National Center for Supercomputing Applications
A Glimpse of NCSAs Role in Support of Research Radha Nandkumar - - PowerPoint PPT Presentation
A Glimpse of NCSAs Role in Support of Research Radha Nandkumar - - PowerPoint PPT Presentation
A Glimpse of NCSAs Role in Support of Research Radha Nandkumar Program Director, International Affiliations & Campus Relations National Center for Supercomputing Applications radha@ncsa.uiuc.edu U.S.- South America Workshop: Mechanics
National Center for Supercomputing Applications
Begin with Thanks
- Organizers – Profs. Borges, Dumont, Espinosa, Paulino, and Rochinha
– For the invitation – Regular engagements – Making everyone feel welcome, special, and important
- NSF
– Vision, encouragement and funding
- Other Brazilian Collaborators
– Bruno Schulze, LNCC – Vinod Robello and Christina Maria Boeres - UFF – for their invitations, hosting the visit, and for several of their visits to NCSA to seal
- ur collaborations.
- Brazilian Colleagues and Community
– Hospitality and warmth
- Other particiapnts in this workshop for interactions and continued
discussions
- Added bonus and a sign of success - Events such as this workshop are
also enabling newer collaborations “between” U.S. researchers
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A little bit about myself
- Professional preparation
– Nearly 2 decades of experience in HPC and computational science (NCSA); among the staff since inception! – Completed recently (May ’02) an Executive MBA – Ph.D. from the University of Illinois, Urbana-Champaign
- Condensed Matter Physics in Astrophysical Systems (neutron
stars) – Thesis Advisor – Prof. David Pines
– Observational X-ray Astronomy (in India) and Cosmic ray physics (Univ. of Chicago) prior to the above.
- Current Activities
– Enabling International partnerships and collaborations for NCSA – Enabling and monitoring interdisciplinary computational science research at NCSA
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Presentation Outline
- Introduction to NCSA
- Partnerships
- Recent Changes &Trends
- Computing Infrastructure
- Software Infrastructure
- Sample Applications
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National Center for Supercomputing Applications
- NCSA
– a unit of the University of Illinois at Urbana-Champaign – a U.S. NSF HPC center started in 1985 with international collaboration, in its 19th year
- federal, state, university, and industry
funded
– Transition from SCC & HPCC (12 yrs) to PACI Center (7 yrs) to SCI Center (soon) – a globally recognized leader in HEC and computational science, scientific visualizations, innovative software
- Mission
– providing access to leading computing and information technologies
- universities and industry
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Strength of Innovation
NCSA Telnet Mosaic Scientific Visualizations Virtual Director HDF, D2K, Open source software, CAVElib “In-a-Box” Software Suite Grid in a Box => NMI High End Computing Center – #4 in Top500 LES for Alliance and the TeraGrid
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NCSA Personnel in a nutshell
- Current Direction & Vision
– Rob Pennington, Acting Interim Director – Danny Powell, Executive Director
- Past Directors
Founding Director – Prof. Larry Smarr (now in SD) Second Director – Prof. Daniel Reed (now at NC)
- A well-known and innovative organization
– 280 FTEs and more than 130 students in 8 buildings, – awaiting the completion of a new building that will house most of us.
- New Director search is nearing completion
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NCSA Satellite Facilities
Alliance Center for Collaboration, Education, Science, and Software Arlington, VA Technology, Research, Education, and Commercialization Center Suburban Chicago
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NCSA Private Sector Partners
- Previous participants
– Amoco – American Airlines – Dow Chemical – Eli Lilly – FMC – Kellogg – Phillips Petroleum – Schlumberger – Shell Oil – Tribune Company – United Technologies Corp.
- Current/recent partners
– Allstate Insurance – Boeing – Caterpillar – Eastman Kodak – J. P. Morgan – Motorola – Sears
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International Affiliations
- NCSA’s Affiliates
– COPPE, Brazil (RSN) – LNCC, Brazil (Most recent) – APAC, Australia – CCLRC, UK – KISTI, Korea – Kurchatov Institute, Russia – NCHC, Taiwan – NCSA is a member of PRAGMA – CDAC, India (in discussion) – BII, Singapore (in progress)
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History and Pathways to Brazil
- First visit -- NSF/U.S.- Brazilian Collaboration - August, 2002
– Talks on NCSA in multiple locations in Brazil – COPPE, FAPERJ, USP, UBrasilia etc.
- Visit to NCSA by LNCC faculty – November 2002
– Bruno Schulze, Leon Sinay
- ACM/IFIP International Middleware Conference 2003 – Rio, June, 2003
- NSF/U.S.- Brazilian Collaboration Workshop on Advanced Materials - June, 2003
- Discussions on MOA with COPPE started in July 2003
–
- Prof. Rochinha and Prof. Coutinho
- Discussions on MOA with LNCC – August 2003
–
- Prof. Marco Raupp, Prof. Bruno Schulze
- Visit to NCSA by COPPE faculty –August 2003
–
- Prof. Rochinha
- Visit to NCSA by USP faculty, October 2003
–
- Prof. Tereza Christina Carvalho
- MOA between NCSA and LNCC – December 2003
- Invitation to NCSA Staff for the LNCC Workshop on Grid Computing
– Highlighted NCSA-LNCC MOA – February 2-5, 2004 – Half a dozen NCSA/UIUC members participated in the workshop + our AU Affiliate
- NSF/U.S.- Brazilian Collaboration Workshop on Advanced Materials - August 2004
- MOA between NCSA and COPPE – Expected to be completed in August 2004
- LNCC Computational Science Workshop and Mini-symposium – next week -August
2004
- Middleware workshop in conjunction with the Middleware Conference – October
2004
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Recent Trends and Transitions
- New Program
– Recent CISE reorganization – PACI Program sunset; New SCI Program at NSF
- NCSA’s new directions
– Cyberinfrastructure in support of research, a new imperative
- New modalities
– Coopetition to cooperation – NCSA & SDSC - maintain our uniqueness and also work together
- Building Stronger Affiliations
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International collaborations outlook “The National Science Foundation should establish and lead a large-scale interagency, and internationally coordinated Advanced Cyberinfrastructure Program (ACP) to create, deploy and apply cyberinfrastructure in ways that radically empower all scientific and engineering research and allied education.”
- - NSF’s Blue Ribbon Panel /Atkin’s Report
ACP => Shared CyberInfrastructure Program
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Cyberenvironments
A cyberenvironment is a subset of general CI capabilities and functionality that is designed and built to meet the needs of a particular community. It includes use of broadly used middleware and networks as well a community specific facilities, software frameworks, networks, and people. It is a persistent, robust, and supported capability.
Specific
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Our core expertise
- Development & Deployment of Cyberinfrastructure
– Computing & Grid Infrastructure – Capability and Capacity Computing – Middleware Development and Deployment
- Access to these environments for empowerment of
science and user communities
– Enabling breakthrough scientific discoveries – Increasing knowledge and understanding
- Community engagement
– Nationally and internationally – Education, Outreach, and Training
- Building successful collaborations
– To pursue all of the above
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NCSA focus in Cyberinfrastructure
Stable, robust and supported cyberenvironments for scientific research and communities
- Community engagement to determine requirements
- Science drivers to make sure that the requirements are
implemented correctly
- R&D if/as necessary to do the development for the
requirements
- Integration into the production environment
- Continuing support plan of the products
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Active Collaborations => Cyberinfrastructure
- Support the effective use of the extant
resources by applications scientists and educators
– Example: analysis of large complex datasets utilizing
- n-demand and interactive resources to enable data to
knowledge results
- Coordinated activities aimed at creating a
national cyberinfrastructure
– Partnerships and joint projects such as TeraGrid, NCSA/SDSC collaborations, NMI, NEESgrid, …
- Encourage and actively participate in
interdisciplinary collaborations
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NCSA/Alliance Multiphase Strategy
- Multiple user classes
– ISV software, hero calculations, data intensive analysis – distributed resource sharing, parameter studies
- Four computing approaches
– shared memory multiprocessors
- 12 32-way IBM IBM p690 systems (2 TF peak)
- large memory and ISV support
– TeraGrid Itanium2 clusters
- 64-bit Itanium2/Madison (10.6 TF peak)
- ETF partners
– IA-32 clusters (>17 TF peak)
- 32-bit systems for hero calculations
- dedicated sub-clusters (3 TF each)
– To be allocated for weeks or longer to specific teams
– Alliance Technology Grid & Condor resource pools
- Complemented by large-scale archives
– ~500 TB secondary and 2 PB tertiary storage
NCSA Control Room
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NCSA Computing Environment — 32 TF
Platinum
Intel Pentium III 1 GHz IBM cluster 1,024 processors 1 TF peak performance GPFS
Titan
Intel Itanium 800 MHz IBM cluster 320 processors 1 TF peak performance NFS
Copper
IBM POWER4 p690 systems 384 processors 2 TF peak performance GPFS, 24 TB
Mercury, phase 1
Intel Itanium 2 1.3 GHz IBM cluster 512 processors 2.662 TF peak performance GPFS, 60 TB
Mercury, phase 2
Intel Itanium 2 1.5 GHz IBM cluster 1,334 processors 8 TF peak performance GPFS, 170TB
Tungsten
Intel Xeon 3.0 GHz Dell cluster 2,560 processors 17.7 TF peak performance Lustre, 140 TB
#135 #111 #99 #35 #4
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Extensible TeraGrid Facility
NCSA: Compute Intensive SDSC: Data Intensive PSC: Compute Intensive
IA64 IA64 Pwr4 EV68 IA32 IA32 EV7 IA64 Sun
10 TF IA-64 128 large memory nodes 230 TB Disk Storage 3 PB Tape Storage GPFS and data mining 4 TF IA-64 DB2, Oracle Servers 500 TB Disk Storage 6 PB Tape Storage 1.1 TF Power4 6 TF EV68 71 TB Storage 0.3 TF EV7 shared-memory 150 TB Storage Server 1.25 TF IA-64 96 Viz nodes 20 TB Storage 0.4 TF IA-64 IA32 Datawulf 80 TB Storage Extensible Backplane Network
LA Hub Chicago Hub
IA32 Storage Server Disk Storage Cluster Shared Memory Visualization Cluster
LEGEND
30 Gb/s
IA64
30 Gb/s 30 Gb/s 30 Gb/s 30 Gb/s
Sun Sun
ANL: Visualization Caltech: Data collection analysis
40 Gb/s
Backplane Router
+ ETF2 sites: TACC, IU, Purdue and ORNL in FY04
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Additional ETF Sites - 2004
LA Hub Chicago Hub 30 Gb/s 30 Gb/s 30 Gb/s 30 Gb/s 30 Gb/s 40 Gb/s
Cluster Agg Switch
LEGEND
Backplane Router
Linda Winkler (winkler@mcs.anl.gov) SDSC Caltech NCSA PSC ANL
20 Gb/s Atlanta Hub 20 Gb/s
IPGrid
10 Gb/s 20 Gb/s 10 Gb/s
PU IUB IUPUI TACC
10 Gb/s 10 Gb/s
10 Gb/s
ORNL
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Combine Data Resources Across TG
Home Directory Node Local Storage Scratch/Staging Storage Parallel Filesystem Archival System Cap.
H
SDSC
H
100 TB QFS 64 TB GPFS SAM-FS 2 TB NFS
L
NCSA
H
70 GB/node 8 TB TTS 1.5 PB UniTree 1 TB NFS
L
ANL
H
132 GB/node IA-32 16 TB PVFS 4 TB NFS
L
Caltech
H
70 GB/node 80 TB PVFS 1.2 PB HPSS 140 GB NFS
L
PSC
H
38 GB/node TCS 30 TB PFS 3 PB DMF .5 TB NFS TCS
L
6 PB HPSS /
L
64 GB/node IA-64
L
35 GB/node
S S
100 TB QFS
S
39 TB GPFS
S
24TB SLASH
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Access to HPC Resources
- Allocation Process
– PIs are U.S. Researchers from academic institutions – Co-PIs/Collaborators could be non-U.S. academicians – Initial small amount of resources with simple web based requests on-line to start-out – Larger, subsequent resource allocations by proposal submissions for peer-review – Review Boards meet frequently
- Our HPC User Community
– ~2000 users per year – ~500 PIs projects – ~58% usage by MPS Division
- Math & Physical Sciences -
- AST, CHE, DMR, DMS & PHY
Materials Research Projects Usage 500000 1000000 1500000 2000000 2500000 3000000 3500000 1 9 8 6 1 9 8 7 1 9 8 8 1 9 8 9 1 9 9 1 9 9 1 1 9 9 2 1 9 9 3 1 9 9 4 1 9 9 5 1 9 9 6 1 9 9 7 1 9 9 8 1 9 9 9 2 2 1 2 2 DMR
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Users by Type in 2003
Grad Student 38% Faculty 29% Postdoc 19% Research Staff 10% Undergrad 2% Other 2%
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Cluster in a Box/OSCAR
- Community code base with strong support
– Bald Guy Software, Dell, IBM, Intel, Indiana, MSC.Software, NCSA, ORNL, Sherbrooke University
- Six releases within the past year
– >29,000 downloads during this period
- Recent additions
– HDF4/HDF5 I/O libraries – OSCAR database for cluster configuration – Itanium2 and Gelato consortium integration – NCSA cluster monitor package (Clumon) – NCSA VMI 2 messaging layer
- Myrinet, gigabit Ethernet and Infiniband
– PVFS
- The First Annual OSCAR Symposium
– May 11-14, 2003, Québec, CANADA
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Grid in a Box => NMI
- Goals
– middleware integration
- packaging, testing, documentation
– community building
- instruments, laboratories and data
- Features and status
– middleware used by many projects – additional funding supporting new sites
www.nsf-middleware.org
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Display Wall In A Box
- Current software
– Chromium and Pixel Blaster Movie Player – Argonne movie viewer – VTK geometry viewer and VNC
- Download via www.ncsa.uiuc.edu
Rear Projectors LCD Panels
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Visualization of Multiple Simulations
Source: Bob Wilhelmson
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NCSA’s Application Centric Efforts
- Astronomy and Astrophysics
- Arts and Humanities
- Biology
- Engineering
- Environmental Sciences
- Geosciences
- Integration of Education
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CI Architecture
Other services
TeraGrid CII
Network
Allocation, performance monitoring, NWS, VMI, GridSolve, MPI
Data- base SMP Cluster Mass Store
Network
Data Movement
GridFTP, MetaData, RFT, File Systems
Security
Kerberos, GSI, KCA, Authorization, Credential Management, OTP, auditing, monitoring, IDS
Physical Core Services
Co- Scheduling
Compute, Data, Network
Data Management
SRB, HDF, Semi- automatic MetaData generation, Data Fusion, Sensor Data Framework
Visualization systems
Application- Centric Services
WorkFlow Services
OGRE
Portal Services
OGCE
User Applications
Cactus
Data Mining
Selection, Transformations, Modeling, Presentation, Predictive Methods, Motif Analysis
Visualization
Automatic Feature Extraction, Mesa, Maya, Trajectory Viz, Professional Visualization Services, VTK
Collaborative Tools
Chef, AG
Cyber- Environments
Resource Management
Condor, Globus, Scheduling, On- demand, Info Svcs, Monitoring
Tools/ Libraries
J2EE, PyGlobus, CoG, Atlas, Blast, FFT...
Bio Portal
...
Chemistry Portal Weather Portal Astro Portal
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Black Hole Collision Problem
1963 Hahn and Lindquist IBM 7090 One Processor Each 0.2 MF 3 Hours 1977 Eppley and Smarr CDC 7600 One Processor Each 35 MF 5 Hours 1999 Seidel and Suen, et al. NCSA SGI Origin 256 Processors Each 500 MF 40 Hours 300X 30,000X 1,800,000,000X 2001 Seidel et al NCSA Pentium III 256 Processors Each 1 GF 500,000 Hours total plus 500,000 hours at NERSC ~200X
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Tornado Modeling – Data to Knowledge
Large complex datasets require data analysis and visualization in the search for understanding
Wilhelmson and Cox
National Center for Supercomputing Applications
Tornado Simulation
Cox and Wilhelmson
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Tornado Simulation – Ground Level
Cox and Wilhelmson
National Center for Supercomputing Applications
Data Management and Visualization Data Set
– Computations were performed on 16 processors of the IBM p690 (Regatta) supercomputer at NCSA – ~ 16,000 time steps, 8.6 days wall clock time – Simulation spans 2.8 hours – 3D volume data available every 2 seconds around main tornado event 6300-9600 sec (~ 55 minutes) (tornado duration ~ 40 minutes) – Data save format HDF – compressed (save ~ 6 x space) and chunked (allows faster reading of partial volumes of data) – Data volume ~ 650 GB in compressed and scales form (~4.0 TBytes if all data in 32 bit form) – Animation time – 30 fps x 2 sec, therefore 1 sec animation = 1 minute in real time
Source: Cronce, Gilmore, Romine, Wilhelmson
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Visualization tools and techniques
- Visualizations by the Experimental Technologies group
- f NCSA
- Trajectories calculated from the model dynamical fields
based on original trajectory code by David Wojtowicz (DAS)
- Renderings
generated with Maya software (professional rendering tool commonly used in animated movies, video games, etc…)
Source: Cronce, Gilmore, Romine, Wilhelmson
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MEAD Expedition => LEAD
– Modeling Environment for Atmospheric Discovery
- cyberinfrastructure for Grid-based parametric studies
– mesoscale convective systems and hurricanes
- recall the Hurricane Floyd experience
– Features
- WRF and ROMS coupling
– community atmospheric and ocean models
- Grid workflow management
- data management and visualization
– very large computed and derived data sets – high performance parallel I/O using HDF5 – metadata, mining and machine learning
- model and performance analysis
- education and outreach
– See www.ncsa.uiuc.edu/Expeditions/MEAD
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LEAD Project Motivation
- Each year, mesoscale weather – floods, tornadoes, hail,
strong winds, lightning, and winter storms – causes hundreds of deaths, routinely disrupts transportation and commerce, and results in annual economic losses > $13B.
Source: Kelvin Droegemeier
National Center for Supercomputing Applications
CI Underpinnings for LEAD
– On-demand – Real time – Automated/intelligent sequential tasking – Resource prediction/scheduling – Fault tolerance – Dynamic interaction – Interoperability – Grid and Web services – Personal virtual spaces
Source: Kelvin Droegemeier
National Center for Supercomputing Applications
Parallel Multi-Scale and Multi-Physics Simulations
micro meso
10-10 m 102 m 10-15 s 106 s macro macro
Source: Keshav Pingali, Cornell
National Center for Supercomputing Applications
Adaptive Software/Understanding Fracture
- Wide range of length and time scales
- Macroscopic components used in engineering practice
- Macroscopic behavior simulated using finite-element
method
- Homogeneous materials at the macroscale become
heterogeneous, polycrystalline assemblies as one zooms down to mesoscales (1-10 microns)
- Structures at the mesoscale (grain boundaries,
dislocation cell structures, and coalescing voids etc.) must be understood in terms of the collective behavior of large numbers of lattice defects (vacancies, dislocations, etc.)
- Atomistic modeling is required to develop effective
descriptions of lattice defects, and collections of such defects, for use at the mesoscale
10-3 10-6 10-9 m
Source: Keshav Pingali, Cornell
National Center for Supercomputing Applications
Multiscale Physics
- How to do it without losing accuracy?
– QMC /DFT – DFT-MD – SE-MD – FE
- How to make it parallel? (Load balancing with
different methods)
< 100Å < 1000 Å 10000 Å
Physical Scale Macroscopic Macroscopic
Mesoscale Mesoscale
Nanoscale
Atomic
Nanoscale
Atomic
Simulation Scale
Classical Monte Carlo Classical Monte Carlo
Effective Mass Schrödinger Equation Effective Mass Schrödinger Equation
Car-Parrinello Quantum Monte Carlo Car-Parrinello Quantum Monte Carlo
Multiscale Hierarchy
MFlop GFlop TFlop
Integrating what is at the microscopic quantum level with the mesoscopic classical level – Great Challenge. Lots of software and interdisciplinary work needed.
Source – David Ceperley, UIUC
National Center for Supercomputing Applications