Session Application: pdf
Session slides: pptx, pdf
All session materials: zip, readme

Introductory Python:

• pythonCrashCourse.py: for those familiar with programming but not Python.
• pythonIntro.py: also including list comprehensions (pythonIntro3.py)

Processes, communication:

• spawningProcesses.py: processes, locks
• communication.py: queues for communication between processes
• speedup.py: parallel versus sequential timings

Pool/map:
Pool-based methods cannot be run through the IDLE shell (see here).

$python[3] file.py

• parallelHello.py
• pools.py
• parallelSumPrimes.py
• parallelMontePi.py: Monte Carlo estimation of &pi
• parallelIntegration.py: Riemann sum

Sorting:

• parallelQuicksort.py: using Process/Pipe
• parallelMergesort.py: using Process/Pipe
• parallelMergesortPool.py: using Pool/map
• C-Pthreads references: parallelQuicksort.c, parallelMergesort.c

Parallel Image Processing: forthcoming

• parallelImageSepia.py: using Pool/map and scipy/PyOpenCV
• additional examples of Photoshop effects applied to images in parallel (color vibrancy, sketch, etc.)

Grid Computing: continuing development

• DistributedPython: See the README. This zip contains all the code, along with testSubmitMaster.py,
  the top level code that simply generates the commands and requests they be executed in parallel (via
  the processCommandsInParallel function in submitMaster.py).
• Further examples using DistributedPython to parallelize embarassingly parallel problems, like DNA
  sequence 'blasting', Monte Carlo runs on stock prices, etc.

Applications:

• applications.py: clustering, pipelined floating point addition
  

Test/quiz questions on PDC:

• SampleQuestions.pdf: extensive examples.
• prog6.pdf, and tex file: brief CS2-apropriate assignment.
• quiz12.pdf, and tex file: fun quiz example introducing parallelism.

We gratefully acknowledge the support of:

• NSF-TCPP Core Curriculum Initiative on Parallel and
  Distributed Computing Early Adopter Award.


• National Science Foundation through grant
  CCF-0915805, SHF:Small:RUI:Collaborative Research:
  Accelerators to Applications - Supercharging the
  Undergraduate Computer Science Curriculum.