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Automated Model Compiler based on Design Space Exploration Tool Sandeep Neema Institute for Software Integrated Systems Vanderbilt University Outline Motivation Design Space Exploration Tool AMC Tool Architecture Example (end-to-end) Conclusions and Future Work AMC Challenge Problem

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automated model compiler based on design space exploration tool

Automated Model Compilerbased onDesign Space Exploration Tool

Sandeep Neema

Institute for Software Integrated Systems

Vanderbilt University

outline
Outline
  • Motivation
  • Design Space Exploration Tool
  • AMC Tool Architecture
  • Example (end-to-end)
  • Conclusions and Future Work
amc challenge problem
AMC Challenge Problem

“A model compiler is a tool that automatically composes a model from a set of sub-models and an architectural description of the arrangement of sub-models, ensuring full-connectivity of all control flow and data flow signals between sub-models, proper sequencing of sub-models, and compatibility of sub-models” †

  • Scale and Complexity
    • 75-100 components, 3-30 component variations, 2000 signal-flow interconnections
  • Size of the Search Space
    • ~10^30
  • Multiple levels of compatibility
    • Structural, signal type, simulation properties, …

†Butts et. al. “Usage Scenarios for an Automated Model Compiler,” EMSOFT 2001

de sign s pace e xplo r ation t ool
Design Space Exploration Tool
  • Meta-programmable tool for navigation/pruning of large design spaces using constraints
  • Generic structured representation of design-space based on the concepts of alternatives and parameters
  • OCL-based notation for representing constraints
  • UDM meta-model based input/output interfaces
  • Current: Uses OBDD-based symbolic constraint solver
  • Planned: Integration of other constraint solver (Mozart, …)

Design-Space

(XML)

DESERT

Pruned-Space

(XML)

structuring design spaces with alternatives
Structuring Design Spaceswith Alternatives

Hierarchical Signal Flow Design Language

Hierarchical Signal Flow Design Language extended with Alternatives

constraints
Constraints
  • Constraint language based on a subset of OCL
  • Constraints may express
    • Composability constraints
      • Type and structural compatibility relations
    • Inter-aspect constraints
      • Software/Hardware/Resource dependencies
    • Performance constraints
      • Bounds on quantitative properties of composed system
      • ROM usage < 10 KB
      • RAM usage < 50 KB
constraint solving in desert
Constraint Solving in DESERT
  • Design space is represented with Boolean formulas using OBDD-s
    • e.g. S is implemented by S1 or S2 or S3 and S2 is implemented by S21 and S22
      • S = S1 + (S21 . S22) + S3
  • Compatibility constraints are expressed as Boolean formulas and encoded as OBDD-s
  • Performance constraints require composition of system-level properties from component-level properties
    • e.g. CPU-usage, memory-usage, latency, throughput, …
    • Composition is property-specific: additive, min-max, multiplicative, membership, …
  • Symbolic conjunction of constraints with design space representation results in restriction/pruning of design space
amc tool architecture
AMC Tool Architecture

GME

DESERT

X’lator1

Comp.

Model

Database

(mdl files)

ConfigGen

Matlab/Simulink

Comp.

Data

Dictionary

(m files)

X’lator2

example architecture model

children("b2p").implementedBy() = children("b2p").children("b2p_2")

implies

children("e6212").implementedBy() = children("e6212").children("e6212_2")

Example: Architecture Model
example data dictionary and component model s
Example: Data Dictionary and Component Model/s

Definition.Input(1).Name = 'trig_b13p_30ms';

Definition.Input(1).Description = 'trigger signal';

Definition.Input(1).Unit = 'none';

Definition.Input(1).FloatingPointTargetType = 'function call';

Definition.Input(1).FixedPointTargetType.Signed = [];

Definition.Input(1).FixedPointTargetType.Bytes = [];

Definition.Input(1).FixedPointTargetType.BinPoint = [];

Definition.Input(1).Size = [1 1];

Definition.Input(1).Min = [];

Definition.Input(1).Max = [];

Definition.Input(1).Period = '30';

Definition.Parameter(2).Name = 'ford_test_manager_ROM';

Definition.Parameter(2).Description = 'bytes of ROM used by etc_manager';

Definition.Parameter(2).Unit = '';

Definition.Parameter(2).FloatingPointTargetType = 'double';

Definition.Parameter(2).FixedPointTargetType.Signed = 0;

Definition.Parameter(2).FixedPointTargetType.Bytes = 2;

Definition.Parameter(2).FixedPointTargetType.BinPoint = 10;

Definition.Parameter(2).Size = [1 1];

Definition.Parameter(2).Min = 0;

Definition.Parameter(2).Max = 1000000;

Definition.Parameter(2).DefaultValue = 150000;

example design space exploration
Example: Design Space Exploration

Design Space

729* 567

567 441

441 441

441 441

441 36

* 3^6  interface constraints applied after design exploration

conclusions
Conclusions
  • Demonstrated application of DESERT in creation of an AMC
  • Meta-programmability of DESERT makes it applicable to diverse product-line architectures
  • Meta-model defined interfaces facilitate integration
  • Current constraint solver is scalable w.r.t. design space representation and composability constraints
future work
Future Work
  • AMC
    • Enable membership constraints
    • Enable assembly with Simulink bus technology
    • Automate component characterization
  • DESERT
    • Integration of other constraint-solvers (Mozart)
    • Integrate the tool with the Open Tool Integration Framework (OTIF)