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CS 111.03 Introduction to Computer Science 6 credits

Open: Size: 34, Registered: 27, Waitlist: 0

Location To Be Announced

MTWTHF
7:00pm8:10pm7:00pm8:10pm7:00pm8:00pm
Synonym: 58542

David R Musicant

This course will introduce you to computer programming and the design of algorithms. By writing programs to solve problems in areas such as image processing, text processing, and simple games, you will learn about recursive and iterative algorithms, complexity analysis, graphics, data representation, software engineering, and object-oriented design. No previous programming experience is necessary. Students who have received credit for Computer Science 201 or above are not eligible to enroll in Computer Science 111.

CS 348.00 Parallel and Distributed Computing 6 credits

Open: Size: 34, Registered: 33, Waitlist: 0

Location To Be Announced

MTWTHF
10:00am11:10am10:00am11:10am9:50am10:50am
Synonym: 58566

David R Musicant

As multi-core machines become more prevalent, different programming paradigms have emerged for harnessing extra processors for better performance. This course explores parallel computation (programs that run on more than one core) as well as the related problem of distributed computation (programs that run on more than one machine). In particular, we will explore the two major paradigms for parallel programming, shared-memory multi-threading and message-passing, and the advantages and disadvantages of each. Other possible topics include synchronization mechanisms, debugging concurrent programs, fork/join parallelism, the theory of parallelism and concurrency, parallel algorithms, cloud computing, and Map/Reduce.

Prerequisite: Computer Science 201

CS 348.01 Parallel and Distributed Computing 0 credits

Closed: Size: 1, Registered: 1, Waitlist: 0

Location To Be Announced

MTWTHF
10:00am11:10am10:00am11:10am9:50am10:50am
Synonym: 59860

David R Musicant

As multi-core machines become more prevalent, different programming paradigms have emerged for harnessing extra processors for better performance. This course explores parallel computation (programs that run on more than one core) as well as the related problem of distributed computation (programs that run on more than one machine). In particular, we will explore the two major paradigms for parallel programming, shared-memory multi-threading and message-passing, and the advantages and disadvantages of each. Other possible topics include synchronization mechanisms, debugging concurrent programs, fork/join parallelism, the theory of parallelism and concurrency, parallel algorithms, cloud computing, and Map/Reduce.

Prerequisite: Computer Science 201

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You must take 6 credits of each of these.
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You must take 6 credits of each of these,
except Quantitative Reasoning, which requires 3 courses.
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