Other Electrical and Computer Engineering Commons^™

Cache-Conscious Sparse Matrix Dense Matrix Multiplication On Gpus, Haoqiang Guo

LSU Doctoral Dissertations

Over the past decade, high-performance deep learning has evolved into a critical research domain, driven by the demand for efficient models and high inference throughput. Deep learning architectures have shifted from stacked convolutional layers to transformer-based models, while pruning techniques and graph-structured data have established sparse matrix–dense matrix multiplication (SpMM) as a fundamental kernel—particularly in graph neural networks (GNNs). Modern GPUs, with their massive parallelism and high-bandwidth memory, offer immense potential for accelerating these workloads. While SpMM implementations using the compressed sparse row (CSR) format remain common to avoid conversion overhead, preprocessing-based methods have recently demonstrated superior potential. In GNN …

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), …

Spam Detection Using Machine Learning And Deep Learning, Olubodunde Agboola

LSU Doctoral Dissertations

Text messages are essential these days; however, spam texts have contributed negatively to the success of this communication mode. The compromised authenticity of such messages has given rise to several security breaches. Using spam messages, malicious links have been sent to either harm the system or obtain information detrimental to the user. Spam SMS messages as well as emails have been used as media for attacks such as masquerading and smishing ( a phishing attack through text messaging), and this has threatened both the user and service providers. Therefore, given the waves of attacks, the need to identify and remove …

An Improved Earned Value Management Method Integrating Quality And Safety, Brian Briggs

LSU Doctoral Dissertations

The construction industry invests significant time and money to improve quality and safety while reducing cost and schedule impacts. The industry has a sincere desire to improve construction project management methods to improve efficiency. Historically, quality and safety underperformances result from undermanaged quality control and safety activities. The cost and schedule impacts associated with poor quality work have always had an impact on construction operations. The unprecedented challenges and uncertainties of COVID-19 highlighted the need to improve the Earned Value Management (EVM) method within construction to reflect these quality and safety activities. The central goal of this dissertation is to …

Semantics-Guided Human Motion Modeling In Virtual Reality Environment, Matthew Korban

LSU Doctoral Dissertations

Human Motion Modeling is essential in Computer Animation and Human-Computer Interaction. This dissertation studies how to enhance the speed and robustness of Human Motion Modeling in Virtual Reality (VR) environments. Specifically, we aim to design a pipeline to effectively capture and use semantic action information to guide the motion capturing from users in physical worlds and its transfer onto digital avatars in VR environments. To recognize the user's action, we first proposed a new Dynamic Directed Graph Convolutional Network (DDGCN) to model spatial and temporal features from users' skeletal representations. The DDGCN consists of several dynamic feature modeling modules to …

Image Processing Applications In Real Life: 2d Fragmented Image And Document Reassembly And Frequency Division Multiplexed Imaging, Houman Kamran Habibkhani

LSU Doctoral Dissertations

In this era of modern technology, image processing is one the most studied disciplines of signal processing and its applications can be found in every aspect of our daily life. In this work three main applications for image processing has been studied.

In chapter 1, frequency division multiplexed imaging (FDMI), a novel idea in the field of computational photography, has been introduced. Using FDMI, multiple images are captured simultaneously in a single shot and can later be extracted from the multiplexed image. This is achieved by spatially modulating the images so that they are placed at different locations in the …