1 3/3/04 Update Virtual Prototyping of Advanced Space System Architectures based on RapidIO...

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1 3/3/04 Update 3/3/04 Update Virtual Prototyping of Advanced Space System Virtual Prototyping of Advanced Space System Architectures based on RapidIO Architectures based on RapidIO Principal Investigator: Principal Investigator: Dr. Alan D. George Dr. Alan D. George OPS Graduate Assistants: OPS Graduate Assistants: David Bueno David Bueno Ian Troxel Ian Troxel RA Graduate Assistants: RA Graduate Assistants: Chris Conger Chris Conger Adam Leko Adam Leko MS Group MS Group HCS Research Laboratory HCS Research Laboratory Department of Electrical and Computer Engineering, University of Florida Department of Electrical and Computer Engineering, University of Florida

Transcript of 1 3/3/04 Update Virtual Prototyping of Advanced Space System Architectures based on RapidIO...

Page 1: 1 3/3/04 Update Virtual Prototyping of Advanced Space System Architectures based on RapidIO Principal Investigator: Dr. Alan D. George OPS Graduate Assistants:

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3/3/04 Update3/3/04 Update

Virtual Prototyping of Advanced Space System Virtual Prototyping of Advanced Space System Architectures based on RapidIOArchitectures based on RapidIO

Principal Investigator:Principal Investigator:

Dr. Alan D. GeorgeDr. Alan D. George

OPS Graduate Assistants:OPS Graduate Assistants:

David BuenoDavid Bueno

Ian TroxelIan Troxel

RA Graduate Assistants:RA Graduate Assistants:

Chris CongerChris Conger

Adam LekoAdam Leko

MS GroupMS Group

HCS Research LaboratoryHCS Research Laboratory

Department of Electrical and Computer Engineering, University of FloridaDepartment of Electrical and Computer Engineering, University of Florida

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TopicsTopics

Review modeling progress– RapidIO (RIO) library overview– Traffic model overview

Discuss project output options– Have several options in mind– Need to clarify what is needed

Conclusions & questions

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RIO Library OverviewRIO Library Overview RIO Packets (data structures)

– Message Passing Logical Layer– Parallel Physical Layer

RapidIO Endpoint Model– Message Passing Logical Layer– Common Transport Layer– Parallel Physical Layer

RapidIO Central Memory Switch Model– Parallel Physical Layer– Transport Layer

Traffic Models Statistics Gathering

– RIO Request Stats (latency and BW)– RIO Response Stats (latency and BW)

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RIO Packets/Data StructuresRIO Packets/Data Structures

Restart-from-retry Packet Control Symbol

– Used to restart after a packet retry RapidIO Flow Control Symbol

– Positive or negative ACK of packet RapidIO Message Passing Logical

Layer over Common Transport Layer over Parallel Physical Layer packet

– Actually a physical hierarchy of data structures within the MLD data structure editor, each one adding the appropriate fields for the given layer

RapidIO Message Passing Response packet

– End-to-end responses used in Message Passing Logical layer

Statistics data structures– Not actual RIO structures, but used to

measure average latency and bandwidth for RIO requests and responses

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RapidIO Endpoint ModelRapidIO Endpoint Model

Key Features– Message Passing Logical Layer– Common Transport Layer– Parallel Physical Layer

Receiver-controlled flow control Error detection and recovery

– Currently under development Priority scheme for buffer management

Key Adjustable Parameters– Packet assembly delay– Packet disassembly delay– Clock frequency– Link width– Input queue length– Output queue length– Four priority thresholds

Determine the maximum number of packets that may be in a buffer to still accept a packet of a given priority Example: If threshold for priority 0 packets is 4, incoming priority 0 packets will be rejected if there are 5 or

more packets currently in the input buffer– Number of device ID bytes in packet (affects packet size and max number of devices in system)– Buffer memory copy delay per byte

Note: As there is no “link model”, parameters such as clock frequency and link width are incorporated into the endpoint model.

High-level Endpoint Model

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RapidIO Central Memory Switch RapidIO Central Memory Switch ModelModel

Key Features– Selectable cut-through or store-and-forward routing– Non-blocking architecture– Routes packets based solely on destination ID (read from a routing table file) as per

RIO spec– RIO Common Transport Layer– RIO Parallel Physical Layer

Key Adjustable Parameters– Cut-through/store-and-forward behavior– Average central memory read latency– Average central memory write latency– Additional switching latency– Queue length per port

To be changed to reflect a single pool of dynamically allocated memory Parameter will become “Central memory size”

– Link width, clock frequency, and other physical layer parameters as detailed in previous slide

– Priority threshold scheme may need to be changed depending on how the central memory switch handles traffic of different priorities

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RIO Central Memory Switch RIO Central Memory Switch SnapshotSnapshot

KeyRead routing table from fileInsert source routing information

Determine correct output portPhysical layer componentsRe-reoute control symbols back to input link partner

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Traffic Models - SourcesTraffic Models - Sources Key Features

– Generic data source (data cube generator)– Creates N RapidIO packets

Uniformly distributed throughout CPI

Key Adjustable Parameters– Pulses– Ranges– Beams– CPI– Max payload size– Size per element of data cube

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Traffic Models – ProcessorsTraffic Models – Processors Key Features

– Generic vector processor Buffers N packets Adds processing delay Resends with configurable distribution

– Can be used to change traffic distributions at various places in model

– Can also be used to model generic processors (set group size=1)

Key Adjustable Parameters– Number packets to buffer– Processing group delay– % Packets to retransmit– Output traffic distribution

Uniform Poisson Normal

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Preliminary System-Level Test ModelPreliminary System-Level Test Model

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Project Output OptionsProject Output Options Excel spreadsheet

– Create analytical models from analysis of MLD models and simulations– Advantages:

Excel spreadsheets easy to use– Disadvantages:

Least accurate option available– Difficult to make analytical models accurate

Cannot model transient conditions Should be reserved for worst-case analysis

Database-backed program– Run trade studies on specific ranges for parameters– Store results of each run in database– Advantages:

Should be easy to use Results can be obtained in small amounts of time

– Disadvantages: Can be very time consuming for lab to run trade studies Results limited by ranges of parameters chosen

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Project Output Options Project Output Options (Recommended)(Recommended)

MLD models + documentation– Deliver both MLD models and extensive documentation on how to use models– Advantages:

No limitations on parameters Turn-key solution Can change underlying assumptions or data flow easily

– Disadvantages: MLD learning curve (although mitigated by documentation) MLD license needed (Honeywell evaluation of tool in progress) Simulation time as compared to pre-run simulations or Excel spreadsheet

MLD models + front end tool– Possible to “script” MLD runs through a front end tool we create

Accomplished via ptclsh tool that comes with MLD– Front end tool would take care of setting up MLD parameters and coordinating runs– Advantages:

Same as MLD models + documentation MLD learning curve not applicable Can modify MLD models later if necessary

– Disadvantages: Same as MLD models + documentation MLD license still needed

Can make site visit to walk everyone through the models and chosen output system prior to the conclusion of output system deliverable

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ConclusionsConclusions Building blocks for RIO library almost complete Still to do:

– Alter switch model to support single dynamically allocated central memory

– Project output definition Need guidance from options listed in this slide set

Next phases:– System architecture specifications– Complete traffic model

Generic traffic model components created will support several different parameters

Need to determine traffic periodicity, distribution, and data partitioning (see questions on next slide)

– System architecture modeling

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QuestionsQuestions Switch modeling

– 1) Are we interested in transmitter-controlled flow control?– 2) Is all traffic in the system of equal priority?

Are the 4 RIO physical-layer packet priority levels going to be important? Traffic modeling

– 1) Does data cube get directly sent to memory first, or is it sent to processing nodes first?

See diagrams on HCS Honeywell website, “Initial GMTI traffic model options”– 2) Data partitioning scheme:

Is incoming data cube split across a single dimension before being sent out to each processing element? If not, how is data partitioned among processors?

Is any data repartitioning needed between phases of the GMTI algorithm (such as corner turn, etc)?

– 3) Processor partitioning scheme(s): Do processors handle all phases of GMTI algorithm (pulse compression, Doppler

processing, etc)? How many processors per board?

– If > 1, what is the onboard inter-processor communication method (RapidIO, …)? Do all processors on the same board share one RapidIO endpoint?

What different schemes is Honeywell interested in exploring?