TY - Generic T1 - Computing the Tree of Life: Leveraging the Power of Desktop and Service Grids T2 - Parallel and Distributed Processing Workshops and Phd Forum (IPDPSW), 2011 IEEE International Symposium on Y1 - 2011 A1 - Adam L. Bazinet A1 - Michael P. Cummings KW - (artificial KW - (mathematics) KW - analysis KW - BOINC KW - COMPUTATION KW - computational KW - computing KW - data KW - Estimation KW - evolutionary KW - GARLI KW - genetic KW - Grid KW - GRIDS KW - handling KW - heterogeneous KW - History KW - HPC KW - information KW - intelligence) KW - interface KW - interfaces KW - Internet KW - jobs KW - lattice KW - learning KW - life KW - likelihood KW - load KW - machine KW - maximum KW - method KW - model KW - molecular KW - phylogenetic KW - portal KW - Portals KW - power KW - project KW - resource KW - Science KW - sequence KW - service KW - services KW - sets KW - software KW - substantial KW - system KW - systematics KW - tree KW - TREES KW - user KW - Web AB - The trend in life sciences research, particularly in molecular evolutionary systematics, is toward larger data sets and ever-more detailed evolutionary models, which can generate substantial computational loads. Over the past several years we have developed a grid computing system aimed at providing researchers the computational power needed to complete such analyses in a timely manner. Our grid system, known as The Lattice Project, was the first to combine two models of grid computing - the service model, which mainly federates large institutional HPC resources, and the desktop model, which harnesses the power of PCs volunteered by the general public. Recently we have developed a "science portal" style web interface that makes it easier than ever for phylogenetic analyses to be completed using GARLI, a popular program that uses a maximum likelihood method to infer the evolutionary history of organisms on the basis of genetic sequence data. This paper describes our approach to scheduling thousands of GARLI jobs with diverse requirements to heterogeneous grid resources, which include volunteer computers running BOINC software. A key component of this system provides a priori GARLI runtime estimates using machine learning with random forests. JA - Parallel and Distributed Processing Workshops and Phd Forum (IPDPSW), 2011 IEEE International Symposium on ER - TY - Generic T1 - MDMap: A system for data-driven layout and exploration of molecular dynamics simulations T2 - Biological Data Visualization (BioVis), 2011 IEEE Symposium on Y1 - 2011 A1 - Patro, R. A1 - Ip, Cheuk Yiu A1 - Bista, S. A1 - Cho, S. S. A1 - Thirumalai, D. A1 - Varshney, Amitabh KW - Biology KW - biomolecular KW - computing KW - data KW - digital KW - driven KW - DYNAMICS KW - exploration KW - folding KW - graph KW - landscapes KW - Layout KW - MDMap KW - method KW - molecular KW - processes KW - simulation KW - Simulations KW - space KW - state KW - Stochastic KW - THEORY KW - time-varying KW - Trajectory KW - transition AB - Contemporary molecular dynamics simulations result in a glut of simulation data, making analysis and discovery a difficult and burdensome task. We present MDMap, a system designed to summarize long-running molecular dynamics (MD) simulations. We represent a molecular dynamics simulation as a state transition graph over a set of intermediate (stable and semi-stable) states. The transitions amongst the states together with their frequencies represent the flow of a biomolecule through the trajectory space. MDMap automatically determines potential intermediate conformations and the transitions amongst them by analyzing the conformational space explored by the MD simulation. MDMap is an automated system to visualize MD simulations as state-transition diagrams, and can replace the current tedious manual layouts of biomolecular folding landscapes with an automated tool. The layout of the representative states and the corresponding transitions among them is presented to the user as a visual synopsis of the long-running MD simulation. We compare and contrast multiple presentations of the state transition diagrams, such as conformational embedding, and spectral, hierarchical, and force-directed graph layouts. We believe this system could provide a road-map for the visualization of other stochastic time-varying simulations in a variety of different domains. JA - Biological Data Visualization (BioVis), 2011 IEEE Symposium on ER - TY - JOUR T1 - Social Snapshot: A System for Temporally Coupled Social Photography JF - Computer Graphics and Applications, IEEEComputer Graphics and Applications, IEEE Y1 - 2011 A1 - Patro, R. A1 - Ip, Cheuk Yiu A1 - Bista, S. A1 - Varshney, Amitabh KW - 3D KW - ACQUISITION KW - computing KW - coupled KW - data KW - Photography KW - reconstruction KW - sciences KW - snapshot KW - social KW - spatiotemporal KW - temporally AB - Social Snapshot actively acquires and reconstructs temporally dynamic data. The system enables spatiotemporal 3D photography using commodity devices, assisted by their auxiliary sensors and network functionality. It engages users, making them active rather than passive participants in data acquisition. VL - 31 SN - 0272-1716 ER -