CS2013-final-report

• Data races and higher-level race conditions
• Deadlock
• Condition variables
What is the format of the course
This is a fairly conventional course with 3 weekly 1-hour lectures and 1 weekly recitation section led by a teaching
assistant. The recitation section often covers software-tool details not covered in lecture. It is a 10-week course
because the university uses a “quarter system” with 10-week terms.
How are students assessed
Students complete 8 written homework assignments, 3 programming projects in Java (1 using parallelism), a
midterm, and a final exam.
Course textbooks and materials
For the classic data structures material, the textbook is Data Structures and Algorithm Analysis in Java by Weiss.
For parallelism and concurrency, materials were developed originally for this course and are now used by several
other institutions (see URL below). Programming assignments use Java, in particular Java’s Fork-Join Framework
for parallelism.
Why do you teach the course this way
Clearly the most novel feature of this course is the integration of multithreading, parallelism, and concurrency.
The paper “Introducing Parallelism and Concurrency in the Data Structures Course” by Dan Grossman and Ruth
E. Anderson, published in SIGCSE2012, provides additional rationale and experience for this approach. In short,
data structures provides a rich source of canonical examples to motivate both parallelism and concurrency.
Moreover, an introduction to parallelism benefits from the same mix of algorithms, analysis, programming, and
practical considerations that is the main ethos of the data structures course.
Body of Knowledge coverage
KA Knowledge Unit Topics Covered Hours
AL Basic Analysis All except the Master Theorem 3
AL
Fundamental Data
Structures and
Algorithms
All topics except string/text algorithms. Also, the preceding CS2
course covers some of the simpler topics, which are then quickly
reviewed
10
AL
Advanced Data
Structures Algorithms
and Analysis
Only these: AVL trees, topological sort, B-trees, and a brief
introduction to amortized analysis
6
DS Graphs and Trees All topics except graph isomorphism 3
PD Parallelism Fundamentals All 2
PD Parallel Decomposition All topics except actors and reactive processes, but at only a
cursory level
1
PD
Communication and
Coordination
All topics except Consistency in shared memory models, Message
passing, Composition, Transactions, Consensus, Barriers, and
Conditional actions. (The treatment of atomicity and deadlock is
also very elementary.)
2
PD
Parallel Algorithms,
Analysis, and
Programming
All Core-Tier-2 topics; none of the Elective topics 4
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