Scheduling and Memory requirements analysis with AADL F

Introduction and motivations (1/2) q The Architecture Analysis & Design Language (AADL) : •

Introduction and motivations (2/2) q Existing AADL toolsets : OSATE, STOOD, TOPCASED, ADe. S

Talk overview q. Introduction and project motivations q. Usual performance analysis methods q. Cheddar

Usual performance analysis methods : real time scheduling (1/2) q. Periodic task model :

Usual performance analysis methods : queueing systems (2/2) Customer arrivals Queue Server Outgoing customers

Cheddar : a performance analyzer framework q. Cheddar provides Ada 95 packages implementing both:

Cheddar and AADL q. Cheddar was not originally designed to work with AADL. How

AADL threads scheduling analysis (1/3) q. AADL includes most of the features used in

AADL threads scheduling analysis (2/3) q. Example : a set of periodic/aperiodic threads scheduled

AADL threads scheduling analysis (3/3) Compute simulation Analysis (eg. deadlines, response times) SIGAda, Atlanta,

Event data ports memory requirement analysis (1/4) q Event data ports are AADL features

Event data ports memory requirement analysis (2/4) q Queueing systems for AADL event data

Event data ports memory requirement analysis (3/4) q. Example 2 : event data port

Event data ports memory requirement analysis (4/4) Buffer simulation Analysis from simulation Analytical worst

Conclusion and ongoing works q. The Cheddar AADL performance analyzer : • Provides performance

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Scheduling and Memory requirements analysis with AADL F. Singhoff, J. Legrand, L. Nana, L. Marcé University of Brest, France LISYC/EA 3883 SIGAda, Atlanta, nov’ 05 1/20

Introduction and motivations (1/2) q The Architecture Analysis & Design Language (AADL) : • SAE standard published in november 2004 (AS 5506 document). • Allows a high level specification of real time systems in order to perform analysis, source code/documentation generation, … q An AADL specification is q A set of components such as : • Thread : flow of control that executes a program (eg. Ada Task). • Data : any data structure in a program (eg. Ada tagged record). • Processor : part of the execution environment. q Connections between components : model component relationships. q Component properties : component information/characteristic (behavior, Ada package file name, Ada task stack requirement, …) SIGAda, Atlanta, nov'05 2/20

Introduction and motivations (2/2) q Existing AADL toolsets : OSATE, STOOD, TOPCASED, ADe. S … but there is currently few open-source performance analysis tools. q Since 2002, at Brest, we’re investigating : • How to extend real time system analysis methods to take distribution into account ? • How to provide tools to help system designers to predict distributed real time system performances ? • Cheddar, an Ada framework designed to real time applications performance analysis. q How Cheddar can be applied to AADL specifications ? SIGAda, Atlanta, nov'05 3/20

Talk overview q. Introduction and project motivations q. Usual performance analysis methods q. Cheddar : a performance analyzer framework q. Examples of AADL analysis : • AADL threads scheduling analysis • AADL event data port memory analysis q. Conclusion and ongoing works SIGAda, Atlanta, nov'05 4/20

Usual performance analysis methods : real time scheduling (1/2) q. Periodic task model : a bound on execution time (capacity, Ci), a fixed delay between two wake-up times (period, Pi), a temporal constraint to meet (deadline, Di). q. Choose a real time scheduling algorithms (eg. Rate Monotonic). q. Perform simulation analysis : compute and analyze time lines q. Perform Analytical/Feasibility test analysis : no scheduling required SIGAda, Atlanta, nov'05 5/20

Usual performance analysis methods : queueing systems (2/2) Customer arrivals Queue Server Outgoing customers q. Queueing system Kendall's notation : X/Y/n. • • X : customer arrival rate (M, G, D). Y : service time rate (M, G, D). n : number of servers. Examples : M/M/1, M/D/1, M/G/1, … q. Goal : From a given customer arrival/service time rate, compute analytical criteria such as customer waiting time and number of waiting customers in the queue. SIGAda, Atlanta, nov'05 6/20

Cheddar : a performance analyzer framework q. Cheddar provides Ada 95 packages implementing both: • Analytical and simulation queueing systems tools (see proceedings of SIGAda 2005). • Analytical and simulation real time scheduling analysis tools (see proceedings of SIGAda 2004). q. Example of computed criteria : • Processors/tasks : worst/best/average response time, number of context switches/preemptions, missed deadlines, processor utilization factor test, . . . • Shared resources & buffers : worst/best/average shared resource blocking task, priority inversion, maximum/average message waiting time, maximum/average number of messages. . . • … SIGAda, Atlanta, nov'05 8/20

Cheddar and AADL q. Cheddar was not originally designed to work with AADL. How such kind of tool may be applied to AADL ? q. In the sequel, we consider the following examples : • AADL threads scheduling analysis. • Buffer/Memory requirements of AADL event data ports. SIGAda, Atlanta, nov'05 9/20

AADL threads scheduling analysis (1/3) q. AADL includes most of the features used in the context of real time scheduling analysis. q. Nevertheless, the following questions have to be investigated : • Can we model any built-in Cheddar's schedulers or task models ? • Are standard properties enough to perform analytical/feasibility tests on any resources ? • How to express new schedulers or task models ? => we need some new AADL properties related to thread, data and processor SIGAda, Atlanta, nov'05 11/20

AADL threads scheduling analysis (2/3) q. Example : a set of periodic/aperiodic threads scheduled with POSIX 1003. 1 b and Rate Monotonic schedulers. thread implementation T 3 properties Dispatch_Protocol => Periodic; processor implementation cpu 0 properties Compute_Execution_Time => 1 ms. . 2 ms; Scheduling_Protocol => RATE_MONOTONIC; Deadline => 10 ms; Cheddar_Properties: : Preemptive_Scheduler => true; Period => 10 ms; Cheddar_Properties: : Scheduler_Quantum => 0 ms; end T 3; end cpu 0; thread implementation fifo 2 processor implementation cpu 1 properties Dispatch_Protocol => Background; Scheduling_Protocol => POSIX_SCHEDULER; Compute_Execution_Time => 1 ms. . 3 ms; Cheddar_Properties: : Preemptive_Scheduler => true; Cheddar_Properties: : POSIX_Scheduling_Policy => SCHED_FIFO; Cheddar_Properties: : Scheduler_Quantum => 2 ms; Cheddar_Properties: : Fixed_Priority => 5; end cpu 1; Deadline => 100 ms; end fifo 2; SIGAda, Atlanta, nov'05 12/20

AADL threads scheduling analysis (3/3) Compute simulation Analysis (eg. deadlines, response times) SIGAda, Atlanta, nov'05 13/20

Event data ports memory requirement analysis (1/4) q Event data ports are AADL features used for asynchronous message transmission between threads. Events/messages are queued. q Queueing systems may be able to predict event data port me mory requirement. . But we have to answer two questions : • How to take into account AADL thread dispatching (eg. periodic) ? • How to take into account AADL thread scheduling (eg. RM) ? q As for the other AADL features, Cheddar provides : • Simulation tools. • Feasibility tests (based on queueing systems, J. Legrand, F. Singhoff, L. Nana & L. Marcé 2004). SIGAda, Atlanta, nov'05 15/20

Event data ports memory requirement analysis (2/4) q Queueing systems for AADL event data ports : • Define a new customer arrival/service time rate : the P rate. • Define new queueing systems based on the P rate. • Define new feasibility tests. q Worst case analytical analysis based on P/P/1 : • Consumer/Producer threads are periodic. • Ex. Feasibility test : the maximum number of messages in an event data port shared by N periodic producers and 1 periodic consumer is : • 2. N (harmonic AADL thread set) • 2. N+1 (other cases) q Average case analytical analysis based on M/P/1 : • See the SIGAda 2005 proceedings for the feasibility tests. SIGAda, Atlanta, nov'05 16/20

Event data ports memory requirement analysis (3/4) q. Example 2 : event data port connections processor implementation cpu_rm. i properties Scheduling_Protocol => Rate_Monotonic; . . . end cpu_rm. i; process implementation p 0. i subcomponents Producer 1 : thread Producer. i; thread Producer Features Data_Source : out event data port; end Producer; thread Consumer features Data_Sink : in event data port; end Consumer; thread implementation Producer. i properties Producer 2 : thread Producer. i; Dispatch_Protocol=>Periodic; Consumer 1 : thread Consumer. i; . . . connections event data port Producer 1. Data_Source -> Consumer 1. Data_Sink; event data port Producer 2. Data_Source -> Consumer 1. Data_Sink; end p 0. i; SIGAda, Atlanta, nov'05 end Producer. i; thread implementation Consumer. i properties Dispatch_Protocol=>Periodic; . . . end Consumer. i; 17/20

Event data ports memory requirement analysis (4/4) Buffer simulation Analysis from simulation Analytical worst case queueing system analysis (based on P/P/1) SIGAda, Atlanta, nov'05 18/20

Conclusion and ongoing works q. The Cheddar AADL performance analyzer : • Provides performance analysis tools for different AADL features, based on real time scheduling and queueing systems analysis. • This AADL analyzer is distributed since the end of october (http: //beru. univ-brest. fr/~singhoff/cheddar). . . but has to be tested ! • Implementation based on Ocarina (ENST’s AADL Ada 95 parser). • Cheddar can be run as a Stood plug-in, the TNI-Europe CASE tool (Thanks to AADL !). q. Ongoing works : • Related to thread precedency relationships (AADL connections). • Related to hierarchical schedulers (eg. ARINC 653 scheduler). SIGAda, Atlanta, nov'05 20/20