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We present an application of hidden Markov models (HMMs) to analysis of geodetic time series in Southern California. Our model-fitting method uses a regularized version of the deterministic annealing expectation-maximization algorithm to ensure that model solutions are both robust and of high quality. Using the fitted models, we segment the daily displacement time series collected by 127 stations of the Southern California Integrated Geodetic Network (SCIGN) over a two-year period. Segmentations of the series are based on statistical changes as identified by the trained HMMs. We look for correlations in state changes across multiple stations that indicate region-wide activity. We find that although in one case a strong seismic event was associated with a spike in station correlations, in all other cases in the study, time period strong correlations were not associated with any seismic event. This indicates that the method was able to identify more subtle signals associated with aseismic events or long-range interactions between smaller events. [ABSTRACT FROM AUTHOR]

We describe the goals and initial implementation of the International Solid Earth Virtual Observatory (iSERVO). This system is built using a Web Services approach to Grid computing infrastructure and is accessed via a component-based Web portal user interface. We describe our implementations of services used by this system, including Geographical Information System (GIS)-based data grid services for accessing remote data repositories and job management services for controlling multiple execution steps. iSERVO is an example of a larger trend to build globally scalable scientific computing infrastructures using the Service Oriented Architecture approach. Adoption of this approach raises a number of research challenges in millisecond-latency message systems suitable for internet-enabled scientific applications. We review our research in these areas. [ABSTRACT FROM AUTHOR]

We are developing simulation and analysis tools in order to develop a solid Earth Science framework for understanding and studying active tectonic and earthquake processes. The goal of QuakeSim and its extension, the Solid Earth Research Virtual Observatory (SERVO), is to study the physics of earthquakes using state-of-the-art modeling, data manipulation, and pattern recognition technologies. We are developing clearly defined accessible data formats and code protocols as inputs to simulations, which are adapted to high-performance computers. The solid Earth system is extremely complex and nonlinear, resulting in computationally intensive problems with millions of unknowns. With these tools it will be possible to construct the more complex models and simulations necessary to develop hazard assessment systems critical for reducing future losses from major earthquakes. We are using Web (Grid) service technology to demonstrate the assimilation of multiple distributed data sources (a typical data grid problem) into a major parallel high-performance computing earthquake forecasting code. Such a linkage of Geoinformatics with Geocomplexity demonstrates the value of the Solid Earth Research Virtual Observatory (SERVO) Grid concept, and advances Grid technology by building the first real-time large-scale data assimilation grid. [ABSTRACT FROM AUTHOR]

We discuss parallel algorithms for solving eight common standard and generalized triangular Sylvester-type matrix equation. Our parallel algorithms are based on explicit blocking, 2D block-cyclic data distribution of the matrices and wavefront-like traversal of the right hand side matrices while solving small-sized matrix equations at different nodes and updating the rest of the right hand side using level 3 operations. We apply the triangular solvers in condition estimation, developing parallel sep− 1-estimators. Some experimental results are presented. [ABSTRACT FROM AUTHOR]

Recent ScaLAPACK-style implementations of the Bartels-Stewart method and the iterative matrix-sign-function-based method for solving continuous-time Sylvester matrix equations are evaluated with respect to generality of use, execution time and accuracy of computed results. The test problems include well-conditioned as well as ill-conditioned Sylvester equations. A method is considered more general if it can effectively solve a larger set of problems. Ill-conditioning is measured with respect to the separation of the two matrices in the Sylvester operator. Experiments carried out on two different distributed memory machines show that the parallel explicitly blocked Bartels-Stewart algorithm can solve more general problems and delivers far more accuracy for ill-conditioned problems. It is also up to four times faster for large enough problems on the most balanced parallel platform (IBM SP), while the parallel iterative algorithm is almost always the fastest of the two on the less balanced platform (HPC2N Linux Super Cluster). Keywords: Sylvester matrix equation, continuous-time, Bartels-Stewart method, explicit blocking, GEMM-based, level 3 BLAS, matrix sign function, c-stable matrices, Newton iteration, ScaLAPACK, PSLICOT. [ABSTRACT FROM AUTHOR]