Open Access. Powered by Scholars. Published by Universities.®
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Institution
- Publication
- Publication Type
Articles 1 - 6 of 6
Full-Text Articles in Physical Sciences and Mathematics
Scalable Algorithms And Hybrid Parallelization Strategies For Multivariate Integration With Paradapt And Cuda, Omofolakunmi Elizabeth Olagbemi
Scalable Algorithms And Hybrid Parallelization Strategies For Multivariate Integration With Paradapt And Cuda, Omofolakunmi Elizabeth Olagbemi
Dissertations
The evaluation of numerical integrals finds applications in fields such as High Energy Physics, Bayesian Statistics, Stochastic Geometry, Molecular Modeling and Medical Physics. The erratic behavior of some integrands due to singularities, peaks, or ridges in the integration region suggests the need for reliable algorithms and software that not only provide an estimation of the integral with a level of accuracy acceptable to the user, but also perform this task in a timely manner. We developed ParAdapt, a numerical integration software based on a classic global adaptive strategy, which employs Graphical Processing Units (GPUs) in providing integral evaluations. Specifically, ParAdapt …
An Accelerated Hierarchical Approach For Object Shape Extraction And Recognition, Mahmoud K. Quweider, Bassam Arshad, Hansheng Lei, Liyu Zhang, Fitratullah Khan
An Accelerated Hierarchical Approach For Object Shape Extraction And Recognition, Mahmoud K. Quweider, Bassam Arshad, Hansheng Lei, Liyu Zhang, Fitratullah Khan
Computer Science Faculty Publications and Presentations
We present a novel automatic supervised object recognition algorithm based on a scale and rotation invariant Fourier descriptors algorithm. The algorithm is hierarchical in nature to capture the inherent intra-contour spatial relationships between the parent and child contours of an object. A set of distance metrics are introduced to go along with the hierarchical model. To test the algorithm, a diverse database of shapes is created and used to train standard classification algorithms, for shape-labeling. The implemented algorithm takes advantage of the multi-threaded architecture and GPU efficient image-processing functions present in OpenCV wherever possible, speeding up the running time and …
Efficient Gpu Tree Walks For Effective Distributed N-Body Simulations, Jianqiao Liu, Michael Robson, Thomas Quinn, Milind Kulkarni
Efficient Gpu Tree Walks For Effective Distributed N-Body Simulations, Jianqiao Liu, Michael Robson, Thomas Quinn, Milind Kulkarni
Computer Science: Faculty Publications
N-body problems, such as simulating the motion of stars in a galaxy, are popularly solved using tree codes like Barnes-Hut. ChaNGa is a best-of-breed n-body platform that uses an asymptotically-efficient tree traversal strategy known as a dual-tree walk to quickly determine which bodies need to interact with each other to provide an accurate simulation result. However, this strategy does not work well on GPUs, due to the highly-irregular nature of the dual-tree algorithm. On GPUs, ChaNGa uses a hybrid strategy where the CPU performs the tree walk to determine which bodies interact while the GPU performs the force computation. In …
High-Performance Computing Frameworks For Large-Scale Genome Assembly, Sayan Goswami
High-Performance Computing Frameworks For Large-Scale Genome Assembly, Sayan Goswami
LSU Doctoral Dissertations
Genome sequencing technology has witnessed tremendous progress in terms of throughput and cost per base pair, resulting in an explosion in the size of data. Typical de Bruijn graph-based assembly tools demand a lot of processing power and memory and cannot assemble big datasets unless running on a scaled-up server with terabytes of RAMs or scaled-out cluster with several dozens of nodes. In the first part of this work, we present a distributed next-generation sequence (NGS) assembler called Lazer, that achieves both scalability and memory efficiency by using partitioned de Bruijn graphs. By enhancing the memory-to-disk swapping and reducing the …
Haptics-Enabled, Gpu Augmented Surgical Simulation Platform For Glenoid Reaming, Vlad Popa
Haptics-Enabled, Gpu Augmented Surgical Simulation Platform For Glenoid Reaming, Vlad Popa
Electronic Thesis and Dissertation Repository
Surgical simulators are technological platforms that provide virtual substitutes to the current cadaver-based medical training models. The advantages of exposure to these devices have been thoroughly studied, with enhanced surgical proficiency being one of the assets gained after extensive use. While simulators have already penetrated numerous medical domains, the field of orthopedics remains stagnant despite a demand for the ability to practice uncommon surgeries, such as total shoulder arthroplasty (TSA). Here we extrapolate the algorithms of an inhouse software engine revolving around glenoid reaming, a critical step of TSA. The project’s purpose is to provide efficient techniques for future simulators, …
High-Performance Reductive Strategies For Big Data From Lc-Ms/Ms Proteomics, Muaaz Gul Awan
High-Performance Reductive Strategies For Big Data From Lc-Ms/Ms Proteomics, Muaaz Gul Awan
Dissertations
Mass Spectrometry (MS)-based proteomics utilizes high performance liquid chromatography in tandem with high-throughput mass spectrometers. These experiments can produce MS data sets with astonishing speed and volume that can easily reach peta-scale level, creating storage and computational problems for large-scale systems biology studies. Each spectrum output by a mass spectrometer may consist of thousands of peaks, which must all be processed to deduce the corresponding peptide. However, only a small percentage of peaks in a spectrum are useful for further processing, as most of the peaks are either noise or are not useful. Our experiments have shown that 90 to …