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Design Of Batrun Distributed Processing System, Fredy Tandiary, Suraj C. Kothari, Ashish Dixit 2017 Iowa State University

Design Of Batrun Distributed Processing System, Fredy Tandiary, Suraj C. Kothari, Ashish Dixit

Suraj Kothari

This paper discusses the design of BATRUN Distributed Processing System (DPS). We have developed this system to automate the execution of jobs in a cluster of workstations where machines belong to different owners. The objective is to use a general purpose cluster as one massive computer for processing large applications. In contrast to a dedicated cluster, the scheduling in BATRUN DPS must ensure that only the idle cycles are used for distributed computing and local users, when they are operating, have the full control of their machines. BATRUN DPS has several unique features: (1) group-based scheduling policy to ensure execution ...


Quo Vadis-A Framework For Intelligent Routing In Large Communication Networks., Armin Mikler, Johnny S. Wong, Vasant Honavar 2017 Iowa State University

Quo Vadis-A Framework For Intelligent Routing In Large Communication Networks., Armin Mikler, Johnny S. Wong, Vasant Honavar

Johnny Wong

This paper presents Quo Vadis, an evolving framework for intelligent traffic management in very large communication networks. Quo Vadis is designed to exploit topological properties of large networks as well as their spatio-temporal dynamics to optimize multiple performance criteria through cooperation among nodes in the network. It employs a distributed representation of network state information using local load measurements supplemented by a less precise global summary. Routing decisions in Quo Vadis are based on parameterized heuristics designed to optimize various performance metrics in an anticipatory or pro-active as well as compensatory or reactive mode and to minimize the overhead associated ...


An Object Oriented Approach To Modeling And Simulation Of Routing In Large Communication Networks, Armin Mikler, Johnny S. Wong, Vasant Honavar 2017 Iowa State University

An Object Oriented Approach To Modeling And Simulation Of Routing In Large Communication Networks, Armin Mikler, Johnny S. Wong, Vasant Honavar

Johnny Wong

The complexity (number of entities, interactions between entities, and resulting emergent dynamic behavior) of large communication environments which contain hundreds of nodes and links make simulation an important tool for the study of such systems. Given the difficulties associated with complete analytical treatment of complex dynamical systems, it is often the only practical tool that is available. This paper presents an example of a flexible, modular, object-oriented toolbox designed to support modeling and experimental analysis of a large family of heuristic knowledge representation and decision functions for adaptive self-managing communication networks with particular emphasis on routing strategies. It discusses in ...


Quo Vadis - Adaptive Heuristics For Routing In Large Communication Networks, Armin Mikler, Johnny S. Wong, Vasant Honavar 2017 Iowa State University

Quo Vadis - Adaptive Heuristics For Routing In Large Communication Networks, Armin Mikler, Johnny S. Wong, Vasant Honavar

Johnny Wong

This paper presents Quo Vadis, an evolving framework for intelligent traffic management in very large communication networks. Quo Vadis is designed to exploit topological properties of large networks as well as their spatio-temporal dynamics to optimize multiple performance criteria through cooperation among nodes in the network. It employs a distributed representation of network state information using local load measurements supplemented by a less precise global summary. Routing decisions in Quo Vadis are based on parameterized heuristics designed to optimize various performance metrics in an anticipatory or pro-active as well as compensatory or reactive mode and to minimize the overhead associated ...


Utility-Theoretic Heuristics For Intelligent Adaptive Routing In Large Communcation Networks, Armin Mikler, Vasant Honavar, Johnny S. Wong 2017 Iowa State University

Utility-Theoretic Heuristics For Intelligent Adaptive Routing In Large Communcation Networks, Armin Mikler, Vasant Honavar, Johnny S. Wong

Johnny Wong

Utility theory offers an elegant and powerful theoretical framework for design and analysis of autonomous adaptive communication networks. Routing of messages in such networks presents a real-time instance of a multi-criterion quasi-optimization problem in a dynamic and uncertain environment. In this paper, we examine several heuristic decision functions that can be used to guide messages along a near-optimal (e.g., minimum delay) path in a large network. We present an analysis of properties of such heuristics under a set of simplifying assumptions about the network topology and load dynamics. In particular, we identify the conditions under which one such utility-theoretic ...


Scalable Kernel Methods Via Doubly Stochastic Gradients, Bo Dai, Bo Xie, Niao He, Yingyu Liang, Anant Raj, Maria-Florina Balcan, Le Song 2017 Georgia Institute of Technology

Scalable Kernel Methods Via Doubly Stochastic Gradients, Bo Dai, Bo Xie, Niao He, Yingyu Liang, Anant Raj, Maria-Florina Balcan, Le Song

Bo Xie

The general perception is that kernel methods are not scalable, so neural nets become the choice for large-scale nonlinear learning problems. Have we tried hard enough for kernel methods? In this paper, we propose an approach that scales up kernel methods using a novel concept called doubly stochastic functional gradients''. Based on the fact that many kernel methods can be expressed as convex optimization problems, our approach solves the optimization problems by making two unbiased stochastic approximations to the functional gradient---one using random training points and another using random features associated with the kernel---and performing descent steps with this noisy ...


Switching Between Page Replacement Algorithms Based On Work Load During Runtime In Linux Kernel, Praveen Subramaniyam 2017 San Jose State University

Switching Between Page Replacement Algorithms Based On Work Load During Runtime In Linux Kernel, Praveen Subramaniyam

Master's Projects

Today’s computers are equipped with multiple processor cores to execute multiple programs effectively at a single point of time. This increase in the number of cores needs to be equipped with a huge amount of physical memory to keep multiple applications in memory at a time and to effectively switch between them, without getting affected by the low speed disk memory. The physical memory of today’s world has become so cheap such that all the computer systems are always equipped with sufficient amount of physical memory required effectively to run most of the applications. Along with the memory ...


Programming Models' Support For Heterogeneous Architecture, Wei Wu 2017 University of Tennessee, Knoxville

Programming Models' Support For Heterogeneous Architecture, Wei Wu

Doctoral Dissertations

Accelerator-enhanced computing platforms have drawn a lot of attention due to their massive peak computational capacity. Heterogeneous systems equipped with accelerators such as GPUs have become the most prominent components of High Performance Computing (HPC) systems. Even at the node level the significant heterogeneity of CPU and GPU, i.e. hardware and memory space differences, leads to challenges for fully exploiting such complex architectures. Extending outside the node scope, only escalate such challenges.

Conventional programming models such as data- ow and message passing have been widely adopted in HPC communities. When moving towards heterogeneous systems, the lack of GPU integration ...


Comparative Analysis Of Graph Partitioning Algorithms In Context Of Computation Offloading, San Ha Seo, Jeremy Straub 2017 North Dakota State University--Fargo

Comparative Analysis Of Graph Partitioning Algorithms In Context Of Computation Offloading, San Ha Seo, Jeremy Straub

Jeremy Straub

This paper considers the efficacy of using active network technology to offload computation from small mobile devices into network node computing centers. The performance of six algorithms for use in this process is compared and conclusions are drawn.


Improving Discovery And Patron Experience Through Data Mining, Boyuan Guan, Jamie Rogers 2017 Florida International University

Improving Discovery And Patron Experience Through Data Mining, Boyuan Guan, Jamie Rogers

Works of the FIU Libraries

As information professionals, we know simple database searches are imperfect. With rich and expansive digital collections, patrons may not find content that is buried in a long list of results. So, how do we improve discovery of pertinent materials and offer serendipitous experience? Following the example of recommendation functionality in online applications like Netflix, we have developed a recommendation function for our digital library system that provides relevant content beyond the narrow scope of patrons' original search parameters. This session will outline the reasoning, methodology, and design of the recommendation system as well as preliminary results from implementation.


Optimization Of A Reporting Process With Input From Multiple Systems, Cheri R. Freedman 2017 Western Oregon University

Optimization Of A Reporting Process With Input From Multiple Systems, Cheri R. Freedman

Student Theses, Papers and Projects (Computer Science)

This project involves the research, development, and improvement of a reporting process used to generate reports in adherence to contractual and legislative requirements. The project will review the beginning process, the proposed and implemented solutions, and the future of the project. The project addresses the goals of data quality, timeliness, and transparency throughout the paper including how they relate to the challenges, solution selection, and overall success of the project. The need for this project reflects the ongoing need for and some of the challenges that are typical of automation and systems integration in state government entities. As the role ...


Alternating Direction Method Of Multipliers For Penalized Zero-Variance Discriminant Analysis, Brendan P.W. Ames, Mingyi Hong 2017 University of Alabama - Tuscaloosa

Alternating Direction Method Of Multipliers For Penalized Zero-Variance Discriminant Analysis, Brendan P.W. Ames, Mingyi Hong

Mingyi Hong

We consider the task of classification in the high dimensional setting where the number of features of the given data is significantly greater than the number of observations. To accomplish this task, we propose a heuristic, called sparse zero-variance discriminant analysis, for simultaneously performing linear discriminant analysis and feature selection on high dimensional data. This method combines classical zero-variance discriminant analysis, where discriminant vectors are identified in the null space of the sample within-class covariance matrix, with penalization applied to induce sparse structures in the resulting vectors. To approximately solve the resulting nonconvex problem, we develop a simple algorithm based ...


Decomposition By Successive Convex Approximation: A Unifying Approach For Linear Transceiver Design In Heterogeneous Networks, Mingyi Hong, Qiang Li, Ya-Feng Liu 2017 Iowa State University

Decomposition By Successive Convex Approximation: A Unifying Approach For Linear Transceiver Design In Heterogeneous Networks, Mingyi Hong, Qiang Li, Ya-Feng Liu

Mingyi Hong

No abstract provided.


Sinr Constrained Beamforming For A Mimo Multi-User Downlink System: Algorithms And Convergence Analysis, Oingjang Shi, Meisam Razaviyayn, Mingyi Hong, Zhi-Quan Luo 2017 Zhejiang University

Sinr Constrained Beamforming For A Mimo Multi-User Downlink System: Algorithms And Convergence Analysis, Oingjang Shi, Meisam Razaviyayn, Mingyi Hong, Zhi-Quan Luo

Mingyi Hong

Consider a multiple-input multiple-output (MIMO) downlink multi-user channel. A well-studied problem in such a system is the design of linear beamformers for power minimization with the quality of service (QoS) constraints. The most representative algorithms for solving this class of problems are the so-called minimum mean square error (MMSE)-second-order cone programming (SOCP) algorithm [Visotksy and Madhow, “Optimum Beamforming Using Transmit Antenna Arrays,” Proc. IEEE Veh. Technol. Conf., May 1999, vol. 1, pp. 851-856] , [Wong, Zheng, and Ng, “Convergence Analysis of Downlink MIMO Antenna System Using Second-Order Cone Programming,” Proc. 62nd IEEE Veh. Technol. Conf., Sep. 2005, pp. 492-496] and ...


Asynchronous Distributed Admm For Large-Scale Optimization—Part I: Algorithm And Convergence Analysis, Tsung-Hui Chang, Mingyi Hong, Wei-Cheng Liao, Xiangfeng Wang 2017 The Chinese University of Hong Kong

Asynchronous Distributed Admm For Large-Scale Optimization—Part I: Algorithm And Convergence Analysis, Tsung-Hui Chang, Mingyi Hong, Wei-Cheng Liao, Xiangfeng Wang

Mingyi Hong

Aiming at solving large-scale optimization problems, this paper studies distributed optimization methods based on the alternating direction method of multipliers (ADMM). By formulating the optimization problem as a consensus problem, the ADMM can be used to solve the consensus problem in a fully parallel fashion over a computer network with a star topology. However, traditional synchronized computation does not scale well with the problem size, as the speed of the algorithm is limited by the slowest workers. This is particularly true in a heterogeneous network where the computing nodes experience different computation and communication delays. In this paper, we propose ...


Sample Approximation-Based Deflation Approaches For Chance Sinr-Constrained Joint Power And Admission Control, Ya-Feng Liu, Mingyi Hong, Enbin Song 2017 Chinese Academy of Sciences

Sample Approximation-Based Deflation Approaches For Chance Sinr-Constrained Joint Power And Admission Control, Ya-Feng Liu, Mingyi Hong, Enbin Song

Mingyi Hong

Consider the joint power and admission control (JPAC) problem for a multiuser single-input single-output (SISO) interference channel. Most existing works on JPAC assume the perfect instantaneous channel state information (CSI). In this paper, we consider the JPAC problem with the imperfect CSI, i.e., we assume that only the channel distribution information (CDI) is available. We formulate the JPAC problem into a chance (probabilistic)-constrained program, where each link's SINR outage probability is enforced to be less than or equal to a specified tolerance. To circumvent the computational difficulty of the chance SINR constraints, we propose to use the ...


Joint Source-Relay Design For Full-Duplex Mimo Af Relay Systems, Qingjiang Shi, Mingyi Hong, Xiqi Gao, Enbin Song, Yunlong Cai, Weiqiang Xu 2017 Southeast University

Joint Source-Relay Design For Full-Duplex Mimo Af Relay Systems, Qingjiang Shi, Mingyi Hong, Xiqi Gao, Enbin Song, Yunlong Cai, Weiqiang Xu

Mingyi Hong

The performance of full-duplex (FD) relay systems can be greatly impacted by the self-interference (SI) at relays. By exploiting multiple antennas, the spectral efficiency of FD relay systems can be enhanced through spatial SI mitigation. This paper studies joint source transmit beamforming and relay processing to achieve rate maximization for FD multiple-input-multiple-output (MIMO) amplify-and-forward (AF) relay systems with consideration of relay processing delay. The problem is difficult to solve mainly due to the SI constraint induced by the relay processing delay. In this paper, we first present a sufficient condition under which the relay amplification matrix has rank-one structure. Then ...


Asynchronous Distributed Admm For Large-Scale Optimization—Part Ii: Linear Convergence Analysis And Numerical Performance, Tsung-Hui Chang, Wei-Cheng Lao, Mingyi Hong, Xiangfeng Wang 2017 The Chinese University of Hong Kong

Asynchronous Distributed Admm For Large-Scale Optimization—Part Ii: Linear Convergence Analysis And Numerical Performance, Tsung-Hui Chang, Wei-Cheng Lao, Mingyi Hong, Xiangfeng Wang

Mingyi Hong

The alternating direction method of multipliers (ADMM) has been recognized as a versatile approach for solving modern large-scale machine learning and signal processing problems efficiently. When the data size and/or the problem dimension is large, a distributed version of ADMM can be used, which is capable of distributing the computation load and the data set to a network of computing nodes. Unfortunately, a direct synchronous implementation of such algorithm does not scale well with the problem size, as the algorithm speed is limited by the slowest computing nodes. To address this issue, in a companion paper, we have proposed ...


Collective Multiagent Sequential Decision Making Under Uncertainty, NGUYEN DUC THIEN, Akshat KUMAR, Hoong Chuin LAU 2017 Singapore Management University

Collective Multiagent Sequential Decision Making Under Uncertainty, Nguyen Duc Thien, Akshat Kumar, Hoong Chuin Lau

Research Collection School Of Information Systems

Multiagent sequential decision making has seen rapidprogress with formal models such as decentralized MDPsand POMDPs. However, scalability to large multiagent systemsand applicability to real world problems remain limited.To address these challenges, we study multiagent planningproblems where the collective behavior of a populationof agents affects the joint-reward and environment dynamics.Our work exploits recent advances in graphical modelsfor modeling and inference with a population of individualssuch as collective graphical models and the notion of fi-nite partial exchangeability in lifted inference. We developa collective decentralized MDP model where policies can becomputed based on counts of agents in different states. Asthe policy ...


Detecting Similar Repositories On Github, Yun ZHANG, David LO, PAVNEET SINGH KOCHHAR, Xin XIA, Quanlai LI, Jianling SUN 2017 Singapore Management University

Detecting Similar Repositories On Github, Yun Zhang, David Lo, Pavneet Singh Kochhar, Xin Xia, Quanlai Li, Jianling Sun

Research Collection School Of Information Systems

GitHub contains millions of repositories among which many are similar with one another (i.e., having similar source codes or implementing similar functionalities). Finding similar repositories on GitHub can be helpful for software engineers as it can help them reuse source code, build prototypes, identify alternative implementations, explore related projects, find projects to contribute to, and discover code theft and plagiarism. Previous studies have proposed techniques to detect similar applications by analyzing API usage patterns and software tags. However, these prior studies either only make use of a limited source of information or use information not available for projects on ...


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