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Articles 1 - 9 of 9

Full-Text Articles in Physical Sciences and Mathematics

Parallel Processes In Hpx: Designing An Infrastructure For Adaptive Resource Management, Vinay Chandra Amatya Jan 2014

Parallel Processes In Hpx: Designing An Infrastructure For Adaptive Resource Management, Vinay Chandra Amatya

LSU Doctoral Dissertations

Advancement in cutting edge technologies have enabled better energy efficiency as well as scaling computational power for the latest High Performance Computing(HPC) systems. However, complexity, due to hybrid architectures as well as emerging classes of applications, have shown poor computational scalability using conventional execution models. Thus alternative means of computation, that addresses the bottlenecks in computation, is warranted. More precisely, dynamic adaptive resource management feature, both from systems as well as application's perspective, is essential for better computational scalability and efficiency. This research presents and expands the notion of Parallel Processes as a placeholder for procedure definitions, targeted at one …


A Persistent Storage Model For Extreme Computing, Shuangyang Yang Jan 2014

A Persistent Storage Model For Extreme Computing, Shuangyang Yang

LSU Doctoral Dissertations

The continuing technological progress resulted in a dramatic growth in aggregate computational performance of the largest supercomputing systems. Unfortunately, these advances did not translate to the required extent into accompanying I/O systems and little more in terms of architecture or effective access latency. New classes of algorithms developed for massively parallel applications, that gracefully handle the challenges of asynchrony, heavily multi-threaded distributed codes, and message-driven computation, must be matched by similar advances in I/O methods and algorithms to produce a well performing and balanced supercomputing system. This dissertation proposes PXFS, a storage model for persistent objects inspired by the ParalleX …


Efficient Indexing For Structured And Unstructured Data, Manish Madhukar Patil Jan 2014

Efficient Indexing For Structured And Unstructured Data, Manish Madhukar Patil

LSU Doctoral Dissertations

The collection of digital data is growing at an exponential rate. Data originates from wide range of data sources such as text feeds, biological sequencers, internet traffic over routers, through sensors and many other sources. To mine intelligent information from these sources, users have to query the data. Indexing techniques aim to reduce the query time by preprocessing the data. Diversity of data sources in real world makes it imperative to develop application specific indexing solutions based on the data to be queried. Data can be structured i.e., relational tables or unstructured i.e., free text. Moreover, increasingly many applications need …


Space-Efficient Data Structures For String Searching And Retrieval, Sharma Valliyil Thankachan Jan 2014

Space-Efficient Data Structures For String Searching And Retrieval, Sharma Valliyil Thankachan

LSU Doctoral Dissertations

Let D = {d_1, d_2, ...} be a collection of string documents of n characters in total, which are drawn from an alphabet set Sigma =[sigma] ={1,2,3,...sigma}. The top-k document retrieval problem is to maintain D as a data structure, such that when ever a query Q=(P, k) comes, we can report (the identifiers of) those k documents that are most relevant to the pattern P (of p characters). The relevance of a document d_r with respect to a pattern P is captured by score(P, d_r), which can be any function of the set of locations where P occurs in …


Evolving Time Surfaces And Tracking Mixing Indicators For Flow Visualization, Farid Harhad Jan 2014

Evolving Time Surfaces And Tracking Mixing Indicators For Flow Visualization, Farid Harhad

LSU Doctoral Dissertations

The complexity of large scale computational fluid dynamic simulations (CFD) demands powerful tools to investigate the numerical results. To analyze and understand these voluminous results, we need to visualize the 3D flow field. We chose to use a visualization technique called Time Surfaces. A time surface is a set of surfaces swept by an initial seed surface for a given number of timesteps. We use a front tracking approach where the points of an in initial surface are advanced in a Lagrangian fashion. To maintain a smooth time surface, our method requires surface refinement operations that either split triangle edges, …


A Study On Fairness And Latency Issues Over High Speed Networks And Data Center Networks, Lin Xue Jan 2014

A Study On Fairness And Latency Issues Over High Speed Networks And Data Center Networks, Lin Xue

LSU Doctoral Dissertations

Newly emerging computer networks, such as high speed networks and data center networks, have characteristics of high bandwidth and high burstiness which make it difficult to address issues such as fairness, queuing latency and link utilization. In this study, we first conduct extensive experimental evaluation of the performance of 10Gbps high speed networks. We found inter-protocol unfairness and larger queuing latency are two outstanding issues in high speed networks and data center networks. There have been several proposals to address fairness and latency issues at switch level via queuing schemes. These queuing schemes have been fairly successful in addressing either …


Scheduling In Transactional Memory Systems: Models, Algorithms, And Evaluations, Gokarna Sharma Jan 2014

Scheduling In Transactional Memory Systems: Models, Algorithms, And Evaluations, Gokarna Sharma

LSU Doctoral Dissertations

Transactional memory provides an alternative synchronization mechanism that removes many limitations of traditional lock-based synchronization so that concurrent program writing is easier than lock-based code in modern multicore architectures. The fundamental module in a transactional memory system is the transaction which represents a sequence of read and write operations that are performed atomically to a set of shared resources; transactions may conflict if they access the same shared resources. A transaction scheduling algorithm is used to handle these transaction conflicts and schedule appropriately the transactions. In this dissertation, we study transaction scheduling problem in several systems that differ through the …


Performance Improvement Of Distributed Computing Framework And Scientific Big Data Analysis, Praveenkumar Kondikoppa Jan 2014

Performance Improvement Of Distributed Computing Framework And Scientific Big Data Analysis, Praveenkumar Kondikoppa

LSU Doctoral Dissertations

Analysis of Big data to gain better insights has been the focus of researchers in the recent past. Traditional desktop computers or database management systems may not be suitable for efficient and timely analysis, due to the requirement of massive parallel processing. Distributed computing frameworks are being explored as a viable solution. For example, Google proposed MapReduce, which is becoming a de facto computing architecture for Big data solutions. However, scheduling in MapReduce is coarse grained and remains as a challenge for improvement. Related with MapReduce scheduler when configured over distributed clusters, we identify two issues: data locality disruption and …


Search-Based Model-Driven Loop Optimizations For Tensor Contractions, Ajay Panyala Jan 2014

Search-Based Model-Driven Loop Optimizations For Tensor Contractions, Ajay Panyala

LSU Doctoral Dissertations

Complex tensor contraction expressions arise in accurate electronic structure models in quantum chemistry, such as the coupled cluster method. The Tensor Contraction Engine (TCE) is a high-level program synthesis system that facilitates the generation of high-performance parallel programs from tensor contraction equations. We are developing a new software infrastructure for the TCE that is designed to allow experimentation with optimization algorithms for modern computing platforms, including for heterogeneous architectures employing general-purpose graphics processing units (GPGPUs). In this dissertation, we present improvements and extensions to the loop fusion optimization algorithm, which can be used with cost models, e.g., for minimizing memory …