Mark L' Green, Ph'D' - PowerPoint PPT Presentation

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Mark L' Green, Ph'D'

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Title: Mark L' Green, Ph'D'


1
GRASE VO Science and Engineering Applicationson
Open Science Grid
  • Mark L. Green, Ph.D.
  • Grid Computational Scientist, CCR

2
Outline
Outline
  • Center for Computational Research
  • Advanced Computational Data Center Grid
    (ACDC-Grid) System Architecture
  • Molecular Structure Determination
  • Quantum Chemistry
  • Earthquake Engineering
  • Princeton Ocean Model and Biohazards
  • Geophysical Mass Flows
  • Numerical Methods
  • ACDC Grid Dashboards

3
Major Compute/Storage Resources
  • SGI Altix3700 (0.4TF peak)
  • 64 Processors (1.3GHz ITF2)
  • 256 GB RAM
  • 2.5 TB Disk
  • Apex Bioinformatics System
  • Sun V880 (3), Sun 6800
  • Sun 280R (2)
  • Intel PIIIs
  • Sun 3960 7 TB Disk Storage
  • HP/Compaq SAN
  • 75 TB Disk 190 TB Tape
  • 64 Alpha Processors (400 MHz)
  • 32 GB RAM 400 GB Disk
  • Dell Linux Cluster (10TF peak)
  • 1600 Xeon EM64T Processors (3.2 GHz)
  • 2 TB RAM 65 TB Disk
  • Myrinet / Force10
  • 30 TB EMC SAN
  • Dell Linux Cluster (2.9TF peak)
  • 600 P4 Processors (2.4 GHz)
  • 600 GB RAM 40 TB Disk Myrinet
  • Dell Linux Cluster (6TF peak)
  • 4036 Processors (PIII 1.2 GHz)
  • 2TB RAM 160TB Disk 16TB SAN
  • IBM BladeCenter Cluster (3TF peak)
  • 532 P4 Processors (2.8 GHz)
  • 5TB SAN
  • SGI Intel Linux Cluster (0.1TF peak)
  • 150 PIII Processors (1 GHz)
  • Myrinet

4
ACDC-Grid System Architecture
Grid Portal Applications and Administration
Grid Collaborations
Campus Grid Infrastructure
Data Grid Infrastructure
5
ACDC-Grid System Architecture
Grid Collaborations
6
Grid-enabled Data Mining Infrastructure
ACDC-Grid Computational Resources
Grid Portal Workflow Job Manager
Molecular Structure Database
7
Grid-enabling Application Template (GAT)
8
Grid-enabling Application Template (GAT)
9
ACDC Data Grid Database Schema
ACDC-Grid Data Grid
10
SnB GAT
  • SnB is a computer program based on Shake-and-Bake
    where
  • A dual-space direct-methods procedure for
    determining molecular crystal structures from
    X-ray diffraction data is used.
  • As many as 2000 unique non-H atom difficult
    molecular structures have been solved in a
    routine fashion.
  • SnB has been routinely applied to jump-start the
    solution of large proteins, increasing the number
    of selenium atoms determined in Se-Met molecules
    from dozens to several hundred.
  • SnB is expected to play a vital role in the study
    of ribosomes and large macromolecular assemblies
    containing many different protein molecules and
    hundreds of heavy-atom sites.

11
SnB GAT
12
SnB GAT
13
SnB GAT
14
SnB GAT
15
Q-Chem GAT
  • Quantum Chemistry Software (Q-Chem)
  • ab initio electronic structure program
  • capable of performing first principles
    calculations on both the ground and excited
    states of molecules
  • the Q-Chem program exploits the latest
    developments in computer science, having adopted
    an Object Oriented approach to program design
  • allows developers to rapidly implement new
    methodologies with ease and reduce program code
    redundancy

16
Q-Chem GAT
  • Features
  • Ground State Self-Consistent Field Methods
  • Hartree-Fock Methods Density Functional Theory
    Linear Scaling Methods AOINTS Package for Two
    Electron Integrals SCF Improvement Features
  • Wave Function Based Treatments of Electron
    Correlation
  • Møller-Plesset Perturbation Theory Local MP2
    Methods Coupled Cluster Methods Optimized
    Orbital Coupled-Cluster Methods
  • Excited State Methods
  • Supported Calculation Types CIS Methods
    Time-Dependent DFT Coupled-Cluster Excited
    State Methods Attachment-Detachment Analysis
  • Properties Analysis
  • Automated Geometry and Transition Structure
    Optimization Vibrational Spectroscopy NMR
    Shielding Tensors Natural Bond Orbital Analysis
    Stewart Atoms Momentum Densities Intracules
    Atoms in Molecules Solvation Modeling
    Relativistic Energy Corrections Diagonal
    Adiabatic Correction
  • Basis Sets
  • Gaussian Basis Sets Pseudopotential Basis Sets
  • Correction for Basis Set Superposition Error

17
Q-Chem GAT
18
Q-Chem GAT
19
Q-Chem GAT
20
Earthquake Engineering
EADR GAT
  • Evolutionary Aseismic Design Retrofit (EADR)
  • In our effort to develop disaster-resilient
    communities, there is a need to model,
    understand, and ultimately direct the behavior of
    a wide variety of complex multi-scale systems,
    including the many engineering systems that shape
    our physical environment.
  • Two aspects of the structural system needs
  • a multi-scale evaluation tools of progressive
    collapse of structures and
  • use of such evaluation tools in a new general
    framework for aseismic design and retrofit, based
    upon evolutionary methodologies.

21
EADR GAT
  • Multidisciplinary Center for Earthquake
    Engineering (MCEER)
  • MCEER is a national center of excellence that
    applies knowledge and advanced technologies to
    reduce earthquake losses.
  • Network for Earthquake Engineering Simulation
    (NEES)
  • NEES is a national, networked, simulation
    resource that includes geographically-distributed,
    shared-use, next-generation experimental
    equipment sites.
  • Department of Civil, Structural, and
    Environmental Engineering (CSEE)
  • CSEE faculty support eight research centers,
    programs, institutes, and laboratories providing
    synergistic collaborative activities.

22
Earthquake Engineering
EADR GAT
23
EADR GAT
24
EADR GAT
25
POM GAT
  • Monitoring and Event Response for Harmful Algal
    Blooms
  • Development of a transport model capable of
    predicting the movement of harmful algal blooms
    in a lake is currently underway.
  • Developed for each of the three main lakes in the
    Monitoring and Event Response for Harmful Algal
    Blooms (MERHAB) study Ontario, Erie and
    Champlain.
  • To accomplish the goal of predicting bloom
    movement, it is necessary to maintain a near
    real-time database for water velocity fields in
    the lakes and to provide short-term predictions
    of lake circulations.
  • This requires a combination of hydrodynamic and
    transport modeling, along with linkages to
    various data sources, including regional weather
    stations, water monitoring stations, and
    satellite data.

26
POM GAT
27
POM GAT
Assessment of the Regional Great Lakes Watershed
28
POM GAT
29
POM GAT
30
Geophysical Mass Flows
Titan GAT
  • Titan2d Mass-Flow Model
  • The risk of potential volcanic eruptions and
    associated mass flows is a problem that public
    safety authorities throughout the world face
    several times a year.
  • Flow models are useful to forecast the movement
    of volcanic materials on or above the surface.
  • Applications of such models include
  • pre-crisis understanding of hazards and
    developing risk maps,
  • real-time crisis assistance and management and
  • post-crisis reconstruction and distribution of
    aid.

31
Geophysical Mass Flows
Titan GAT
32
Geophysical Mass Flows
Titan GAT
33
Geophysical Mass Flows
Titan GAT
34
Geophysical Mass Flows
35
OSTRICH GAT
  • Ostrich Optimization Software Tool
  • OSTRICH implements numerous model-independent
    optimization and calibration (parameter
    estimation) algorithms including
  • Particle Swarm Optimization,
  • Genetic Algorithm,
  • Simulated Annealing,
  • Levenberg-Marquardt least-squares regression and
  • several zero- and 1st-order numerical techniques.
  • OSTRICH can be used for optimizing many of the
    existing ACDC-Grid grid-enabled applications.

36
OSTRICH GAT
37
OSTRICH GAT
38
OSTRICH GAT
39
OSTRICH GAT
40
ACDC Grid Dashboards
41
Acknowledgments
  • GAT Team Leaders
  • Russ Miller (SnB)
  • Tom Furlani (Q-Chem)
  • Gary Dargush (EADR)
  • Joseph Atkinson (POM)
  • Abani Patra (Titan)
  • Alan Rabideau (OSTRICH)
  • ACDC-Grid Portal
  • Steve Gallo
  • Jon Bednasz
  • ACDC-Grid Research
  • Naimesh Shah
  • Cathy Ruby
  • Amin Ghadersohi
  • Center Personnel
  • Jason Rappleye
  • Sam Guercio
  • Tony Kew
  • Dori Macchioni
  • Martins Innus
  • Adam Koniak
  • Collaborators
  • Charles Weeks
  • Dave Pape
  • Bill Furey
  • Steve Potter
  • NSF, NIH, NYS, DOE
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