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Full-Text Articles in Engineering
Extracting The Structure And Conformations Of Biological Entities From Large Datasets, Ali Dashti
Extracting The Structure And Conformations Of Biological Entities From Large Datasets, Ali Dashti
Theses and Dissertations
In biology, structure determines function, which often proceeds via changes in conformation. Efficient means for determining structure exist, but mapping conformations continue to present a serious challenge. Single-particles approaches, such as cryogenic electron microscopy (cryo-EM) and emerging "diffract & destroy" X-ray techniques are, in principle, ideally positioned to overcome these challenges. But the algorithmic ability to extract information from large heterogeneous datasets consisting of "unsorted" snapshots - each emanating from an unknown orientation of an object in an unknown conformation - remains elusive.
It is the objective of this thesis to describe and validate a powerful suite of manifold-based algorithms …
Efficient Computation Of K-Nearest Neighbor Graphs For Large High-Dimensional Data Sets On Gpu Clusters, Ali Dashti
Efficient Computation Of K-Nearest Neighbor Graphs For Large High-Dimensional Data Sets On Gpu Clusters, Ali Dashti
Theses and Dissertations
The k-Nearest Neighbor Graph (k-NNG) and the related k-Nearest Neighbor (k-NN) methods have a wide variety of applications in areas such as bioinformatics, machine learning, data mining, clustering analysis, and pattern recognition. Our application of interest is manifold embedding. Due to the large dimensionality of the input data (<15k), spatial subdivision based techniques such OBBs, k-d tree, BSP etc., are not viable. The only alternative is the brute-force search, which has two distinct parts. The first finds distances between individual vectors in the corpus based on a pre-defined metric. Given the distance matrix, the second step selects k nearest neighbors for each member of the query data set.
This thesis presents the development and implementation of a distributed exact k-Nearest Neighbor Graph (k-NNG) construction method. The proposed method uses Graphics Processing Units (GPUs) and exploits multiple levels of parallelism for distributed computational systems using GPUs. It is scalable for different cluster sizes, with each compute node in the cluster …
Advanced Optimization Techniques For Monte Carlo Simulation On Graphics Processing Units, Eyad Hailat
Advanced Optimization Techniques For Monte Carlo Simulation On Graphics Processing Units, Eyad Hailat
Wayne State University Dissertations
The objective of this work is to design and implement a self-adaptive parallel GPU optimized Monte Carlo algorithm for the simulation of adsorption in porous materials. We focus on Nvidia's GPUs and CUDA's Fermi architecture specifically. The resulting package supports the different ensemble methods for the Monte Carlo simulation, which will allow for the simulation of multi-component adsorption in porous solids. Such an algorithm will have broad applications to the development of novel porous materials for the sequestration of CO2 and the filtration of toxic industrial chemicals.
The primary objective of this work is the release of a massively parallel …
Efficient, Scalable, Parallel, Matrix-Matrix Multiplication, Enrique Portillo
Efficient, Scalable, Parallel, Matrix-Matrix Multiplication, Enrique Portillo
Open Access Theses & Dissertations
For the past decade, power/energy consumption has become a limiting factor for large-scale and embedded High Performance Computing (HPC) systems. This is especially true for systems that include accelerators, e.g., high-end computing devices, such as Graphics Processing Units (GPUs), with terascale computing capabilities and high power draws that greatly surpass that of multi-core CPUs. Accordingly, improving the node-level power/energy efficiency of an application can have a direct and positive impact on both classes of HPC systems.
The research reported in this thesis explores the use of software techniques to enhance the execution-time and power-consumption performance of applications executed on a …