1. CReSIS Cyberinfrastructure
CReSIS Lawrence Kansas
February
Geoffrey Fox
Computer Science, Informatics, Physics
Chair Informatics Department
Director Digital Science Center and Community Grids Laboratory of Pervasive Technology Institute (PTI)
Indiana University Bloomington IN 47404

2. What is Cyberinfrastructure
Cyberinfrastructure is infrastructure that supports distributed research and learning (e-Science, e-Research, e-Education)
Links data, people and computers
Exploits Internet technology (Web2.0 and Clouds) adding (via Grid technology) management, security, supercomputers etc.
It has two aspects: parallel – low latency (microseconds) between nodes and distributed – highish latency (milliseconds) between nodes
Parallel needed to get high performance on individual large simulations, data analysis etc.; must decompose problem
Distributed aspect integrates already distinct components (data)
Integrate with TeraGrid (and Open Science Grid)
We are using Cyberinfrastructure – with innovation from special characteristics of use; exploit software from astronomy, biology, earth science, particle physics, business (clouds) …. experience 2 2

3. Indiana University Experience
Indiana University PTI team is a partnership between a research group (Community Grids Laboratory led by Fox) and the University IT Research Technologies (UITS-RT led by Stewart)
This allows us robust systems support from expeditions to lower 48 systems with use of leading edge technologies
PolarGrid would not have succeeded without this collaboration
IU runs Internet2/NLR Network Operations Center
IU is a member of TeraGrid and Open Science Grid
IU has provided Cyberinfrastructure for LEAD (Tornado forecasting), QuakeSim (Earthquakes), Sensor Grids for Air Force in areas with some overlap with CReSIS requirements
IU has significant parallel computing expertise (Fox developed some of earliest successful parallel machines); Lumsdaine leader in many MPI projects – MPI.NET and OpenMPI

5. PolarGrid 2008-2009 Supported several expeditions starting July 2008
Ilulissat: airborne radar
NEEM: ground-based radar, remote deployment
Thwaites: ground-based radar
Expedition Cyberinfrastructure simplified after initial experiences as power/mobility more important than ability to do sophisticated analysis.
Offline analysis partially done on PolarGrid system at Indiana University
Education and Training supported by laboratory and systems at ECSU
Collaboration enhanced by Polycom systems
PolarGrid was an NSF MRI Instrument grant – substantial people support donated by Indiana University

6. CReSIS Cyberinfrastructure
Base and Field Camps for Arctic and Antarctic expeditions
Initial data analysis to monitor experimental equipment
Training and education resources
Computer labs; Cyberlearning/collaboration
Full off-line analysis of data on “lower 48” systems exploiting TeraGrid as appropriate
Data management, metadata support and long term data repositories
Hardware available through PolarGrid, Indiana University (archival and dynamic storage), TeraGrid
Parallel (multicore/cluster) versions of simulation and data analysis codes
Portals for ease of use

7. Technical Approach I
Clouds and Web 2.0 are disruptive technologies but
One should still build distributed components as services
But keep to simple interfaces – REST or basic SOAP
Still access systems through portals
Allowing either gadgets or portlets
Still orchestrate systems using workflow
But mash-ups can be used in simple cases
Still use OGC (Open Geospatial Consortium) standards for Geographic Information System Services
Still use MPI for parallel computing
Threading may be useful on multicore but not obvious (we find better performance with MPI than threads on 24 core nodes for large jobs)

8. Technical Approach II
Semantic Web still useful for metadata but be sure only to use simple RDF and be use it can be mapped to MySQL or equivalent databases
Relevant areas of uncertainty include “Data Intensive” Web 2.0 technologies such as Hadoop (Yahoo) and Dryad (Microsoft)
Likely to change workflow and systems architecture for data intensive problems – as CReSIS has
Clouds likely to change architectures for loosely coupled dynamic jobs such as spawning a bunch of independent Matlab’s
No reason to develop new core technologies for CReSIS but rather deploy and customize existing technologies
Over next year will focus on portal (have some TeraGrid funding with ECSU) and gather requirements in data and modeling areas
Followed by examples of IU Cyberinfrastructure

9. Disloc model of Northridge fault
Disloc model of Northridge fault. Disloc used in Gerry Simila’s geophysics classes (CSUN).
OGCE QuakeSim Portlets

10. OGCE (Open Grid Computing Environments led by CGL) Google Gadgets: MOAB dashboard, remote directory browser, and proxy management.

11. LEAD Cyberinfrastructure

12. WRF-Static running on Tungsten
OGCE Workflow Tools
WRF-Static running on Tungsten

13. N800 Webcam carried by robot
AFRL Sensor Grid
Sensors on robot
RFID Reader
Lego Robot
N800 Webcam carried by robot
GPS
RFID Signal

14. Comparison of MPI and Threads on Classic parallel Code
Parallel Overhead f Speedup = 24/(1+f)
24-way
16-way
2-way
4-way
8-way
1-way
Speedup 28
MPI Processes
CCR Threads
4 Intel Six Core Xeon E GHz 48GB Memory 12M L2 Cache
3 Dataset sizes