NASA/JPL Future Computing Needs

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1 NASA/JPL Future Computing Needs Frontiers of Extreme Computing 2007 October 24, 2007 Dr. Tom Cwik Associate Chief Technologist

2 Introduction Challenges of Space (Systems & Environment) Spaceborne Computing Ground-based Computing (specific to NASA/JPL needs) Spaceborne Computing Path 10/24/07 2

3 1958 First U.S. satellite Explorer 1 10/24/07 3

4 Where are we now? NASA has more than 50 missions exploring our solar system (some examples) Spitzer studying stars and galaxies in the infrared Cassini studying Saturn Ulysses studying the sun GALEX surveying galaxies in the ultraviolet CALIPSO studying Earth s climate Aqua studying Earth s oceans Mars Odyssey, rovers Spirit and Opportunity studying Mars Two Voyagers on an interstellar mission MESSENGER on its way to Mercury Aura studying Earth s atmosphere Hubble studying the universe QuikScat,, Jason 1, CloudSat, and GRACE (plus ASTER, MISR, AIRS, MLS and TES instruments) monitoring Earth. 10/24/07 Chandra studying the 4 x-ray universe New Horizons on its way to Pluto

5 Space Challenges Environment High Radiation Total dose (>mega rads for some missions) SEU Temperature Wide range (-270 deg F on Europa to >900 deg F on Venus) Rapid cycling (>1000 cycles of 100 deg on MER) Vibration Launch Planetary Entry, Descent, Landing. These present severe constraints to the compute hardware 10/24/07 5

6 Space Challenges Communications and Guidance Bandwidth 6 Mbit/s max (modulator limit) Typically much less based on SNR (100 bits/sec) Spacecraft transmitter power typically less than light bulb in your refrigerator Latency (one-way) 20 min to Mars 13 hr to Voyager 1 Navigation Positional accuracy for critical events Velocity determination (continuous) These present severe constraints to mission operations 10/24/07 6

7 Space Challenges Engineering Only flight qualified parts are typically used Systems are >5 yrs out of date when launched (two generations behind commercial art) Several Power and Mass Restrictions W for a flight computer Often can t test final system until its flown Importance of modeling and simulation Long mission duration challenges maintainability of ground assets in operations phase Voyager is based on customer flight computer designed with MSI parts and ferrite core memory of the late 1960 s (programmed in assembler) Ground computers based on Univac 1100 series Silver lining: software is about the only thing that can be changed after launch 10/24/07 7

8 Agenda Challenges of Space (Systems & Environment) Spaceborne Computing Ground-based Computing (specific to NASA/JPL needs) Future Spacecraft Computing Directions 10/24/07 8

Space Flight Avionics & Microcomputer Processor History 100,000,000 10,000,000 Rad-hard components are always at least 2 generations behind commercial State Of The Art Multi-Core Regime (speculative)

9 Space Flight Avionics & Microcomputer Processor History 100,000,000 10,000,000 Rad-hard components are always at least 2 generations behind commercial State Of The Art Multi-Core Regime (speculative) Cell (4/64SP) Cell (8/256SP) Cell (64/1024SP) 1,000,000 Cell (2/16SP) Computational Rate (MIPS) Pentium 4/2530 Pentium 4/2000 PPC7470/1250 Pentium III/450 PPC7455/ Pentium II/450 PPC7441/700 Pentium Pro/ Virtx (2/10M) 400 PPC7400/ PPC604/ Pentium II/233 Deep Impact Pentium/ /75 PPC603e/133 (RadLite750) / /50 PPC601/110 PPC601/80 Mars Pathfinder AIM Stardust 68030/50 (RAD6000) (RAD6000) 68020/ /25 Deep Space 1 (RAD6000) SIRTF 80386/33 Clementine HKP (RAD6000) Cassini (1750) (1750A) COTS Single-Core Era Galileo CDS (1802) Mars Observer EDF (1750A) Mars Global Surveyor (1750A) Mars Pathfinder Rover (80C85) Launch Year Intel Motorola 680X0 PowerPC Missions 10/24/07 9 Cell (1/9SP) X 10 3 RAD750 III FPGA (Core+gates) Flight (Rad-hard) Single-Core Virtx V OASIS/ Hyperion SAR MultiCore FPGA (Core Only) FPGA

10 Future Mission Applications New Types of Science Event detection Opportunistic science (eg dust devils detectors) Model based autonomous mission planning Multiple platform cooperative missions (fleets, swarms ) Smart high resolution sensors (eg., gigapixel, SAR,..) Entry Descent & Landing Flight control thru disparate flight regimes Landing zone identification Hazard avoidance Soft touchdown Surface Mobility Terrain traversal Obstacle avoidance Science Target identification Image/video Compression 10/24/07 10

Data Mining of Image and Time-series Data Capability Recognize events & trends -

and send alerts Features craters volcanoes clouds floods ice Multi-Source Triggers

recognition Data fusion correlate data from several sources to improve accuracy.

11 Data Mining of Image and Time-series Data Capability Recognize events & trends - machine-assisted discovery - automatically generate catalogs, summaries - Watch data streams and send alerts Features craters volcanoes clouds floods ice Multi-Source Triggers Technologies Scale and orientation invariant template matching Time-series analysis Texture recognition Data fusion correlate data from several sources to improve accuracy. Cloud-cover (GOES) + infrared Time Series match + = Eruption (take image) Ground sensors Query 10/24/07 11 Novelty & Changes time

12 Mars Dust Devils Mars Dust Devils 10/24/07 12

Planning and Scheduling commands State Updates goals Automatically generate plan of action that achieves goals while obeying resource & operations constraints.

13 Planning and Scheduling commands State Updates goals Automatically generate plan of action that achieves goals while obeying resource & operations constraints. Continuously revises plan in response to events (~10s) Data_Take Cool Open_Door Scan Close_Door Repair plan Dump_to_SSR Dump_to_SSR Dump_to_SSR Power 10/24/07 13 execute Error: have to retry close, takes longer

14 Duck Bay: Site of Opportunity s descent into Victoria Crater 10/24/07 14

15 Fault Tolerant Space-Borne Scalable Computer (FTSSC) Spacecraft Control Computer System Controller Fault-tolerant recycle-able FTSSC Rad-hard unbreakable COTS Multi-core Compute engine Cluster FPGA Based PIM Interface fabric Intelligent Processor In Memory Data Server Communication Subsystem Instrument Interface Instruments 10/24/07 15

16 Multi-Core Challenges for Space General Programming and execution model Porting of legacy code Heterogeneous/homogeneous architectures Design tools, environments, libraries Space critical Real-time Fault tolerance issues Testability / validation 10/24/07 16

17 Agenda Challenges of Space (Systems & Environment) Spaceborne Computing Ground-based Computing (specific to NASA/JPL needs) Future Spacecraft Computing Directions 10/24/07 17

18 End-to-End Capabilities Needed to Implement Missions Project Formulation - Team X Mission Design Mars Rovers Large Structures - SRTM Real Time Operations Ion Engines Environmental Test Integration and Test Spacecraft Development 10/24/07 18 Ion Engine (DS-1)

Phoenix Mission Landing Simulation NASA s 2007 Phoenix Mars Lander mission is sending a spacecraft to land in the

content of the soil, and also measure local weather phenomena A key phase of Phoenix is the approximately

This phase is commonly termed Entry, Descent and Landing (EDL).

19 Phoenix Mission Landing Simulation NASA s 2007 Phoenix Mars Lander mission is sending a spacecraft to land in the northern polar region of Mars (launch: August 2007; land at Mars: late May 2008) Will sample water ice and chemical content of the soil, and also measure local weather phenomena A key phase of Phoenix is the approximately six-minute traversal of the Martian atmosphere, descent on parachute, and rocket-powered landing on Mars. This phase is commonly termed Entry, Descent and Landing (EDL). The Phoenix EDL team has made extensive use of the JPL advanced computing, beginning in January Continued supercomputer usage planned through Phase E - until actual EDL 10/24/07 19

20 Phoenix Mission Landing Simulation (cont d) Primary advanced computing usage performed sets of 2000-case Monte Carlo simulations of the Phoenix EDL event, for a range of atmospheric entry conditions Varying location, speed and attitude at the top of the Martian atmosphere Varying random noise effects, and injecting various error modes, in the accelerometers, gyroscopes, and radar Varying atmospheric density, winds, terrain features of the landing site, landing thruster performance characteristics Each individual trajectory simulation case takes ~ 3.5 node-hours to run (due to the high-fidelity radar model) Each 2000-case Monte Carlo batch produces ~ 25 Gbytes of raw output data (compressed) that are post-processed by the Phoenix EDL engineers This simulation campaign has logged > 1 Node-Decade of run-time, and ~ 1 TB of useful raw data for sensitivity analyses, statistical characterizations, and outlier analyses. 10/24/07 20

Observing Systems Simulation Experiments (OSSEs) For

sensitivity studies to assess the impact of a remote

Challenges Building/establishing model interfaces

21 Observing Systems Simulation Experiments (OSSEs) For Instrument Design Objective Perform design trade and sensitivity studies to assess the impact of a remote sensing instrument on specific science goals. Challenges Building/establishing model interfaces Large-scale data assimilation High-productivity computing systems (distributed?) Validation of OSSE components New Data Prediction Without Prediction With Improvement 10/24/07 21

22 Observing Systems Simulation Experiments (OSSEs) For Instrument Design (cont d) OSSE Framework Models Instrument Forecast, retrieval, radiative transfer Mission design Data Assimilation Integrated computational environment Physical Parameters Physics Transfer Module Are Science Requirements Met? Comparison Modules Physics-Based Simulation Observed Retrieval Data Level 3 Data Physical Parameters Data Interpretation To Level 3 Integration of Science goals Instrument development Mission design Assessment and sensitivity Science goals to instrument and mission design Optical Parameters ρ, ε, τ, etc. Radiative Transfer Module Constraints Input Radiance Data Instrument Simulator Measured Radiance (Level 1 Data) Level 2 Data ρ, ε, τ, etc. Data Calibration To Level 2 Proposed instrument requirements 1. Physics-based: conservation of energy, diffraction limit, Instrument specifications (measurements) proposed to answer photon noise science questions (spatial, spectral resolution, SNR, etc.) 10/24/07 2. Experience-based: Team I/P historical database 3. Engineering-based: Phase B Preliminary Design and PDR 22

23 Agenda Challenges of Space (Systems & Environment) Spaceborne Computing Ground-based Computing (specific to NASA/JPL needs) Future Spacecraft Computing Directions 10/24/07 23

24 Spaceborne Computing Path Current Generation (Phoenix and Mars Science Lab - 09 Launch) Single BAE Rad 750 Processor 256MB of DRAM and 2 GB Flash Memory (MSL) 266 MFLOPS peak, 14 Watts available power 19 MFLOPS/Watt Performance NASA ST8 Honeywell Dependable Multiprocessor ( 09 task end) COTS Multi-board system with Rad Hard 603e controller Fault-tolerant architecture 6.4 GFLOPS peak/board & 31 Watts available power; overhead needed for FT 220 MFLOPS/Watt Performance - but can scale total MFLOPS with power Scalable to 20 COTS processing nodes Target Radar Application, Large focal-plane array processing, autonomy > 1000 MFLOPS/Watt sustained performance Can multi-core architectures improve power utilization? 10/24/07 24

Ground systems in support of space exploration for Ground Systems Architectures Workshop April 3, 2008

Ground systems in support of space exploration for Ground Systems Architectures Workshop April 3, 2008 Charles Elachi, Director NASA 4/3/08 Elachi GSAW 1 Ground systems have supported space exploration