Environment Modeling in Quasi- Static Scheduling EE249 Project Donald Chai Mentors: Alex Kondratyev, Yoshi Watanabe.

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Environment Modeling in Quasi- Static Scheduling EE249 Project Donald Chai Mentors: Alex Kondratyev, Yoshi Watanabe

Environment Modeling in QSS2 Outline Motivation Method for QSS Problems Environment Modeling Conclusions

Environment Modeling in QSS3 Motivation Schedule some set of processes on one CPU Dynamic scheduling requires overhead for communication and context switching Static scheduling minimizes context switching overhead—scheduling for BDF is undecidable QSS is a compromise, somewhat like cooperative multitasking by inserting sleep s

Environment Modeling in QSS4 QSS Input Specification comes in FlowC (YAPI framework) Sequential processes communicate over FIFO channels, a process may  READ, WRITE  SELECT nondeterministically from a set of ready input ports

Environment Modeling in QSS5 QSS Algorithm FlowC descriptions are translated into a Petri Net The Petri Net is partitioned into single source schedules. QSS is a game between the scheduler and the environment.

Environment Modeling in QSS6 Example A system that is not schedulable Is schedulable in the right environment From Clarisó, Cortadella, Kondratyev, Lavagno, Passerone, Watanabe, INT2002

Environment Modeling in QSS7 Environment Model Input ports may be fully uncontrollable or fully controllable No known relation between inputs Output ports are always fully controllable

Environment Modeling in QSS8 Problems Boundedness (previous example) Deadlock (two processes B,A, sequenced by the environment into A,B) Interference (arbitration)

Environment Modeling in QSS9 Environment Modeling The form we should use is asymmetric: Sys abs is QSS schedulable · is the trace containment relation Assume-guarantee proof rule states:

Environment Modeling in QSS10 Approaches Assume some environment during scheduling, check this. Construct an abstract environment. (correct by construction) Restrict the power of our model of computation.

Environment Modeling in QSS11 Assume, then Guarantee “Try and see” Basically we generate a trace of the assumptions made Not very robust, and very compute intensive 42

Environment Modeling in QSS12 Guarantee First The environment is abstracted using a set of reduction rules Can be done via trace algebra projection, but may be overkill

Environment Modeling in QSS13 Example (I) Arbiter ModuleArbiter + Process

Environment Modeling in QSS14 Example (II) SELECT is reducedMore reductions

Environment Modeling in QSS15 Expressiveness Processes look like FCPNs (free choice from if statements) When add READs and SELECTs, looks more like asymmetric choice

Environment Modeling in QSS16 Future Work Partitioning is used extensively for equivalence checking of circuits. What would be good places to partition the environment?