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Performance Modelling of Complex Hardware/Software Systems. B.D. Theelen. Overview. Introduction System-Level Design Software/Hardware Engineering Case Studies Modelling and Validation Performance Evaluation Accuracy Analysis Summary. Concepts Requirements. System-Level Design.

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performance modelling of complex hardware software systems

Performance Modelling of Complex Hardware/Software Systems

B.D. Theelen

  • Introduction
  • System-Level Design
  • Software/Hardware Engineering
  • Case Studies
  • Modelling and Validation
  • Performance Evaluation
  • Accuracy Analysis
  • Summary


Concepts Requirements

System-Level Design

Design Time

Component-Level Design

(Automatic)System Implementation



  • Designing a complex system within limited time involves taking important decisions in an early phase of the design process, which may have a deep impact on the performance of the system
  • Early assessment of the impact of design decisions involves using system-level design methods and tools


Three Phases

  • Formulation
    • Informal identification and specification of system concepts and design issues
  • Formalisation
    • Formal specification of behaviour and architecture
    • Validation of adequacy of formal system specification
    • Formal specification of the properties to evaluate
  • Evaluation
    • Property analysis and design decisions


Software/Hardware Engineering (SHE)

  • Formulation using(stereotyped) UML diagrams
    • Performed case studies: documents with plain texts and various diagrams
  • Formalisation based on system-level modelling language POOSL
    • Intended for complex real-time distributed hardware/software systems
    • Small set of very expressive language primitives
    • Formal semantics
      • Defines unambiguously how to handle concurrency, time and probabilism
  • Evaluation
    • Performance evaluation founded onMarkov chain analysis
      • Analytic computation or estimation by simulation
    • Formal verification of correctness properties based on model checking
  • Tools
    • SHESim: Interactive creation and validation of POOSL models
    • Rotalumis: Fast execution of POOSL models for analysis


Case Study: Network Processor

  • (Deep) packet processing in telecommunication systems
  • Utilisation of shared busses
  • Identify possible bottlenecks
  • Comparison POOSL - SystemC


Case Study: Dataflow System

  • Part of Alcatel’s Internet Router
  • Prepares/processes packets for correct routing
  • Arbitration of memory accesses from 3 components
  • Evaluate alternative arbitration mechanisms

case study internet router


Input Buffers

Switch Core

Output Buffers
















Case Study: Internet Router

Is the specified flow-control mechanismsuitable for various product variants?


Executable Model

  • Modelling guidelines (validation)
    • Readability (aggregate data objects), postpone optimising for execution speed
    • Log considerations on the adequacy of abstractions
  • Modelling patterns
    • Point abstractions, abstraction from scheduling mechanisms, stream-based modelling, scalability of model, model refinement



  • Validation guidelines
    • Perform step-by-step inspections
    • Analyse easy-to-check properties
    • Investigate impact of rare events
    • Consider symmetries in system
    • Recall considerations on adequacy of abstractions


Understandable POOSL Model

+ Extensions for Performance Evaluation

Formal Semantics

Markov Decision Process

+ Reward Structure

External Scheduler

Discrete-Time Markov Chain + Reward Structure

Property Formalisation

  • Two options for expressing performance metrics
    • Performance analysis based on external observers: temporal rewards
    • Reflexive performance analysis: POOSL
      • Extend model with additional behaviour to evaluate performance metrics
  • Guidelines for reflexive performance analysis
    • Define extensions in subclasses
    • Use method overriding capabilities of POOSL


Performance Evaluation

  • Analytical computation: Ergodic Theorem
  • Estimation by simulation: Central Limit Theorem
    • Example: packet-loss probability
    • Enables accuracy analysis with confidence intervals
    • Enables automatic termination of simulation when results are accurate


Accuracy Analysis

  • For Internet Router example: a 99% confidence interval [0.001046, 0.001052] is obtained for the average latency
    • Estimation of average latency is 0.001049 seconds
    • We are 99% sure that the real average latency lies in [0.001046, 0.001052]
    • An upper bound for the relative error is 1%
    • Takes 0.0072 seconds of simulated real-time
    • Takes 11.9 hours of simulation time
  • Central Limit Theorem only applicable for simple averages
    • Latency, packet loss probability
  • Complex averages and variances: algebra of confidence intervals
    • Defines set operations on confidence intervals
    • Enables accuracy analysis for range of different averages and variances
    • Jitter, buffer occupancy, processor utilisation, throughput, burstiness
  • POOSL library classes for analysing different long-run averages



  • Three large case studies in corporation with industrial partners
  • SHE method distinguishes three phases
    • Formulation based on informal UML diagrams
    • Formalisation with formal modelling language POOSL
      • Guidelines for modelling and validation
      • Modelling patterns
      • Guidelines for reflexive performance analysis
    • Performance evaluation based on Markov chain analysis
      • POOSL model implicitly defines Markov chain
      • Extensions for performance analysis define reward structure
      • Analytical computation or estimation by simulation
  • Techniques for performance analysis
    • Confidence intervals allow automatic termination of simulation
    • Algebra of confidence intervals for accuracy analysis of complex metrics
      • Library classes for accuracy analysis