subtasks and in which tasks become self contained units of abstraction. The major problem addressed is how to allow tasks to wait for the results of their subtasks without tying up the resources of volunteer machines. By drawing a programming analogy with the asynchronous implementation of web services in *** we create a familiar yet powerful programming model for creating parallel programs using a variety of paradigms.

关键词： parallel programming programming model cycle stealing NET web services

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CharmPy: A Python Parallel programming model

CharmPy: A Python Parallel Programming Model

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IEEE International Conference on Cluster Computing (CLUSTER)

作者： Galvez, Juan J. Senthil, Karthik Kale, Laxmikant V. Univ Illinois Dept Comp Sci Champaign IL 61820 USA

ISBN: (纸本)9781538683194

Parallel programming can be extremely challenging. programming models have been proposed to simplify this task, but wide acceptance of these remains elusive for many reasons, including the demand for greater accessibility and productivity. In this paper, we introduce a parallel programming model and framework called CharmPy, based on the Python language. CharmPy builds on Charm++, and runs on top of its C++ runtime. It presents several unique features in the form of a simplified model and API, increased flexibility, and the ability to write everything in Python. CharmPy is a high-level model based on the paradigm of distributed migratable objects. It retains the benefits of the Charm++ runtime, including dynamic load balancing, asynchronous execution model with automatic overlap of communication and computation, high performance, and scalability from laptops to supercomputers. By being Python-based, CharmPy also benefits from modern language features, access to popular scientific computing and data science software, and interoperability with existing technologies like C, Fortran and OpenMP. To illustrate the simplicity of the model, we will show how to implement a distributed parallel map function based on the Master-Worker pattern using CharmPy, with support for asynchronous concurrent jobs. We also present performance results running stencil code and molecular dynamics mini-apps fully written in Python, on Blue Waters and Cori supercomputers. For stencil3d, we show performance similar to an equivalent MPI-based program, and significantly improved performance for imbalanced computations. Using Numba to JIT-compile the critical parts of the code, we show performance for both mini-apps similar to the equivalent C++ code.

关键词： programming model parallel programming distributed computing multiprocessing Python HPC

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A Scenario-Aware Dataflow programming model 18

A Scenario-Aware Dataflow Programming Model

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18th Euromicro Conference on Digital System Design (DSD)

作者： van Kampenhout, Reinier Stuijk, Sander Goossens, Kees Eindhoven Univ Technol NL-5600 MB Eindhoven Netherlands

ISBN: (纸本)9781467380355

The FSM-SADF model of computation allows to find a tight bound on the throughput of firm real-time applications by capturing dynamic variations in scenarios. We explore an FSM-SADF programming model, and propose three different alternatives for scenario switching. The best candidate for our CompSOC platform was implemented, and experiments confirm that the tight throughput bound results in a reduced resource budget. This comes at the cost of a predictable overhead at runtime as well as increased communication and memory budgets. We show that design choices offer interesting trade-offs between run-time cost and resource budgets.

关键词： CompSOC dataflow programming model scenario-aware data flow Runtime Budgets Throughput programming

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Energy-efficient Distributed programming model for Swarm Robot

Energy-efficient Distributed Programming Model for Swarm Rob...

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13th International Conference on Control, Automation and Systems (ICCAS)

作者： Huh, Sungju Hong, Seongsoo Lee, Joonghyun Seoul Natl Univ Dept Elect & Comp Engn Seoul 151744 South Korea Seoul Natl Univ Grad Sch Convergence Sci & Technol Dept Transdisciplinary Studies Seoul 443270 South Korea

ISBN: (纸本)9788993215052

A swarm robot system is a multi-robot system which consists of a large number of simple, lightweight and interoperating robots. Since it mimics the behaviors of social insects, it is critical to program artificial swarm intelligence in a versatile manner. Distributed, scalable and severely resource-limited nature of swarm robotics, however, makes it very difficult to write application programs. In this paper, we propose an easy-to-use and effective programming model that addresses such programming difficulties as well as the energy-efficient deployment and execution of swarm intelligence programs. Specifically, the proposed model lets programmers concentrate on writing a core swarm intelligence algorithm while abstracting the implementation issues such as communication, synchronization and parallel processing of the algorithms. In order to show the utility and viability of the proposed approach, we have demonstrated a 3D map building application and performed experiments. The results show that the proposed approach reduces data traffic up to 82% with an acceptable error.

关键词： Swarm robotics programming model Energy efficient modeling Data aggregation

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SysCellC: a data-flow programming model on multi-GPU

SysCellC: a data-flow programming model on multi-GPU

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International Conference on Computational Science (ICCS)

作者： Houzet, Dominique Huet, Sylvain Rahman, Anis CNRS GIPSA Lab F-38402 St Martin Dheres France

High performance computing with low cost machines becomes a reality with GPU. Unfortunately, high performances are achieved when the programmer exploits the architectural specificities of the GPU prefetching: he has to focus on inter-GPU communications, task allocations among the GPUs, task scheduling, external memory prefetching, and synchronization. In this paper, we propose and evaluate a compile flow. It automates the transformation of a program expressed with the high level system design language SystemC, to its implementation on a cluster of multi-GPU. SystemC constructs and schedualer are directly mapped to the GPU API, preserving their semantic. Inter-GPU communications are abstracted by means of SystemC channels. (C) 2010 Published by Elsevier Ltd.

关键词： programming model GPU SystemC

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RoleML: a Role-Oriented programming model for Customizable Distributed Machine Learning on Edges 24

RoleML: a Role-Oriented Programming Model for Customizable D...

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25th International Middleware Conference

作者： Tan, Yuesheng Yang, Lei Li, Wenhao Wu, Yuda South China Univ Technol Guangzhou Guangdong Peoples R China

ISBN: (纸本)9798400706233

Edge AI aims to enable distributed machine learning (DML) on edge resources to fulfill the need for data privacy and low latency. Meanwhile, the challenge of device heterogeneity and discrepancy in data distribution requires more sophisticated DML architectures that differ in topology and communication strategy. This calls for a standardized and general programming interface and framework to develop them. Existing frameworks are only meant for specific architectures (e.g., FedML and Flower for Federated Learning) and do not support others by design. This paper presents RoleML, a novel programming model for general DML architecture development. RoleML breaks a DML architecture into a series of interactive components and represents them with a unified abstraction named role. The behavior of each role is expressed as several message channels, while its workloads are declared as elements in order to decouple from the distributed training workflow. Powered by a runtime system, RoleML allows developers to flexibly and dynamically assign roles to different computation nodes, simplifying the implementation of complex architectures. The runtime further improves the reliability of DML applications via an automatic role offloading mechanism based on containerization. We conduct case studies and experiments to demonstrate the wide applicability and high customizability of RoleML with low performance overhead, as well as the effectiveness of the role offloading mechanism in mitigating device overload.

关键词： programming model Distributed Machine Learning Edge Computing Computation Offloading

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