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Articles 1 - 14 of 14
Full-Text Articles in Physical Sciences and Mathematics
Unsupervised Semantic Classification Methods, John Gilmer
Unsupervised Semantic Classification Methods, John Gilmer
Honors Theses
No abstract provided.
A Partial Order On Classical And Quantum States, Arka Bandyopadhyay
A Partial Order On Classical And Quantum States, Arka Bandyopadhyay
LSU Master's Theses
In this work we extend the work done by Bob Coecke and Keye Martin in their paper “Partial Order on Classical States and Quantum States (2003)”. We review basic notions involving elementary domain theory, the set of probability measures on a finite set {a1, a2, ..., an}, which we identify with the standard (n-1)-simplex ∆n and Shannon Entropy. We consider partial orders on ∆n, which have the Entropy Reversal Property (ERP) : elements lower in the order have higher (Shannon) entropy or equivalently less information . The ERP property is important because of its applications in quantum information theory. We …
Cognitive Radio Network With A Distributed Control Channel And Quality-Of-Service Solution, Urban Terrell Wiggins
Cognitive Radio Network With A Distributed Control Channel And Quality-Of-Service Solution, Urban Terrell Wiggins
LSU Doctoral Dissertations
The proliferation of wireless access and applications to the Internet and the advent of a myriad of highly evolved portable communication devices; creates the need for an efficiently utilized radio spectrum. This is paramount in the licensed and unlicensed radio frequency bands, that spawn an exponential growth in Dynamic Spectrum Access (DSA) research, Cognitive Radio (CR) and Cognitive Radio Networks (CRN) research. DSA research has given way to the paradigm shift toward CR with its dynamic changes in transmission schemas. This paradigm shift from a fixed and centralized frequency spectrum environment has morphed into a dynamic and decentralized one. CR …
Quality Of Service Based Data-Aware Scheduling, Archit Kulshrestha
Quality Of Service Based Data-Aware Scheduling, Archit Kulshrestha
LSU Doctoral Dissertations
Distributed supercomputers have been widely used for solving complex computational problems and modeling complex phenomena such as black holes, the environment, supply-chain economics, etc. In this work we analyze the use of these distributed supercomputers for time sensitive data-driven applications. We present the scheduling challenges involved in running deadline sensitive applications on shared distributed supercomputers running large parallel jobs and introduce a ``data-aware'' scheduling paradigm that overcomes these challenges by making use of Quality of Service classes for running applications on shared resources. We evaluate the new data-aware scheduling paradigm using an event-driven hurricane simulation framework which attempts to run …
Advanced Semantics For Accelerated Graph Processing, Dylan Thomas Stark
Advanced Semantics For Accelerated Graph Processing, Dylan Thomas Stark
LSU Doctoral Dissertations
Large-scale graph applications are of great national, commercial, and societal importance, with direct use in fields such as counter-intelligence, proteomics, and data mining. Unfortunately, graph-based problems exhibit certain basic characteristics that make them a poor match for conventional computing systems in terms of structure, scale, and semantics. Graph processing kernels emphasize sparse data structures and computations with irregular memory access patterns that destroy the temporal and spatial locality upon which modern processors rely for performance. Furthermore, applications in this area utilize large data sets, and have been shown to be more data intensive than typical floating-point applications, two properties that …
Sensor-Based Autonomous Pipeline Monitoring Robotic System, Jong-Hoon Kim
Sensor-Based Autonomous Pipeline Monitoring Robotic System, Jong-Hoon Kim
LSU Doctoral Dissertations
The field of robotics applications continues to advance. This dissertation addresses the computational challenges of robotic applications and translations of actions using sensors. One of the most challenging fields for robotics applications is pipeline-based applications which have become an indispensable part of life. Proactive monitoring and frequent inspections are critical in maintaining pipeline health. However, these tasks are highly expensive using traditional maintenance systems, knowing that pipeline systems can be largely deployed in an inaccessible and hazardous environment. Thus, we propose a novel cost effective, scalable, customizable, and autonomous sensor-based robotic system, called SPRAM System (Sensor-based Autonomous Pipeline Monitoring Robotic …
Efficient Replica-Exchange Across Distributed Production Infrastructure, Abhinav S. Thota
Efficient Replica-Exchange Across Distributed Production Infrastructure, Abhinav S. Thota
LSU Master's Theses
Replica-Exchange (RE) methods represent a class of algorithms that involve a large number of loosely-coupled ensembles and are used to understand physical phenomena -- ranging from protein folding dynamics to binding affinity calculations. We develop a framework for RE that supports different replica pairing and coordination mechanisms, that can use a wide range of production cyberinfrastructure concurrently. Additionally, our framework uses a flexible pilot-job implementation, which enables effective resource allocation for multiple replicas. We characterize the performance of two different RE algorithms - synchronous and asynchronous - at unprecedented scales on production distributed infrastructure (Teragrid and LONI). The synchronous RE …
An Intelligent Othello Player Combining Machine Learning And Game Specific Heuristics, Kevin Anthony Cherry
An Intelligent Othello Player Combining Machine Learning And Game Specific Heuristics, Kevin Anthony Cherry
LSU Master's Theses
Artificial intelligence applications in board games have been around as early as the 1950's, and computer programs have been developed for games including Checkers, Chess, and Go with varying results. Although general game-tree search algorithms have been designed to work on games meeting certain requirements (e.g. zero-sum, two-player, perfect or imperfect information, etc.), the best results, however, come from combining these with specific knowledge of game strategies. In this MS thesis, we present an intelligent Othello game player that combines game-specific heuristics with machine learning techniques in move selection. Five game specific heuristics, namely corner detection, killer move detection, blocking, …
Extreme Scale Parallel Nbody Algorithm With Event Driven Constraint Based Execution Model, Chirag Dekate
Extreme Scale Parallel Nbody Algorithm With Event Driven Constraint Based Execution Model, Chirag Dekate
LSU Doctoral Dissertations
Traditional scientific applications such as Computational Fluid Dynamics, Partial Differential Equations based numerical methods (like Finite Difference Methods, Finite Element Methods) achieve sufficient efficiency on state of the art high performance computing systems and have been widely studied / implemented using conventional programming models. For emerging application domains such as Graph applications scalability and efficiency is significantly constrained by the conventional systems and their supporting programming models. Furthermore technology trends like multicore, manycore, heterogeneous system architectures are introducing new challenges and possibilities. Emerging technologies are requiring a rethinking of approaches to more effectively expose the underlying parallelism to the applications …
Oblivious Buy-At-Bulk Network Design Algorithms, Srivathsan Srinivasagopalan
Oblivious Buy-At-Bulk Network Design Algorithms, Srivathsan Srinivasagopalan
LSU Doctoral Dissertations
Large-scale networks such as the Internet has emerged as arguably the most complex distributed communication network system. The mere size of such networks and all the various applications that run on it brings a large variety of challenging problems. Similar problems lie in any network - transportation, logistics, oil/gas pipeline etc where efficient paths are needed to route the flow of demands. This dissertation studies the computation of efficient paths from the demand sources to their respective destination(s). We consider the buy-at-bulk network design problem in which we wish to compute efficient paths for carrying demands from a set of …
An Evaluation Of Synchronization Loss Rate Calculations On High Speed Networks, Aaron Tureau
An Evaluation Of Synchronization Loss Rate Calculations On High Speed Networks, Aaron Tureau
LSU Master's Theses
This paper is broken down into two parts:(1) discussion of current formulas that are used to calculate synchronized loss rates among concurrent TCP flows with the results of those equations on flows running through a bottleneck on a high speed emulated network and (2)steps to create revised forms of these equations that are more accurate and give a more reasonable estimation without having the shortcomings of the current equations. This paper brings to light three equations that were previously proposed and were used in published research projects along with their strengths and shortcomings. Through the study of these equations a …
Parallel Surrogate Detection In Large-Scale Simulations, Lei Jiang
Parallel Surrogate Detection In Large-Scale Simulations, Lei Jiang
LSU Master's Theses
Simulation has become a useful approach in scientific computing and engineering for its ability to model real natural or human systems. In particular, for complex systems such as hurricanes, wildfire disasters, and real-time road traffic, simulation methods are able to provide researchers, engineers and decision makers predicted values in order to help them to take appropriate actions. For large-scale problems, the simulations usually take a lot of time on supercomputers, thus making real-time predictions more difficult. Approximation models that mimic the behavior of simulation models but are computationally cheaper, namely "surrogate models", are desired in such scenarios. In the thesis, …
The Design Of A Computer System To Determine The Causes Of Edema Using Magnetic Resonance Spectroscopy, Carl Allen Fink
The Design Of A Computer System To Determine The Causes Of Edema Using Magnetic Resonance Spectroscopy, Carl Allen Fink
LSU Master's Theses
Diabetes is a growing problem in the U.S.A., closely linked to the current obesity epidemic. Two common complications of diabetes, osteomyelitis of the foot, and Charcot's joint, are impossible to differentiate via traditional Magnetic Resonance Imaging. The background of Magnetic Resonance Spectroscopy, which transforms the time-domain MRI signal into the frequency domain spectrum, is explored, and its use to aid in this differentiation is proposed. Artificial Neural Networks can be employed to evaluate the MRS data and to automate the process.
Data-Aware Workflow Scheduling In Heterogeneous Distributed Systems, Dengpan Yin
Data-Aware Workflow Scheduling In Heterogeneous Distributed Systems, Dengpan Yin
LSU Doctoral Dissertations
Data transferring in scientific workflows gradually attracts more attention due to large amounts of data generated by complex scientific workflows will significantly increase the turnaround time of the whole workflow. It is almost impossible to make an optimal or approximate optimal scheduling for the end-to-end workflow without considering the intermediate data movement. In order to reduce the complexity of the workflow-scheduling problem, most researches done so far are constrained by many unrealistic assumptions, which result in non-optimal scheduling in practice. A constraint imposed by most researchers in their algorithms is that a computation site can only start the execution of …