Scenario-based PA Method for Dynamic Component-Based Systems

1
Scenario-based PA Method for Dynamic
Component-Based Systems

• Egor Bondarev, Michel Chaudron, Peter de With
• E.Bondarev_at_tue.nl
• Eindhoven University of Technology, The
  Netherlands

2
Problem Statement

• - To accurately predict the performance
  attributes
• - of software component-based systems
• - built on multiprocessor architectures
• Performance attributes
• Timing behaviour,
• Processor usage,
• Memory consumption,
• Bus load

3
Example Problem Car Navigation System (CNS)
4
CNS Architectural Alternatives
1. Predict performance for every alternative 2.
Find optimal alternatives in terms of Resource
usage Performance Robustness
5
Proposed Solution
Based on the following concepts

• Models for both software- and hardware
  components.
• Scenarios-based evaluation
• The designer can focus on critical run-time
  configurations.
• Allows trade-off between modeling effort and
  accuracy.
• Simulation of scenarios schedulability analysis

6
Performance Prediction Approach (2/2)
Input
Application requirements
7
Behaviour and Resource Models
BehavourModel_MPEG4Decoder_Component
behaviour operation IDecode.decodeFrame()
calls IBufferAccess.getElement()
passedBits 0 returnedBits 1024
synchronous TRUE
numberOfIterations 1 calls
IBufferAccess.storeElement()
passedBits 1024 returnedBits 1
synchronous TRUE
numberOfIterations 1
ResourceModel_MPEG4Decoder_Component resource
use operation IDecode.decodeFrame()
cpu claim max 1E7 cycles
(reference processor) aver 1E5
cycles (reference processor) min
1E4 cycles (reference processor) mem
claim 10 KB mem release 3 KB
IDecode
IBufferAccess
getElement()
decodeFrame()
storeElement()
8
Composition of Software Components
9
Composition of Hardware Components

• Performance model specifies IP processing
  capabilities.
• For processing core ? frequency rate and
  scheduling policy
• For memory ? a memory size and addressing type
• For bus ? bit-size, frequency and arbitration
  policy

10
SW / HW Mapping
11
Application Scenario Modelling

• A scenario model defines
• environmental events or system interrupts
• application level stimuli (task triggers)
• for a specific hw/sw-configuration (composition
  structure)

12
Composing the Models

• The generated task specifies
• sequence of constituent method invocations
• period, deadline, priority, synchronization
  constraints

Service_A
Operation_A
13
Scenario Simulation Analysis

• Simulation or Schedulability analysis are
  performed with scheduling algorithms deployed on
  the target OS (RMA, EDF, CBS)
• Simulation results in task latencies, number of
  missed deadlines, CPU, memory and bus utilization

Simulation time
Bus load
Mem load
Simulation time
Simulation time
14
Not mentioned Facilities and Benefits

• Modelling of parameter-dependent behaviour and
  resource usage
• Multiple-platform resource models
• Task synchronization aspects can be modeled
• Component mapping on multiprocessor architecture
• Multidimensional design space exploration
• robusteness vs cost, memory_load vs cpu_load, etc

15
Framework Deployment Issues

• We have developed a tool chain supporting the
  design activities
• We have validated the prediction approach by
  MPEG4 Decoder case study
• prediction accuracy of task latencies is gt 90

Real-Time Prediction Framework