Physical Sciences and Mathematics Commons^™

Improving Scalability And Usability Of Parallel Runtime Environments For High Availability And High Performance Systems, Thara Angskun

Doctoral Dissertations

The number of processors embedded in high performance computing platforms is growing daily to solve larger and more complex problems. Hence, parallel runtime environments have to support and adapt to the underlying platforms that require scalability and fault management in more and more dynamic environments. This dissertation aims to analyze, understand and improve the state of the art mechanisms for managing highly dynamic, large scale applications.

This dissertation demonstrates that the use of new scalable and fault-tolerant topologies, combined with rerouting techniques, builds parallel runtime environments, which are able to efficiently and reliably deliver sets of information to a large …

Statistical And Machine Learning Techniques Applied To Algorithm Selection For Solving Sparse Linear Systems, Erika Fuentes

Doctoral Dissertations

There are many applications and problems in science and engineering that require large-scale numerical simulations and computations. The issue of choosing an appropriate method to solve these problems is very common, however it is not a trivial one, principally because this decision is most of the times too hard for humans to make, or certain degree of expertise and knowledge in the particular discipline, or in mathematics, are required. Thus, the development of a methodology that can facilitate or automate this process and helps to understand the problem, would be of great interest and help. The proposal is to utilize …

Towards Automatic And Adaptive Optimizations Of Mpi Collective Operations, Jelena Pjesivac-Grbovic

Doctoral Dissertations

Message passing is one of the most commonly used paradigms of parallel programming. Message Passing Interface, MPI, is a standard used in scientific and high-performance computing. Collective operations are a subset of MPI standard that deals with processes synchronization, data exchange and computation among a group of processes. The collective operations are commonly used and can be application performance bottleneck. The performance of collective operations depends on many factors, some of which are the input parameters (e.g., communicator and message size); system characteristics (e.g., interconnect type); the application computation and communication pattern; and internal algorithm parameters (e.g., internal segment size). …

Automated Gene Classification Using Nonnegative Matrix Factorization On Biomedical Literature, Kevin Erich Heinrich

Doctoral Dissertations

Understanding functional gene relationships is a challenging problem for biological applications. High-throughput technologies such as DNA microarrays have inundated biologists with a wealth of information, however, processing that information remains problematic. To help with this problem, researchers have begun applying text mining techniques to the biological literature. This work extends previous work based on Latent Semantic Indexing (LSI) by examining Nonnegative Matrix Factorization (NMF). Whereas LSI incorporates the singular value decomposition (SVD) to approximate data in a dense, mixed-sign space, NMF produces a parts-based factorization that is directly interpretable. This space can, in theory, be used to augment existing ontologies …

Leaf: A Learning-Based Fault Diagnostic System For Multi-Robot Teams, Balajee Kannan

Doctoral Dissertations

The failure-prone complex operating environment of a standard multi-robot application dictates some amount of fault-tolerance to be incorporated into every system. In fact, the quality of the incorporated fault-tolerance has a direct impact on the overall performance of the system. Despite the extensive work being done in the field of multi-robot systems, there does not exist a general methodology for fault diagnosis and recovery. The objective of this research, in part, is to provide an adaptive approach that enables the robot team to autonomously detect and compensate for the wide variety of faults that could be experienced. The key feature …