How Can This Initiative Succeed? Mohamed G. Gouda National Science Foundation The University of Texas at Austin February 2010

To Succeed in This (and Any) Mission Be realistic (in our expectation) Be focused (on our most important goal) Be humble (in our planning)

Be Realistic (in our expectation) Do not expect that we will (or can) agree on a set of topics for a good curriculum on distributed and parallel computing spanning: K-12, undergraduate, and graduate education Even if we do agree on such a set, do not expect that the rest of the world will agree with us on this set

Be Focused (on our most important goal) Our most important goal is not to teach our students a new set of topics or facts about distributed and parallel computing. Our most important goal is to teach our students how to develop and use mental capabilities that are needed to reason about distributed and parallel computing: How to reason about nondeterminism How to reason about parallelism

Be Humble (in our planning) The graduate curriculum on distributed and parallel computing in our universities is mostly unbroken. So let us not try to fix it. Let us resist the temptation to introduce required undergraduate courses on distributed and parallel computing. Simply let us try to enhance existing required courses with some topics related to distributed and parallel computing. Can we think of an advanced High School class that urges students to think of nondeterminism and parallelism?

Advantage of Distributed and Parallel Computing Most disciplines of Computer Science, other than distributed and parallel computing, require thinking of sequentiality, just like Algebra and Calculus do Thus, teaching any of these disciplines in high-school does not provide students with new experiences Distributed computing requires students to think of nondeterminism – A new experience! Parallel computing requires students to think of parallelism – A new experience!

High-School Course on Distributed and Parallel Computing This course first introduces the “computation graph” model It then proceeds to use this model in presenting simple theories of scheduling Code generation Synchronization Fault-tolerance Consistency control