Number of transistors per
chip continues to follow
Moore’s Law; but the
transistors are going into
multiple cores, bigger
cache, bridge technology,
etc
But in 2003, clock
speed hit a wallWhere are the
32GHz
processors?
Parallel & Distributed Computing (PD) is
now its own Knowledge Area (KA).
 Architecture and Organization (AR) is 16
Tier 2 core hours
 PD is 5 Tier 1 hours, and 10 Tier 2 hours.
 PD is seen as critical to many other KA’s,
and can properly be placed there;
Strawman seems to indicate a standalone course is fastest way to get up and
running now.

http://www.cs.gsu.edu/~tcpp/curriculum/
 Using a Bloom’s taxonomy of KnowComprehend-Apply this group proposes
some 90 hours of instruction in PD
 Only about 15 hours at the “Apply” level
 They see 5 core courses involved, and a
larger list of upper division electives

› CS1, CS2, Architecture, DataStruc/Algor,
Discrete
ACM SIGCSE 2009 (Chattanooga)
 Dr. Michael Wrinn (Intel Senior Course Architect):

› Intel is not going to be making
any single core processors. The
world has already gone parallel
and you better start teaching
parallel computing to your
students.
The Free Lunch is over
 Professional societies have served notice
that our curricula must include PD.
 The world in which our students will live
their careers will be a parallel world. It is
already a multicore world.
 It must begin as early as CS1/CS2

Intel microgrant program to develop PD
curricular material
 ACM SIGCSE “Nifty Programming
Assignments”

› Nick Parlante at nifty.stanford.edu
If we want to target CS1/CS2, why not begin
with those assignments the SIGCSE
community has already endorsed as nifty?
 My thanks to the 2011 Nifty Authors for their
gracious permission to use their work

› DO NOT MAKE SOURCE CODE AVAILABLE
Take students’ serial solution to a
problem and add parallelism by
“grabbing the low-hanging fruit”.
 We use C++ in the MS Visual Studio.NET
IDE
 The Intel Parallel Studio, especially the
Parallel Advisor, is a natural choice.

› Parallel Studio is also available for Unix as a
stand-alone product, both as command line
& GUI

Trapezoidal Numerical Integration
› Not a “nifty”, but is embarrassingly parallel

BMP puzzles: who done it?
› David Malan, Harvard University

Book Recommendations: look out Netflix
› Michele Craig, University of Toronto

Hamming Codes: old school error correction
› Stuart Hansen, University of Wisconsin-Parkside

Evil Hangman: cheating is a strategy!
› Keith Schwarz, Stanford University
A classic Numerical Methods technique
 Improves upon Riemann sums by adding
area of trapezoids rather than simple
rectangles.

b

a
ba
 f ( x1)  2 f ( x2)  2 f ( x3)  ... 2 f ( xN )  f ( xN  1)
f ( x)dx 
2N
N = number of subintervals
 Obviously a big for-loop to add the f(x)’s

Mr. Body has met foul play. But he left a
“Clue” to his murderer’s identity by
coding the green & blue pixel values in a
harmless-looking BMP image. The red
pixels merely obscure the message
 So process the 2D array of pixels in the
BMP, suppressing red and enhancing
green/blue to find the killer.
 2D arrays & parallel for loops is a natural

Given a list of books, have a set of
readers give their rating of the book [-5
to +5]. Then take a new reader and
comparing her ratings to your total
population, make the appropriate book
recommendations to her.
 Computing dot products (actually just
about any array processing) in an O(n2)
environment is a parallel dream


Prof Hansen uses this assignment to teach:
› Error correcting codes
› Matrix multiplication
› Binary representations of data
› Binary I/O (optional)
Use a generator matrix and a parity check
matrix to manipulate Hamming(7,4)
 Matrix multiplication (even tiny matrices) is
bull's-eye parallel fodder.

Find a big list of words. Challenge a
human to solve Hangman. The wrinkle is
that the computer never actually picks a
word till it is forced to do so.
 For every human guess, find the largest
subset of words possible
 For example: HEAR_
(can be HEARD, HEART, HEARS)
 Essentially impossible to beat in 10
guesses.
