A uniform asteroseismic analysis of 22 solar-type stars observed by Kepler

Asteroseismology with the Kepler space telescope is providing not only an improved characterization of exoplanets and their host stars, but also a new window on stellar structure and evolution for the large sample of solar-type stars in the field. We perform a uniform analysis of 22 of the brightest asteroseismic targets with the highest signal-to-noise ratio observed for 1 month each during the first year of the mission, and we quantify the precision and relative accuracy of asteroseismic determinations of the stellar radius, mass, and age that are possible using various methods. We present the properties of each star in the sample derived from an automated analysis of the individual oscillation frequencies and other observational constraints using the Asteroseismic Modeling Portal (AMP), and we compare them to the results of model-grid-based methods that fit the global oscillation properties. We find that fitting the individual frequencies typically yields asteroseismic radii and masses to \sim1% precision, and ages to \sim2.5% precision (respectively 2, 5, and 8 times better than fitting the global oscillation properties). The absolute level of agreement between the results from different approaches is also encouraging, with model-grid-based methods yielding slightly smaller estimates of the radius and mass and slightly older values for the stellar age relative to AMP, which computes a large number of dedicated models for each star. The sample of targets for which this type of analysis is possible will grow as longer data sets are obtained during the remainder of the mission.Comment: 13 pages, 5 figures in the main text, 22 figures in Appendix. Accepted for publication in Ap

2004: Comparing Linux clusters for the Community Climate System Model. Fifth Int

Abstract. In this paper, we examine the performance of two components of the NCAR Community Climate System Model (CCSM) executing on clusters with a variety of microprocessor architectures and interconnects. Specifically, we examine the execution time and scalability of the Community Atmospheric Model (CAM) and the Parallel Ocean Program (POP) on Linux clusters with Intel Xeon and AMD Opteron processors, using Dolphin, Myrinet, and Infiniband interconnects, and compare the performance of the cluster systems to an SGI Altix and an IBM p690 supercomputer. Of the architectures examined, clusters constructed using AMD Opteron processors generally demonstrate the best performance, outperforming Xeon clusters and occasionally an IBM p690 supercomputer in simulated years per day.

Grid-BGC: A Grid-Enabled Terrestrial Carbon Cycle Modeling System, Euro-Par 2005

Abstract. Grid-BGC is a Grid-enabled terrestrial biogeochemical cycle simulator collaboratively developed by the National Center for Atmospheric Research (NCAR) and the University of Colorado (CU) with funding from NASA. The primary objective of the project is to utilize Globus Grid technology to integrate inexpensive commodity cluster computational resources at CU with the mass storage system at NCAR while hiding the logistics of data transfer and job submission from the scientists. We describe a typical process for simulating the terrestrial carbon cycle, present our solution architecture and software design, and describe our implementation experiences with Grid technology on our systems. By design the Grid-BGC software framework is extensible in that it can utilize other grid-accessible computational resources and can be readily applied to other climate simulation problems which have similar workflows. Overall, this project demonstrates an end-to-end system which leverages Grid technologies to harness distributed resources across organizational boundaries to achieve a cost-effective solution to a computeintensive problem.

Experiences from Simulating the Global Carbon Cycle in a Grid Computing Environment, The Fourteenth Global Grid Forum (GGF 14),Chicago

Abstract. We discuss our software development experiences with Grid-BGC, a gridenabled terrestrial carbon cycle modeling environment. Grid-BGC leverages grid computing technologies to create a secure, reliable and easy to use distributed computational environment for climate modeling. The goal is to develop a system which insulates the scientists from tedious configuration details thereby increasing scientific productivity. This project is part of a collaborative effort between th