Physical Sciences and Mathematics Commons^™

Compilation Optimizations To Enhance Resilience Of Big Data Programs And Quantum Processors, Travis D. Lecompte

LSU Doctoral Dissertations

Modern computers can experience a variety of transient errors due to the surrounding environment, known as soft faults. Although the frequency of these faults is low enough to not be noticeable on personal computers, they become a considerable concern during large-scale distributed computations or systems in more vulnerable environments like satellites. These faults occur as a bit flip of some value in a register, operation, or memory during execution. They surface as either program crashes, hangs, or silent data corruption (SDC), each of which can waste time, money, and resources. Hardware methods, such as shielding or error correcting memory (ECM), …

Computational Imaging For Shape Understanding, Yuqi Ding

LSU Doctoral Dissertations

Geometry is the essential property of real-world scenes. Understanding the shape of the object is critical to many computer vision applications. In this dissertation, we explore using computational imaging approaches to recover the geometry of real-world scenes. Computational imaging is an emerging technique that uses the co-designs of image hardware and computational software to expand the capacity of traditional cameras. To tackle face recognition in the uncontrolled environment, we study 2D color image and 3D shape to deal with body movement and self-occlusion. Especially, we use multiple RGB-D cameras to fuse the varying pose and register the front face in …

Scheduling Many-Task Computing Applications For A Hybrid Cloud, Shifat Perveen Mithila

LSU Doctoral Dissertations

A centralized scheduler can become a bottleneck for placing the tasks of a many-task application on heterogeneous cloud resources. Previously, it was demonstrated that a decentralized vector scheduling approach based on performance measurements can be used successfully for this task placement scenario. In this dissertation, we extend this approach to task placement based on latency measurements. Each node collects performance metrics from its neighbors on an overlay graph, measures the communication latency, and then makes local decisions on where to move tasks. We present a decentralized and a centralized algorithm for configuring the overlay graph based on latency measurements and …

Optimizing The Performance Of Parallel And Concurrent Applications Based On Asynchronous Many-Task Runtimes, Weile Wei

LSU Doctoral Dissertations

Nowadays, High-performance Computing (HPC) scientific applications often face per- formance challenges when running on heterogeneous supercomputers, so do scalability, portability, and efficiency issues. For years, supercomputer architectures have been rapidly changing and becoming more complex, and this challenge will become even more com- plicated as we enter the exascale era, where computers will exceed one quintillion cal- culations per second. Software adaption and optimization are needed to address these challenges. Asynchronous many-task (AMT) systems show promise against the exascale challenge as they combine advantages of multi-core architectures with light-weight threads, asynchronous executions, smart scheduling, and portability across diverse architectures.

In …

From Equal-Mass To Extreme-Mass-Ratio Binary Inspirals: Simulation Tools For Next Generation Gravitational Wave Detectors, Samuel Douglas Cupp

LSU Doctoral Dissertations

Current numerical codes can successfully evolve similar-mass binary black holes systems, and these numerical waveforms contributed to the success of the LIGO Collaboration's detection of gravitational waves. LIGO requires high resolution numerical waveforms for detection and parameter estimation of the source. Great effort was expended over several decades to produce the numerical methods used today. However, future detectors will require further improvements to numerical techniques to take full advantage of their detection capabilities. For example, the Laser Interferometer Space Antenna (LISA) will require higher resolution simulations of similar-mass-ratio systems than LIGO. LISA will also be able to detect extreme-mass-ratio inspiral …

Practical Considerations And Applications For Autonomous Robot Swarms, Rory Alan Hector

LSU Doctoral Dissertations

In recent years, the study of autonomous entities such as unmanned vehicles has begun to revolutionize both military and civilian devices. One important research focus of autonomous entities has been coordination problems for autonomous robot swarms. Traditionally, robot models are used for algorithms that account for the minimum specifications needed to operate the swarm. However, these theoretical models also gloss over important practical details. Some of these details, such as time, have been considered before (as epochs of execution). In this dissertation, we examine these details in the context of several problems and introduce new performance measures to capture practical …

Performance Analysis And Improvement For Scalable And Distributed Applications Based On Asynchronous Many-Task Systems, Nanmiao Wu

LSU Doctoral Dissertations

As the complexity of recent and future large-scale data and exascale systems architectures grows, so do productivity, portability, software scalability, and efficient utilization of system resources challenges presented to both industry and the research community. Software solutions and applications are expected to scale in performance on such complex systems. Asynchronous many-task (AMT) systems, taking advantage of multi-core architectures with light-weight threads, asynchronous executions, and smart scheduling, are showing promise in addressing these challenges.

In this research, we implement several scalable and distributed applications based on HPX, an exemplar AMT runtime system. First, a distributed HPX implementation for a parameterized benchmark …

Digital Discrimination In The Sharing Economy: Evidence, Policy, And Feature Analysis, Miroslav Tushev

LSU Doctoral Dissertations

Applications (apps) of the Digital Sharing Economy (DSE), such as Uber, Airbnb, and TaskRabbit, have become a main facilitator of economic growth and shared prosperity in modern-day societies. However, recent research has revealed that the participation of minority groups in DSE activities is often hindered by different forms of bias and discrimination. Evidence of such behavior has been documented across almost all domains of DSE, including ridesharing, lodging, and freelancing. However, little is known about the under- lying design decisions of DSE systems which allow certain demographics of the market to gain unfair advantage over others. To bridge this knowledge …

Using Memory Forensics To Analyze Programming Language Runtimes, Modhuparna Manna

LSU Doctoral Dissertations

The continued increase in the use of computer systems in recent times has led to a significant rise in the capabilities of malware and attacker toolkits that target different operating systems and their users. Over the last several years, cybersecurity threat reports have documented numerous instances of users that were targeted by governments, intelligence agencies, and criminal groups, and the result was that the victims ended up having highly sophisticated malware installed on their systems. Unfortunately, the rise of these threats has not been met with equal research and development of defensive mechanisms that can detect and analyze such malware. …