Tackling the Complexity of Timing-relevant Deployment Decisions in Multicore-based Embedded Automotive Software Systems Rolf Schneider, AUDI AG



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Transcription:

Tackling the Complexity of Timing-relevant Deployment Decisions in Multicore-based Embedded Automotive Software Systems Rolf Schneider, AUDI AG 1

Topics Introduction Project ARAMiS ARAMiS Automotive LSSI Demonstrator Deployment Challenges CADMOS Basics Modeling Timing-relevant Deployment Decisions Tool Extensions Development Process Remarks Relationship with AUTOSAR Concluding Remarks 2

Introduction Project Environment, Motivation and Challenge 3

Project ARAMiS key facts Acknowledgements 4 Coordinator: Karlsruhe Institute of Technology Consortium of about 40 Partners (Industrial and Academic) Duration: 40 month Start: 12/2011, End: 03/2015 Funded by: German BMBF (Federal Ministry of Education and Research)

Large Scale Software Integration Demonstrator From Hardware Integration to Software Integration 5

Large Scale Software Integration And Integration Platforms Application A Application B Application C Application D Block of Flats for SW modules 6

ARAMiS AP6.2 Demonstrator Functional integration AURIX TC277 Hardware: Close-to-Production ECU with a wide range of I/O for Prototyping purposes Software: Functional integration with standard methods of AUTOSAR 4 JTAG DAP Ethernet FlexRay CAN ADC GTM PWM SPI USB Transceiver Transceiver Transceiver PWM DCM Inertial Sensor EEPROM Extension Ports IO Switches 7

Goals of the Demonstrator AUTOSAR based System (v4.x) Evolution of current prototyping hardware Integration of functions with varying safety integrity level (ASIL acc. to ISO26262) Mixed criticality system Gaining experience hands-on in or at least close to normal practice Aiming on common practice Using typical development tools and processes if possible Using function software components already in production with known history 8

Deployment Challenges 9

Overwhelming Complexity of Deployment Decisions Millions 100 10 1 0,1 Possible Static Allocations O(p t ) 0,01 0,001 Parallel Cores p 5 6 7 8 3125 5 3125 7776 16807 32768 6 15625 46656 117649 262144 7 78125 279936 823543 2097152 8 390625 1679616 5764801 16777216 Distributable Tasks t What is the impact of a (small) change in deployment on timing? 16.7 Mio. 10

CADMOS A Tool based Approach 11

Approach with Constructive & Analytic Part: Separation of Concerns, Modeling and Extensive Automation Software Component Network Reduced complexity of individual engineering subtasks Allocation Mappings Platform Component Network Better work division for teams of domain experts Increased reusability by low coupling and high cohesion Flexible re-deployment with tool support (generators, analyzers, schedulers, ) 12

CADMOS work flow Model Solver Logic Change Modell SAT? Z3 Deployment Schedule 13

CADMOS Input/Output Software Architecture Hardware Topology Deployment Schedule Cost Model Constraints 14

Modeling Using a Basic System Model to Develop Dedicated Views on Architectures 15

A Basic System Model Components OutboundPorts Components Behavior S C x 1 y 1 Ports Interface Points x 1 x A y x x 2 D y 2 y 1 E x y y 2 y 1 y 2 Channels Communication x 2 x B y y 3 Nested composition enables Systems of Systems Inbound Ports Channels Parallel, pipelined and recursive composition 16

Nested Composition Systems of Systems L 1 L m S C 1 C n S L 1 L k C 1 Root Component S Composition Children of Root C 1 C 2 C n Leaf Components Behavior of parent P follows from composed behavior of children C 1 to C n Finally, behavior of complete system S follows from leafs L i L 1 L k L m-h L m 17

Dedicated Architectures Software Component Architecture L is a model for software-implemented application logic Platform Component Architecture R is a model for platform-provided resources Software Component Network L Allocation Mappings R Platform Component Network 18

Timing-relevant Deployment Decisions Allocations and Schedules by Formal Constraints 19

Explicit Deployment Decisions by Dedicated Models Deployment D = (M, Z) Mapping M allocates software onto platform-elements Schedule Z defines the start times of software-elements Timing-relevant deployment decisions are precisely documented in allocation mapping M and the schedule Z 20

A Deployment Example X(A) T P1 B1 P2 A B H C A B Ressource Axis M(A) = P1 M(H) = B1 M(B) = P2 M(C) = P2 Z(B) Iteration i (B,C) Time Axis Iteration i + 1, 21

Formalized Timing Constraints Execution Times: Precedence: Distances in Time: Mutual Exclusiveness: 22

Tool Extensions Results from current Master Theses 23

Goals of Master Theses Generation of Architecture model Annotation of Timing Constraints Calculation of Schedules including Deployment Find and Resolve Errors and Inconsistencies Consistency of Use Usability 24

Categorization of Constraints Timing Assumptions/ Properties Requirements Deployment- Insensitive Deployment- Sensitive I/O latency Multi-rates of runnables Robustness for communication Expiry Points... Schedule is preemptive and priority-based The precedence constraints All runnables of an atomic SWC on same core AUTOSAR tasks... WCET depending on cores Memory allocation Instruction code allocation WCET depend on nr. of runnables on same core... 25

Work Flow Extension Model Solver Logic UNSAT CORE SAT? Z3 Retrieving information from the solver where changes could help to find a valid solution Deployment Schedule 26

27 GUI Extensions

Development Process Remarks Step by Step from Early Approximations to Precisely Predicted Product Properties 28

Iterative Incremental Development Process User-defined system model and timing constraints C (and L, R) Constraint Solving & Result Synthesis Output: M, Z Precision Architecture Analysis & Constraint Synthesis 100% Automation Refinement of system or constraints Input: L, R, C, T Assessment of allocation and schedule by users 0% Time 29

AUTomotive Open System ARchitecture In Touch with Industrial Relevance 30

Relation to AUTOSAR Concepts Top-Level Software Composition SwcToEcuMapping S System Composition SwComponent Type System Perspective A System S is the comprehensive AUTOSAR element of the whole vehicle system and owns exactly one Top- Level Software Composition implemented as RootSwCompositionProtype Every dedicated SwComponentPrototype is a part of the TLSwC EcuInstance L 1 C 1 C 2 C n L k L m-h Atomic SwComponent Type L m Platform Perspective (left-hand side) The System owns several SystemMappings The SwcToECUMapping C will decompose one or more SwComponentPrototypes to an individual EcuInstance L Application Perspective (right-hand side) Software Components (SWC) can either be a composition of other SWCs implemented by a CompositionSwComponentType C Or are atomic represented by am AtomicSwComponentType L 31

Concluding Remarks 32

Concluding Remarks Complexity tackled by mixed constructive/analytic approach Separation of concerns using dedicated models Extensive automated analysis and generationinstant answers In alignment with typical automotive development process (iterative incremental) Static scheduling only for WCET scenarios : self-timed or dynamic scheduling also possible Future Work / Open Issues Optimization instead of feasibility only Finer grained mapping from components to tasks Direct interfaces to AUTOSAR tools Allow interrupts 33

Thanks to Wolfgang Schwitzer and Christoph Döbber for their Support and Material and Thank You for your Attention! 34