Quantifying Uncertainty and Kinematics of Earthquakes (QUAKES-A) provides an analytic center framework for creating a uniform crustal deformation reference model for the active plate margin of California by fusing InSAR, topographic, and GNSS geodetic imaging data. The objective is to provide tools for sampling spatial processes ranging from local to earthquake faults to broad tectonic deformation and temporal processes ranging from immediately following earthquakes to long-term tectonics. A reference model allows exploration of a uniform model and comparison to new data.

Geodetic imaging is useful for measuring topography and motions of the Earth's surface. Geodetic imaging measurements can be used, for example, to measure earthquakes, landslides, debris flows, wildfire extent, volcanos, and anthropogenic changes such as fluid withdrawal from aquifers. Different geodetic measurements sample different parts of the spatio-temporal deformation field. Combining the measurements and analysis improves understanding of a broad range of Earth surface processes. Here we describe a concept to Quantify Uncertainty and Kinematics of Earth Systems (QUAKES) that combines radar interferometry and optical imaging into one airborne platform and the analysis system required to analyze and model the data.

GeoGateway is a web-enabled map-based system for analysis, modeling, and response of geodetic imaging products for studying earthquakes and crustal deformation. The system provides a data product search and analysis gateway for scientific discovery, field use, and disaster response. To be effective users require data overlay and visualization, interactive analysis features, and data product download. The data products of focus in this project are NASA's UAVSAR and spaceborne interferometric radar, (InSAR), geologic earthquake faults, Global Positioning System (GPS) position time series, and seismicity.

Library software implementing a parallel small-bulge multishift QR algorithm with Aggressive Early Deflation (AED) targeting distributed memory high-performance computing systems is presented. Starting from recent developments of the parallel multishift QR algorithm [Granat et al., SIAM J. Sci. Comput. 32(4), 2010], we describe a number of algorithmic and implementation improvements. These include communication avoiding algorithms via data redistribution and a refined strategy for balancing between multishift QR sweeps and AED. Guidelines concerning several important tunable algorithmic parameters are provided. As a result of these improvements, a computational bottleneck within AED has been removed in the parallel multishift QR algorithm. A performance model is established to explain the scalability behavior of the new parallel multishift QR algorithm. Numerous computational experiments confirm that our new implementation significantly outperforms previous parallel implementations of the QR algorithm.

Abstract The Virtual California simulation tool can be used to study fault and stress interaction scenarios for realistic California earthquakes and produces a large data set, which is ideally suited for statistical analysis. As with any complex system, it can produce emergent phenomena unexpected by its designers; these can be studied in order to gain insight into real world geophysical phenomena. We have developed a statistical method to analyze Virtual California data that enables us to determine the correlation relationships between the simulated fault elements. We present the results of this analysis of 40 000 years of data for 59 faults (639 elements). We focus on five specific cases that display noteworthy behavior that includes long‐range fault interactions, activation–quiescence, and complex small‐scale interactions. Copyright © 2009 John Wiley & Sons, Ltd.

Parallel ScaLAPACK-style algorithms for solving eight common standard and generalized Sylvester-type matrix equations and various sign and transposed variants are presented. All algorithms are blocked variants based on the Bartels--Stewart method and involve four major steps: reduction to triangular form, updating the right-hand side with respect to the reduction, computing the solution to the reduced triangular problem, and transforming the solution back to the original coordinate system. Novel parallel algorithms for solving reduced triangular matrix equations based on wavefront-like traversal of the right-hand side matrices are presented together with a generic scalability analysis. These algorithms are used in condition estimation and new robust parallel sep − 1 -estimators are developed. Experimental results from three parallel platforms, including results from a mixed OpenMP/MPI platform, are presented and analyzed using several performance and accuracy metrics. The analysis includes results regarding general and triangular parallel solvers as well as parallel condition estimators.

We continue our presentation of parallel ScaLAPACK-style algorithms for solving Sylvester-type matrix equations. In Part II, we present SCASY (SCAlable SYlvester solvers), a state-of-the-art HPC software library for solving 44 sign and transpose variants of eight common standard and generalized Sylvester-type matrix equations.

Abstract A parallel algorithm for reordering the eigenvalues in the real Schur form of a matrix is presented and discussed. Our novel approach adopts computational windows and delays multiple outside‐window updates until each window has been completely reordered locally. By using multiple concurrent windows the parallel algorithm has a high level of concurrency, and most work is level 3 BLAS operations. The presented algorithm is also extended to the generalized real Schur form. Experimental results for ScaLAPACK‐style Fortran 77 implementations on a Linux cluster confirm the efficiency and scalability of our algorithms in terms of more than 16 times of parallel speedup using 64 processors for large‐scale problems. Even on a single processor our implementation is demonstrated to perform significantly better compared with the state‐of‐the‐art serial implementation. Copyright © 2009 John Wiley & Sons, Ltd.

We report on a unified on-the-fly, Web services-based observation/analysis/modeling environment for crustal deformation and natural hazards research, intended as a plug-in service for early warning systems, transfer of rapid information to civilian decision makers and the media, and educational purposes. We demonstrate an early warning system for a large earthquake in southern California using the components developed under several NASA-funded projects, including real-time GPS network infrastructure, Geophysical Resources Web Services, and GPS Explorer data portal with its on-the-fly earthquake modeling software. We generate an on-the-fly earthquake fault model based on simulated real-time (dynamic and coseismic) displacements computed by the GPS network, and viewable through GPS Explorer. Our objective is to demonstrate an operational service that could be transitioned to appropriate civilian agencies in southern California.

We present a method for performing mode classification of real-time streams of GPS surface position data. Our approach has two parts: an algorithm for robust, unconstrained fitting of hidden Markov models (HMMs) to continuous-valued time series, and SensorGrid technology that manages data streams through a series of filters coupled with a publish/subscribe messaging system. The SensorGrid framework enables strong connections between data sources, the HMM time series analysis software, and users. We demonstrate our approach through a Web portal environment through which users can easily access data from the SCIGN and SOPAC GPS networks in Southern California, apply the analysis method, and view results. Ongoing real-time mode classifications of streaming GPS data are displayed in a map-based visualization interface

Recent specifications such as WS-management and WS-distributed management have stressed the importance of management of resources and services and propose methods towards querying Web services to gather the meta-data associated with these services. Management often entails system setup, querying system metadata, manipulation of system parameters at runtime and taking actions based on the system parameters to tune system performance. Real-time applications require rapid deployment of application components and demand results in real time. In this paper we present the HPSearch system which enables dynamic management of the system including both streams and Web services, and rapid deployment of applications via a scripting interface. We illustrate the functioning of the system by modeling a data streaming application and rapidly deploying the system and application components.

We describe and test a software approach to fault detection in common numerical algorithms. Such result checking or algorithm-based fault tolerance (ABFT) methods may be used, for example, to overcome single-event upsets in computational hardware or to detect errors in complex, high-efficiency implementations of the algorithms. Following earlier work, we use checksum methods to validate results returned by a numerical subroutine operating subject to unpredictable errors in data. We consider common matrix and Fourier algorithms which return results satisfying a necessary condition having a linear form; the checksum tests compliance with this condition. We discuss the theory and practice of setting numerical tolerances to separate errors caused by a fault from those inherent in finite-precision floating-point calculations. We concentrate on comprehensively defining and evaluating tests having various accuracy/computational burden tradeoffs, and we emphasize average-case algorithm behavior rather than using worst-case upper, bounds on error.

We describe and test a software approach to overcoming radiation-induced errors in spaceborne applications running on commercial off-the-shelf components. The approach uses checksum methods to validate results returned by a numerical subroutine operating subject to unpredictable errors in data. We can treat subroutines that return results satisfying a necessary condition having a linear form; the checksum tests compliance with this condition. We discuss the theory and practice of setting numerical tolerances to separate errors caused by a fault from those inherent infinite-precision numerical calculations. We test both the general effectiveness of the linear fault tolerant schemes we propose, and the correct behavior of our parallel implementation of them.