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Topology for statistical modeling of petascale data

Bennett, Janine C.; Pebay, Philippe P.; Mascarenhas, Ajith A.

This document presents current technical progress and dissemination of results for the Mathematics for Analysis of Petascale Data (MAPD) project titled 'Topology for Statistical Modeling of Petascale Data', funded by the Office of Science Advanced Scientific Computing Research (ASCR) Applied Math program. Many commonly used algorithms for mathematical analysis do not scale well enough to accommodate the size or complexity of petascale data produced by computational simulations. The primary goal of this project is thus to develop new mathematical tools that address both the petascale size and uncertain nature of current data. At a high level, our approach is based on the complementary techniques of combinatorial topology and statistical modeling. In particular, we use combinatorial topology to filter out spurious data that would otherwise skew statistical modeling techniques, and we employ advanced algorithms from algebraic statistics to efficiently find globally optimal fits to statistical models. This document summarizes the technical advances we have made to date that were made possible in whole or in part by MAPD funding. These technical contributions can be divided loosely into three categories: (1) advances in the field of combinatorial topology, (2) advances in statistical modeling, and (3) new integrated topological and statistical methods.

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TYPE SAND Report YEAR 2011
OSTIDOI

Current parallel I/O limitations to scalable data analysis

Mascarenhas, Ajith A.

This report describes the limitations to parallel scalability which we have encountered when applying our otherwise optimally scalable parallel statistical analysis tool kit to large data sets distributed across the parallel file system of the current premier DOE computational facility. This report describes our study to evaluate the effect of parallel I/O on the overall scalability of a parallel data analysis pipeline using our scalable parallel statistics tool kit [PTBM11]. In this goal, we tested it using the Jaguar-pf DOE/ORNL peta-scale platform on a large combustion simulation data under a variety of process counts and domain decompositions scenarios. In this report we have recalled the foundations of the parallel statistical analysis tool kit which we have designed and implemented, with the specific double intent of reproducing typical data analysis workflows, and achieving optimal design for scalable parallel implementations. We have briefly reviewed those earlier results and publications which allow us to conclude that we have achieved both goals. However, in this report we have further established that, when used in conjuction with a state-of-the-art parallel I/O system, as can be found on the premier DOE peta-scale platform, the scaling properties of the overall analysis pipeline comprising parallel data access routines degrade rapidly. This finding is problematic and must be addressed if peta-scale data analysis is to be made scalable, or even possible. In order to attempt to address these parallel I/O limitations, we will investigate the use the Adaptable IO System (ADIOS) [LZL+10] to improve I/O performance, while maintaining flexibility for a variety of IO options, such MPI IO, POSIX IO. This system is developed at ORNL and other collaborating institutions, and is being tested extensively on Jaguar-pf. Simulation code being developed on these systems will also use ADIOS to output the data thereby making it easier for other systems, such as ours, to process that data.

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TYPE SAND Report YEAR 2011
OSTIDOI

Report on the analysis of field data relating to the reliability of solar hot water systems

Utilities are overseeing the installations of thousand of solar hot water (SHW) systems. Utility planners have begun to ask for quantitative measures of the expected lifetimes of these systems so that they can properly forecast their loads. This report, which augments a 2009 reliability analysis effort by Sandia National Laboratories (SNL), addresses this need. Additional reliability data have been collected, added to the existing database, and analyzed. The results are presented. Additionally, formal reliability theory is described, including the bathtub curve, which is the most common model to characterize the lifetime reliability character of systems, and for predicting failures in the field. Reliability theory is used to assess the SNL reliability database. This assessment shows that the database is heavily weighted with data that describe the reliability of SHW systems early in their lives, during the warranty period. But it contains few measured data to describe the ends of SHW systems lives. End-of-life data are the most critical ones to define sufficiently the reliability of SHW systems in order to answer the questions that the utilities pose. Several ideas are presented for collecting the required data, including photometric analysis of aerial photographs of installed collectors, statistical and neural network analysis of energy bills from solar homes, and the development of simple algorithms to allow conventional SHW controllers to announce system failures and record the details of the event, similar to how aircraft black box recorders perform. Some information is also presented about public expectations for the longevity of a SHW system, information that is useful in developing reliability goals.

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TYPE SAND Report YEAR 2011
OSTIDOI

Utility-scale grid-tied PV inverter reliability workshop summary report

Atcitty, Stanley A.; Granata, Jennifer E.; Quintana, Michael A.

A key to the long-term success of the photovoltaic (PV) industry is confidence in the reliability of PV systems. Inverters are the most commonly noted cause of PV system incidents triggered in the field. While not all of these incidents are reliability-related or even necessarily failures, they still result in a loss of generated power. With support from the U.S. Department of Energy's Solar Energy Technologies Program, Sandia National Laboratories organized a Utility-Scale Grid-Tied Inverter Reliability Workshop in Albuquerque, New Mexico, January 27-28, 2011. The workshop addressed the reliability of large (100-kilowatt+) grid-tied inverters and the implications when such inverters fail, evaluated inverter codes and standards, and provided discussion about opportunities to enhance inverter reliability. This report summarizes discussions and presentations from the workshop and identifies opportunities for future efforts.

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TYPE SAND Report YEAR 2011
DOIOSTI
Results 66201–66400 of 96,771
Results 66201–66400 of 96,771