CSinParallel Modules and the Topics in the Curriculum 2013 Core Libby Shoop Math, Statistics, and Computer Science Macalester College.

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Presentation transcript:

CSinParallel Modules and the Topics in the Curriculum 2013 Core Libby Shoop Math, Statistics, and Computer Science Macalester College

The CSinParallel Project Modular PDC material for CS courses – Short units Conceptual Active – Add to different courses Many CSinParallel modules have CS2013 PDC concepts and topics, both core tier 1 and 2

Modules Provide intro reading and class activities Online or you can download and edit yourself We’re working on adding more corresponding homework problems for depth, demonstration aspects of the curriculum guidelines

CS Curriculum 2013 (CS2013) To accommodate different kinds of programs, CS2013 spreads the CS “core” knowledge units (KUs) across two tiers: – All programs should cover 100% of the Tier 1 KUs – Programs should cover 80-90% of the Tier 2 KUs Different programs may decide to cover different Tier 2 KUs.

Module Coverage: PD, SF Introductory Parallel Concepts Patternlets in Parallel Programs Multicore Programming with OpenMP Concurrent Access to Data Structures – Java and C++ Parallel Sorting Introduction to Map-Reduce Distributed Computing Fundamentals GPU computing Heterogeneous computing Exemplar applications: drug design, pandemic epidemiology Stay tuned… More on the way! Tier 1 Tier 2,E

Story: a mapping exercise Gave me insight into what we chose to emphasize so far in the modules Gives me ideas for new material

CS2013 Knowledge Areas

Levels of Mastery in Learning Objectives Familiarity Usage – Apply Assessment – Choose between alternatives

What is in SF (p. 186)?

Parallel Computing Concepts Patternlets Multicore Programming with Open MP

Parallel Computing Concepts Patternlets Multicore Programming with Open MP Introduction to Map-Reduce Exemplars: Drug Design and Pandemic

Parallel Computing Concepts Multicore Programming with Open MP Exemplars: Drug Design and Pandemic

What is in PD (p. 147)?

PD, p. 145 Because parallelism interacts with so many areas of computing, … many curricula will put different parts of the knowledge area in different courses, rather than in a dedicated course. While we acknowledge that computer science is moving in this direction and may reach that point, in 2013 this process is still in flux and we feel it provides more useful guidance to curriculum designers to aggregate the fundamental parallelism topics in one place

Parallel Computing Concepts Patternlets Multicore Programming with Open MP

Parallel Computing Concepts Patternlets Multicore Programming with Open MP Drug design exemplar Pandemic exemplar

Parallel Computing Concepts Patternlets Multicore Programming with Open MP Distributed Computing Fundamentals Concurrent Access to Data Structures

Parallel Computing Concepts Patternlets Parallel Sorting Introduction to Map-Reduce

Topics :

Parallel Computing Concepts Patternlets Multicore Programming with Open MP Distributed Computing Fundamentals