Space Applications Measurement Testbed N. B. Toomarian Jet Propulsion Laboratory

Outline Autonomy Lab Mission Scenario Data Collection Coarse grain performance data collecting Fine grain performance data collecting Measurement bench Integration of Measurement bench into Autonomy lab APGEN Resources Issues (ITAR Restrictions)

The Autonomy Lab

The basic capabilities Realistic flight computing environment composed of a minimal set of re-configurable modules derived from proven flight software that provide all basic spacecraft services. Spacecraft hardware and dynamics simulation. Deployment on the Motorola PowerPC 603, 604, and 750 processors. Support for VME, PCI, CPCI, simulated 1553 busses. Support for shared memory, reflective memory, Ethernet, and 1394 simulation communication

Overview Deep Impact Mars ’03 Mars Sample Return – Rendezvous Studies Space Technology 3 (ST3) Space Interferometry Mission (SIM) X2000 Customer Missions Provides complete flight, ground, and infrastructure software systems normally only accessible through full scale mission development efforts Facilitates demonstration of autonomy technology integrated within a traditional flight system Furnishes a compete development environment including development tools, configuration control, spacecraft simulation, and test-bed hardware Capabilities Provide development and demonstration environment for autonomy technologies seeking TRL 6 qualification Integrate autonomy technologies into legacy flight software systems for the demonstration of new capabilities through complete and realistic mission operation scenarios Purpose Heritage Systems DARTS/Dshell Spacecraft Simulation Deep Space One FSW Deep Space One Simulation Mars Pathfinder FSW Remote Agent Technology Simulation Comm. CORBA Reflective Memory Shared Memory TCP/IP 1394 (Firewire) Target Test-beds PowerPC 750 (cPCI) PowerPC 603 (cPCI & VME) PowerPC 68K (VME) JEM Java Processor Development Infrastructure Technology Demonstrations NEW AUTONOMY TECHNOLOGY FSW CPU Heritage FSW Operating System Spacecraft Bus [Simulation Interface] Ground System Autonomy Test-Bed Mission Scenarios Visualization Simulation CPU Simulation

Implementation Architecture diagram

Mission Scenario Power performance monitoring and measurement we will be done in the context of the Deep Impact mission. Detailed information on Deep Impact can be found in the mission website at gov/. gov/

Deep Impact Mission The spacecraft launches in early January 2004 with an Earth flyby in December The flyby is used to test and calibrate the science instruments. Spacecraft cameras take images of Comet Tempel 1 at least one month prior to impact. The spacecraft approaches Tempel 1 in early July 2005 and releases the impactor 24 hours before impact. High-precision tracking telescopes are used on both the flyby spacecraft and impactor to target the comet and set the impactor on course to hit the sunlit side of the comet.

Deep Impact Mission The flyby spacecraft uses a fixed solar array and a small NiH2 battery for its power system. The impactor is a simple, battery-powered spacecraft that operates independently of the flyby spacecraft for just one day between separation and impact. Two instruments on the flyby spacecraft accomplish optical imaging and infrared spectral mapping to observe the impact and crater. The spacecraft uses an X-band radio (8,000 megahertz) to communicate to Earth while listening to the impactor at UHF frequencies. For most of the mission, the spacecraft communicates to the smaller Deep Space Network 34m beam-wave-guide antenna. During the short period of encounter and impact, a 70m antenna is used to gather the increased speed and volume of data return to Earth.

Why Deep Impact This mission is of great interest for its: –Planning and Scheduling –Computing intensive applications such as: High-precision tracking, Image processing and compression.

Data Collection Four Step Process: –Coarse grain performance data collecting. –Fine grain performance data collecting. –Measurement bench. –Integration of Measurement bench into Autonomy lab.

Data Collecting Coarse Grain Performance Use the Power PC (PPC)-750 to run the DS1 Flight Software. Collect performance data on the percentage of processing time used by each of the approximately thirty major DS1 tasks. Measurements of L1 instruction and L1 data cache misses and total instructions executed during the test will be collected. From this data, we will estimates the actual instruction per second performance of the processor during different operational loads. –During the tests the L1 cache will be enabled and the L2 cache will be disables to emulate the flight configuration for Deep Impact with no L2 cache.

Approach At this stage, the DS1 FSW has been converted to run on a commercial Motorola PPC-750 board running at 233 Mhz. The response of the flight hardware is simulated using the DS1 Simulation Software, which has been converted to run on PPC- 603 board. The Flight and Simulation hardware/software communicate through a pair of reflective memory boards plugged into their respective Compact-PCI backplanes and connected by high speed optical cable.

The operational test scenarios –Using unmodified DS1 FSW: Generic Cruise Idle (no navigation, maneuver, or science activities) A Maneuver Maneuver Planing Collection and Downlink of Science Telemetry Collection and Downlink of an Operational Navigation image with image compression Orbit Determination Operational Navigation with Autonomous bright spot pointing –Using DS1 FSW with Deep Impact Navigation additions for tracking: Collection and Downlink of an Operational Navigation image with image compression Autonomous Operational Navigation with scene analysis

Data Collecting Fine Grain Performance We will modify the compute intensive parts of Deep Impact FSW to get the performance measurements at the subroutine level. This will include either the image processing and compression or the autonomous operational navigation with bright spot target tracking.

The Measurements Bench

Build a PowerPC 750 based test-bed running vxWorks RTOS for the power measurements. Carryout detailed power measurements at the instruction level granularity. Based on the measurements formulate and implement power optimization techniques on the test-bed. Goal

Available power management schemes Power 2.2 W 1.8 mW 126 mW 358 mW 2.2 W

PowerPC 750 pin layout

PowerPC-750 based Test-bed Oscilloscope Tektronix TDS Channels 16 MB per channel 1 GHz sample rate Logic Analyzer > 160 channels High bandwidth PowerPC 750 PGA PowerPC MB L2 cache Ethernet, serial, JTAG Intermediate power supply board PC vxWorks compiler SBC software vxWorks applications Current readings Bus signals Triggers

Integration of Measurement Bench into Autonomy Lab  We can observe the power consumption characteristics of an application by using the performance data gathered by the DS1 test bench and power measurements generated by our measurement bench. Whereas the DS1 test bench measures processor usage and L1 cache misses, our test bench characterizes power consumption of the PowerPC 750. Our test setup analyzes power on an instruction-level granularity. Estimations made on our test bench and applied to the DS1 test bench would definitely benefit from some source of confirmation. By integrating both test benches, we can examine the actual power consumed on a specific application and compare the results with our estimated figures.

APGEN Apgen is a multi-mission planning tool developed at JPL. Early prototype used by Cassini to illustrate the Cruise Plan present: used by Cassini, Mars 98, SRTM, Stardust, etc. This Apgen tool, allows planning personnel to produce ‘rough’ mission plans well before the details of the spacecraft commands are known. It main characterizations are as follows:  Easy and intuitive to use; in particular,  Able to represent simple resources such as Power and Fuel  Able to model the effect of activities on resources in a simplified way  Able to interface with sequencing tools,  Able to operate in networked fashion, with several users sharing data

APGEN Characterization The requirements for Apgen were drawn from the experience of mission planners who were primarily interested in ‘traditional’ (non- autonomous) methods of commanding a spacecraft. A plan is a collection of activities, usually ordered according to increasing start times. An ‘activity’ can be defined loosely (‘orbit insertion’, ‘imaging observation’) or quite precisely (e. g. as a fully defined maneuver with 32 parameters specifying the timing of all related events, the delta V and change in attitude, etc.) Such a plan is summarized in a graphical timeline, each activity being a horizontal bar stretching from its start time to its end time.