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1. (8/27) Discussion: Course introduction and logistics.

1. (9/3) Discussion: [CXH or JR] Version control (SVN)

1. (9/8) [JR away]
2. (9/10) Discussion [JR away]

1. (10/13) [SS away]
2. (10/15) Discussion [SS away]

1. (11/8) [SS and JR away, tentatively]
2. (11/10) [SS and JR away, tentatively]

  ** Introduction to computer-aided design methodologies (RTL, TLM, Analog, CPS)

1. Software Engineering (consult Andreas)

   • Version control: SVN
   • Eclipse
   • Working with open-source code
   • Copyrights and licenses
   • Language features: templates, operator overloading
   • When to use what language
   • Building on Ptolemy II

Suggested Projects

1. Scheduling dataflow graphs for minimum memory usage.
2. Scheduling dataflow graphs on parallel processors.

1. (8/27) Discussion
2. (8/30)
3. (9/1)
4. (9/3) Discussion
5. (9/6) Holiday
6. (9/8)
7. (9/10) Discussion
8. (9/13)
9. (9/15)
10. (9/17) Discussion
11. (9/20)
12. (9/22)
13. (9/24) Discussion
14. (9/27)
15. (9/29) [MuSyC review]
16. (10/1) Discussion
17. (10/4) [EAL away]
18. (10/6) [EAL away]
19. (10/8) Discussion [EAL away]
20. (10/11)
21. (10/13)
22. (10/15) Discussion
23. (10/18)
24. (10/20)
25. (10/22) Discussion
26. (10/25) [ESWeek, EAL away]
27. (10/27) [ESWeek, EAL away]
28. (10/29) Discussion [ESWeek, EAL away]
29. (11/1)
30. (11/3)
31. (11/5) Discussion
32. (11/8)
33. (11/10)
34. (11/12) Discussion
35. (11/15)
36. (11/17)
37. (11/19) Discussion
38. (11/22)
39. (11/24)
40. (11/26) Holiday: Thanksgiving
41. (11/29)
42. (12/1)
43. (12/3) Discussion: Last day of instruction

Topics

  ** Introduction to computer-aided design methodologies (e.g. Register-Transfer-Level: RTL, Transaction-level modeling: TLM)
  ** Analog CAD, cyber-physical systems

  ** Modeling, problem formulation, abstraction/refinement, nondeterminism, discrete vs. continuous.

1. From Algorithms to Software

   • Complexity and modularity
   • Concurrency and parallelism
   • Parallel programming for dynamic programming and graph algorithms.
2. Algorithms for Continuous Models

   • Solving nonlinear equations (e.g. Newton-Raphson)
   • Solving continuous-time dynamics numerically (transient concepts)
   • Continuous-time frequency domain concepts and computational algorithms
   • Continuous-time stochastics
3. Emerging problem spaces: Biosystems, cyber-physical systems, nanotechnology

  ** Timing analysis for circuits and embedded software (common themes: True (feasible) vs. False (infeasible) paths)
  ** Hash functions (e.g. in Discrete-event simulations, use of a calendar queue for maintaining an event queue)
  ** Linear programming and ILP [several applications -- which ones to cover?]
  ** Observability and controllability (Testing for stuck-at & delay faults, Controller synthesis?)
  ** Basic Boolean algebra: cube, minterm, Boolean operations, factorization, etc. (Logic synthesis and optimization)
  ** Boolean function representation & manipulation (BDDs): Equivalence checking, model checking, etc.
  ** Boolean satisfiability (SAT): Equivalence checking of combinational circuits (aka "implementation verification")
  ** Reachability analysis & temporal logic: Formal verification: Sequential equivalence checking, model checking
  ** Scheduling algorithms: dataflow models, managing event queues, parallel scheduling (multicore, high-level circuit synthesis).

1. Introduction:

   • Introduction to computer-aided design methodologies (e.g. Register-Transfer-Level: RTL, Transaction-level modeling: TLM)
   • Examples of problem domains: integrated circuits, biosystems, nanosystems, smart buildings, etc.
2. Algorithms for Discrete Models (with their applications)

   • Longest/shortest path in a DAG

• Introduction: - Introduction to computer-aided design methodologies (e.g. Register-Transfer-Level: RTL, Transaction-level modeling: TLM) - Examples of problem domains: integrated circuits, biosystems, nanosystems, smart buildings, etc.
• Algorithms for Discrete Models (with their applications) + Longest/shortest path in a DAG

    - Timing analysis for circuits and embedded software
      . True (feasible) vs. False (infeasible) paths

+ Hash functions

    - Discrete-event simulations (e.g. in calendar queue for maintaining an
      event queue)
    - other applications? 
  + Linear programming and ILP 
    [several applications -- which ones to cover?]
  + Observability and controllability 
    - Testing for stuck-at & delay faults
    - Controller synthesis ?
  + Basic Boolean algebra: cube, minterm, Boolean operations, factorization, etc.
    - Logic synthesis and optimization
  + Boolean function representation & manipulation (BDDs)
    - Equivalence checking, model checking, etc.
  + Boolean satisfiability (SAT)  
    - Equivalence checking of combinational circuits (aka "implementation verification")
  + Reachability analysis & temporal logic
    - Formal verification: Sequential equivalence checking, model checking
  + Scheduling algorithms
    - dataflow models, managing event queues 
    - other applications?

• Algorithms for Continuous Models - Solving nonlinear equations (e.g. Newton-Raphson) - Solving continuous-time dynamics numerically (transient concepts) - Continuous-time frequency domain concepts and computational algorithms - Continuous-time stochastics
• From Algorithms to Software - Complexity and modularity - Concurrency and parallelism

1. Parallel programming for dynamic programming and graph algorithms.

1. Reachability analysis and temporal logic: model checking

1. Boolean modeling: True (feasible) vs. False (infeasible) paths. Basic Boolean algebra: cube, minterm, Boolean operations, factorization, etc.
2. Solving SAT problems.
3. BDDs
4. Logic synthesis and optimization

1. Longest/shortest path in a DAG. Timing analysis for circuits and embedded software.
2. Modeling, problem formulation, abstraction/refinement, nondeterminism, discrete vs. continuous.
3. Modeling continuous systems 1.
4. Modeling continuous systems 2.
5. Boolean modeling: True (feasible) vs. False (infeasible) paths.

1. Emerging problem spaces: Biosystems, cyber-physical systems, nanotechnology

1. Intro problem space (CAD (RTL, TLM), software, circuits).

2. Emerging problem spaces: Biosystems, cyber-physical systems

1. Intro problem space (CAD (RTL, TLM), software, cyber-physical, circuits).
2. Longest/shortest path in a DAG. Timing analysis for circuits and embedded software. True (feasible) vs. False (infeasible) paths.
3. Modeling, problem formulation, abstraction/refinement, nondeterminism.

Lecture outline (Fall 2010, 27 lectures)

1. Intro problem space
2. Longest/shortest path in a DAG. Timing analysis for circuits and embedded software. True (feasible) vs. False (infeasible) paths

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