modeling timing constraints, parameterized and multi-clock systems in tadl2
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Modeling timing constraints, parameterized and multi-clock systems in TADL2. Johan Nordlander, Chalmers University of Technology. System models & constraints. A system model:. cost. timing. logical. resource usage. structural. - PowerPoint PPT PresentationTRANSCRIPT
ITEA 2 – 09033: TIMMO-2-USE
Timing Model –Tools, algorithms, languages, methodology, USE cases
2012-09-24..25 AMST Workshop - Berlin Slide 1
Modeling timing constraints, parameterized and multi-clock
systems in TADL2
Johan Nordlander, Chalmers University of Technology
System models & constraints
2012-09-24..25 AMST Workshop - Berlin Slide 2
A system model:
Industry objective: specify / characterize / verify models using constraints
logical...
resource usage...
cost...timing...
structural...
TADL2 (Timing Augmented Description Language)
2012-09-24..25 AMST Workshop - Berlin Slide 3
A language of timing constraints (and timing constraints only)
TADL2
Model
ConstraintsConnecting points:the events exposedby a system model
Delay... Periodic...
Events & occurrences
2012-09-24..25 AMST Workshop - Berlin Slide 4
For each execution / simulation / prediction of a system,every event occurs a some points in time.
Model
time
TADL2 constraintsput demands on therelative placementof such occurrences
Source-to-target delay• What if source repeats?• Can multiple target
occurrences match?• Are stray target
occurrences allowed?
The need for semantic precision
2012-09-24..25 AMST Workshop - Berlin Slide 5
• But what about jitter?• What if jitter > period?• What if repetition stops?
• Is jitter meaningful here too?• Same as upper-lower difference?• Accumulating vs. non-accumulating drift?
Some well-known occurrence patterns:
Periodic repetition
Sporadic repetition
DelayConstraint
2012-09-24..25 AMST Workshop - Berlin Slide 6
DelayConstraint (source, target, lower, upper)x source : y target : lower ≤ y – x ≤ upper
time
source
target
lowerupper
duplicate and stray occurrences allowed
StrongDelayConstraint
2012-09-24..25 AMST Workshop - Berlin Slide 7
StrongDelayConstraint (source, target, lower, upper)i : x : x = source(i) y : y = target(i) : lower ≤ y – x ≤ upper
time
source
target
lowerupper
1 2 3
1 2 3
duplicate and stray occurrences disallowed(lock-step enforced)
ReactionConstraint
2012-09-24..25 AMST Workshop - Berlin Slide 8
time
minimummaximum
stimulus
response
scope
ReactionConstraint ( scope, minimum, maximum )x scope.stimulus : y scope.response :
x.color = y.color (y’ scope.response : y’.color = y.color y ≤
y’) minimum ≤ y – x ≤ maximum
only first related response of interest
TADL2 constraint overview
2012-09-24..25 AMST Workshop - Berlin Slide 9
DelayConstraint (source, target, lower, upper)StrongDelayConstraint (source, target, lower, upper)RepetitionConstraint (event, lower, upper, span, jitter)SynchronizationConstraint (event, tolerance)StrongSynchronizationConstraint (event, tolerance)ExecutionTimeConstraint (start, stop, preempt, resume, lower, upper)OrderConstraint (source, target)ComparisonConstraint (leftOperand, rightOperand, operator)SporadicConstraint (event, lower, upper, jitter, minimum)PeriodicConstraint (event, period, jitter, minimum)PatternConstraint (event, period, offset, jitter, minimum)ArbitraryConstraint (event, minimum, maximum)BurstConstraint (event, length, maxOccurrences, minimum)ReactionConstraint (scope, minimum, maximum)AgeConstraint (scope, minimum, maximum)OutputSynchronizationConstraint (scope, tolerance) InputSynchronizationConstraint (scope, tolerance)
+ mode-dependencyparameter (optional)
... but quite ok when restricted to mode M!
M
A mode-dependent DelayConstraint
2012-09-24..25 AMST Workshop - Berlin Slide 10
time
source
target
lowerupper
Not satisfied overall...start(M)
stop(M)
(a mode is defined by its start- and stop-events)
M
A borderline mode-example
2012-09-24..25 AMST Workshop - Berlin Slide 11
time
source
target
lowerupper
start(M)
stop(M)
Should this trace be accepted by the mode-dependent DelayConstraint?
There’s no matchingtarget occurrence inside M...
TADL2 thus chooses to answers yes! (the optimistic assumption)
... but a matching occurrence is stillpossible outside M(where we don’t look!)