NASA Briefing onInformation Technology R&D

Lee B. Holcomb

CIO for NASA

February 25, 2000

Agenda

• Highlights of FY 99 Accomplishments

• Plans for FY 00 and 01

• Budgets for FY 00 and 01

Develop and flight demonstrate a flightcontrol technique that can effectivelyidentify aircraft stability and controlcharacteristics using neural networksand utilize this information to optimizeaircraft performance.

Intelligent Flight Controls

Impact• Enhanced Safety• Reduced Cost

Flight CriticalParameters

Optimize ControlResponse

Results from MPS, a MHD PseudoSpectral codesimulating magnetic fields in the Sun

• Carried out on a 512x512x97 grid.

• The size of the simulation enables it tocontain several coherent structures that canbe associated with the sun's granules.

• Run at 50 Gigaflop/s on 512 processors ofthe ESS Cray T3E at GSFC.

• 100,000 iterations

For the first time the resolution of simulations ofturbulent convection on the Sun’s surface canexceed the resolution of the observations.

• Provides an important framework for the analysis ofobservations by eliminating incorrect interpretations.

• Provides robust theoretical guidelines for the planningof future missions like Solar-B.

Light color represents hotter fluid moving upout of the page; dark color represents colder,sinking fluid.

Light color represents large positive fluxpointing up out of the page; dark colorrepresents large negative flux.

"actual” distributionproduced by simulation

”blurred” distribution that would beobserved by an instrument. It may beinterpreted incorrectly as an emerging

coherent flux tube.

Temperature of top layer Magnetic Flux of top layer

Andrea Malagoli, University of Chicagohttp://astro.uchicago.edu/Computing/HPCC/

Turbulent Convection and Dynamosin Stars

Earth and Space Science (ESS) Project

Goal: To understand the structure andevolution of both large- and small-scale magnetic fields near thesurface of the Sun.

Computational Aerosciences (CAS) Project

FY 00 Plans• Demonstrate a prototype, heterogeneous,

distributed computing system linking multiple,geographically distributed computing testbedsinto a single computing environment

• Demonstrate a 500-times end-to-endimprovement (over 1992 baseline) ininternetwork capability for grand challengeapplications

• Demonstrate scalable, spaceborne applicationsand software-based fault tolerance on a firstgeneration embedded computing testbed

FY 00 Plans (Continued)

• Benchmark and identify high-payoff disciplinetools, integration methods and architecture, andlife-cycle processes for a selected set of testbedapplications:

– Reusable space transportation

– Space station/space shuttle operations

– Earth observation

– Deep space robotic/human exploration

FY 01 Plans

• Prototype network connectivity, databases,query and analysis tools, and intelligent agentsfor access to aviation safety data

• Develop software tools to simulate, benchmark,and optimize the performance of advancedcomputing systems

• Demonstrate real-time capability with software-based fault tolerance for spaceborne computingsystems

FY 01 Plans (Continued)

• Demonstrate a portable, scalable debugging andtest environment for computationalaerosciences applications on a TeraFLOPSsystem

• Demonstrate 1000-times improvement (over1992 baseline) in time-to-solution for grandchallenge applications

• Establish prototype collaborative engineeringenvironments focused on a selected set oftestbed applications (as defined in FY 00)

FY 01 Plans (Continued)

• Establish architectural “plug and play”integration standards

• Develop preliminary knowledge recovery anddata mining tools

• Executive Reasoning• Case-Based Reasoning• High Assurance Software• Biologically-Motivated (Biomimetic)

Adaptive Systems• Planning & Scheduling

Automated Reasoning• Optimized Displays• Immersive / Haptic Environments• Biologically-Motivated (Biomimetic)

Computer/Component Architectures and SW• Internet-Based Knowledge Representation• Cognitive Architectures

Human-Centered Computing

Revolutionary Computing• Quantum Mechanical Computing• Neurally-inspired Computing• Holographic Memory Devices• Biological Computing

• Geographically Distributed Computing• Knowledge Management and Institutional

Knowledge Capture• Reconfigurable Computer Architectures• Knowledge Discovery and Data Mining

Intelligent Systems for Data Understanding

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Cost and RiskManagement Technology

Develop advanced cost analysis andrisk tools in a unified frameworkcovering end-to-end mission design,and compatible with design andanalysis tools for fully integrated lifecycle simulations.

Rapid Synthesis andSimulation Tools

Developing advancedintelligence-based engineeringand science simulation tools foranalysis and design from conceptthrough disposal and synthesistools for seamless coupling ofdiverse discipline tools

Revolutionize Cultural Change,Training and Education

Changing the engineering culture to take fulladvantage of advanced tools and environmentsand developing distributed active learning andtraining collaborative environment

Collaborative EngineeringEnvironment

Advancing the state of practice and insertingthe state of the art collaborative infrastructureand applied design and analysis capabilitiesinto enterprise use.

Life-CycleIntegration and Validation

Developing integration methods,smart interfaces and frameworks toachieve seamless “plug and play”integrated design and analysis, andassessment, validation anddemonstration of ISE technologies.

BETTER, FASTER, CHEAPER

NASA Crosscut BudgetFY 00 FY 01

High End Computing 2 5 . 4 2 5 . 8High End Computation and Infrastructure 9 9 . 4 1 2 9 . 1Large Scale Networking 2 0 . 1 1 9 . 5High Confidence Systems 6 . 5 9 . 1Human Computer Interface and Information Management 5 . 5 1 7 . 9Social, Economic, and Workforce Implications of IT and IT Workforce Development 6 . 7 8 . 3Software Design & Productivity 1 0 2 0

TOTAL 1 7 3 . 6 2 2 9 . 7