Current version - Indiana University South Bend

IU SOUTH BEND COURSE DESCRIPTIONS 4297
CSCI-B 424
CSCI-B 438
CSCI-B 451
PARAllel and distributed programming
(3 cr.)
P: CSCI-C 243. P or C: MATH-M 301.
Overview of parallel computers, shared
memory, message passing, MIMD and
SIMD classifications. Understanding
and use of message passing and
synchronization facilities such as MPI.
Study of parallel programming models
such as master-slave, client-server,
task-farming, divide-and-conquer,
and pipelining. Performance analysis
of parallel systems, execution time,
time complexity, load balancing, and
scalability. Credit not given for both
CSCI-B 424 and CSCI-B 524.
fundamentals of COMPUTER
NETWORKS (3-4 cr.)
P: CSCI-C 243, CSCI-C 335. Fundamental
concepts and technologies used in design
of computer networks. Architecture
and design philosophy of Internet and
basic performance issues. Low-level
technologies like Ethernet and wireless.
Packet switching and virtual circuits. Core
protocols of the Internet, such as TCP and
IP. Error control, congestion control, and
routing.
security in COMPUTing (3 cr.)
P: CSCI-C 335. An introduction
to computing security to include
confidentiality, integrity and availability
triad, cryptography, software security,
operating system security, trusted
operating system design and evaluation,
authentication, network threats and
defenses, security management, legal
aspects of security, privacy and ethics.
CSCI-B 503 ALGORITHMS DESIGN AND ANALYSIS (3 cr.)
P: CSCI-C 243 and MATH-M 260 or
MATH-M 365 or MATH-M 463. Models,
algorithms, recurrences, summations,
growth rates. Probabilistic tools,
upper and lower bounds, worst-case
and average-case analysis, amortized
analysis, dynamization. Comparisonbased
algorithms: search, selection,
sorting, hashing. Information extraction
algorithms (graphs, databases). Graph
algorithms: spanning trees, shortest
paths, connectivity, depth-first, breadthfirst
search. Credit not given for both
CSCI-C503 and C455. II
CSCI-B 524
parallelism in Programming
languages and systems (3 cr.)
P: CSCI-C 243, MATH-M 301. Overview
of parallel computers, shared memory,
message passing, MIMD and SIMD
CSCI-B 538
CSCI-B 541
CSCI-B 551
CSCI-B 553
classifications. Understanding and use
of message passing and synchronization
facilities such as MPI. Study of parallel
programming models such as masterslave,
client-server, task-farming,
divide-and-conquer, and pipelining.
Performance analysis of parallel systems,
execution time, time complexity, load
balancing, and scalability. Credit not
given for both CSCI-B 524 and B424.
networks and distributed computing
(3 cr.)
P: CSCI-B 438. R: CSCI-C 435. Advanced
concepts and technologies of computer
networks. Protocols and protocol stacks.
Client-server models. Distributed object
technology. High-performance and
high-bandwidth techniques. Distributed
operating systems. I
hardware system design i (3 cr.)
P: CSCI-C 243, CSCI-C 335, PHYS-P
303. Structured approach to hardware
design, emphasizing hardwired and
microprogrammed control. Boolean
algebra, hardware building blocks,
architecture and control, implementation
issues. In the laboratory, students build
a working computer using hardware
prototyping technologies. Basic training
in the use of design and simulation
software. Lecture and laboratory. Credit
not given for both CSCI-B 541 and CSCI-C
421.
elementary artificial intelligence
(3 cr.)
P: CSCI-C 251. Major issues and
approaches in artificial intelligence.
Principles of reactive, goal-based, and
utility-based agents. Problem solving and
search. Knowledge representation and
design of representational vocabularies.
Inference and theorem proving, reasoning
under uncertainty, and planning.
Overview of machine learning. Credit not
given for both CSCI-B 551 and C463.
neural and genetic approaches to
artificial intelligence (3 cr.)
P: Permission of instructor. Biologicallyinspired
approaches to the design of
intelligent systems. Distributed and
perceptually-grounded representations.
Temporal processing. Neural-network
approaches to vision and natural language
processing. Evolutionary computation.
Additional topics may include an
introduction to analogy computing,
dynamical systems, and artificial life.