Molecular dynamics simulations of complex systems including HIV-1 protease

Advances in supercomputer architectures have resulted in a situation where many scienti�fic codes are used on systems whose performance characteristics di�ffer considerably from the platform they were developed and optimised for. This is particularly apparent in the realm of Grid computing, where new technologies such as MPIg allow researchers to connect geographically disparate resources together into virtual parallel machines. Finding ways to exploit these new resources efficiently is necessary both to extract the maximum bene�fit from them, and to provide the enticing possibility of enabling new science. In this thesis, an existing general purpose molecular dynamics code (LAMMPS) is extended to allow it to perform more efficiently in a geographically distributed Grid environment showing considerable performance gains as a result. The technique of replica exchange molecular dynamics is discussed along with its applicability to the Grid model and its bene�fits with respect to increasing sampling of configurational space. The dynamics of two sub-structures of the HIV-1 protease (known as the flaps) are investigated using replica exchange molecular dynamics in LAMMPS showing considerable movement that would have been difficult to investigate by traditional methods. To complement this, a study was carried out investigating the use of computational tools to calculate binding affinity between HIV-1 protease mutants and the drug lopinavir in comparison with results derived experimentally by other research groups. The results demonstrate some promise for computational methods in helping to determine the most eff�ective course of treatment for patients in the future

Acquisition of a High-Speed, High Capacity Storage System to Support Scientific Computing: The Data Capacitor Final Report

Final report to the National Science Foundation on ACI-0521433.National Science Foundatio

I-Light Symposium 2005 Proceedings

I-Light was made possible by a special appropriation by the State of Indiana. The research described at the I-Light Symposium has been supported by numerous grants from several sources. Any opinions, findings and conclusions, or recommendations expressed in the 2005 I-Light Symposium Proceedings are those of the researchers and authors and do not necessarily reflect the views of the granting agencies.Indiana University Office of the Vice President for Research and Information Technology, Purdue University Office of the Vice President for Information Technology and CI

Large-scale lattice Boltzmann simulations of complex fluids: advances through the advent of computational grids

During the last two years the RealityGrid project has allowed us to be one of the few scientific groups involved in the development of computational grids. Since smoothly working production grids are not yet available, we have been able to substantially influence the direction of software development and grid deployment within the project. In this paper we review our results from large scale three-dimensional lattice Boltzmann simulations performed over the last two years. We describe how the proactive use of computational steering and advanced job migration and visualization techniques enabled us to do our scientific work more efficiently. The projects reported on in this paper are studies of complex fluid flows under shear or in porous media, as well as large-scale parameter searches, and studies of the self-organisation of liquid cubic mesophases. Movies are available at http://www.ica1.uni-stuttgart.de/~jens/pub/05/05-PhilTransReview.htmlComment: 18 pages, 9 figures, 4 movies available, accepted for publication in Phil. Trans. R. Soc. London Series

Distributed computing practice for large-scale science and engineering applications

It is generally accepted that the ability to develop large-scale distributed applications has lagged seriously behind other developments in cyberinfrastructure. In this paper, we provide insight into how such applications have been developed and an understanding of why developing applications for distributed infrastructure is hard. Our approach is unique in the sense that it is centered around half a dozen existing scientific applications; we posit that these scientific applications are representative of the characteristics, requirements, as well as the challenges of the bulk of current distributed applications on production cyberinfrastructure (such as the US TeraGrid). We provide a novel and comprehensive analysis of such distributed scientific applications. Specifically, we survey existing models and methods for large-scale distributed applications and identify commonalities, recurring structures, patterns and abstractions. We find that there are many ad hoc solutions employed to develop and execute distributed applications, which result in a lack of generality and the inability of distributed applications to be extensible and independent of infrastructure details. In our analysis, we introduce the notion of application vectors: a novel way of understanding the structure of distributed applications. Important contributions of this paper include identifying patterns that are derived from a wide range of real distributed applications, as well as an integrated approach to analyzing applications, programming systems and patterns, resulting in the ability to provide a critical assessment of the current practice of developing, deploying and executing distributed applications. Gaps and omissions in the state of the art are identified, and directions for future research are outlined

Deploying and Maintaining a Campus Grid at Clemson University

Many institutions have all the tools needed to create a local grid that aggregates commodity compute resources into an accessible grid service, while simultaneously maintaining user satisfaction and system security. In this thesis, the author presents a three-tiered strategy used at Clemson University to deploy and maintain a grid infrastructure by making resources available to both local and federated remote users for scientific research. Using this approach virtually no compute cycles are wasted. Usage trends and power consumption statistics collected from the Clemson campus grid are used as a reference for best-practices. The loosely-coupled components that comprise the campus grid work together to form a highly cohesive infrastructure that not only meets the computing needs of local users, but also helps to fill the needs of the scientific community at large. Experience gained from the deployment and management of this system may be adapted to other grid sites, allowing for the development of campus-wide, grid-connected cyberinfrastructures

Enabling technology for non-rigid registration during image-guided neurosurgery

In the context of image processing, non-rigid registration is an operation that attempts to align two or more images using spatially varying transformations. Non-rigid registration finds application in medical image processing to account for the deformations in the soft tissues of the imaged organs. During image-guided neurosurgery, non-rigid registration has the potential to assist in locating critical brain structures and improve identification of the tumor boundary. Robust non-rigid registration methods combine estimation of tissue displacement based on image intensities with the spatial regularization using biomechanical models of brain deformation. In practice, the use of such registration methods during neurosurgery is complicated by a number of issues: construction of the biomechanical model used in the registration from the image data, high computational demands of the application, and difficulties in assessing the registration results. In this dissertation we develop methods and tools that address some of these challenges, and provide components essential for the intra-operative application of a previously validated physics-based non-rigid registration method.;First, we study the problem of image-to-mesh conversion, which is required for constructing biomechanical model of the brain used during registration. We develop and analyze a number of methods suitable for solving this problem, and evaluate them using application-specific quantitative metrics. Second, we develop a high-performance implementation of the non-rigid registration algorithm and study the use of geographically distributed Grid resources for speculative registration computations. Using the high-performance implementation running on the remote computing resources we are able to deliver the results of registration within the time constraints of the neurosurgery. Finally, we present a method that estimates local alignment error between the two images of the same subject. We assess the utility of this method using multiple sources of ground truth to evaluate its potential to support speculative computations of non-rigid registration

Report from the TeraGrid Evaluation Study, Part 1: Project Findings

TeraGrid integrates multiple high-performance computing resources at distributed provider facilities. In 2006, the National Science Foundation (NSF) awarded a grant to the University of Michigan's School of Information (UM-SI) to conduct an external evaluation of TeraGrid. The primary goals of the evaluation were to provide specific information to TeraGrid managers that will increase the likelihood of TeraGrid success, and to give NSF and policy makers general data that will assist them in making strategic decisions about future directions for cyberinfrastructure. In order to accomplish these objectives, the UM-SI study assessed four aspects of the TeraGrid project: 1) progress in meeting user requirements; 2) impact of TeraGrid on research outcomes; 3) quality and content of TeraGrid education, outreach, and training activities; and 4) satisfaction among TeraGrid partners. We employed a mixed method approach that consisted of a user workshop; participant observation; document analysis; interviews with 86 individuals representing five different categories; a survey of a sample of 595 TeraGrid users; and two surveys to assess TeraGrid tutorials held in 2006 and 2007. Most of the data were collected from June 2006 through May 2007. Findings from the evaluation study are presented in two parts. In this first part, we report results from analyses of all data collected during the investigation. Detailed findings from the user survey are presented in Part 2 of the report.National Science Foundationhttps://deepblue.lib.umich.edu/bitstream/2027.42/61838/2/TeraGrid_Evaluation_Report_Project_Findings_August_2008.pdfDescription of TeraGrid_Evaluation_Report_Project_Findings_August_2008.pdf : Final repor