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Research in this
area focuses on the design and analysis of algorithms and data
structures for problems arising in several areas of computer science,
including automatic software verification, computational geometry, data
mining, and machine learning.
Research in this area includes developing efficient and scalable
algorithms for biomolecular simulation and applying data mining,
statistical machine learning, natural language processing, and
information retrieval to analyze and mine all kinds of biological data,
including DNA sequences, protein sequences and structures, microarray
data, and biology literature, for the purpose of facilitating biology
discovery.
Networking and distributed
systems group research includes a broad range of topics that include
mobile systems, wireless protocols, ad-hoc networks, Quality of Service
management, multimedia networking, peer-to-peer networking, routing,
network simulations, active queue management, and sensor networks.
Security research includes dynamic security architectures; security for
active networks; privacy, authentication, authorization, access control,
and trust in ubiquitous computing environments that have mobile users;
authentication in sensor networks; specification and validation of
security access control policies; simulation of network security
problems and solutions including denial of service; and next generation
phone security.
Individuals working in
the specialty area of scientific computing conduct research on the
development and analysis of numerical techniques for approximating
mathematical models of physical systems and on algorithms for solving
the resulting equations on high performance computer systems. Specific
scientific and engineering applications considered include biological
molecular dynamics, materials science, semiconductor si
Computer Science
LISA MEEDEN, Professor and Chair
TIA NEWHALL, Associate Professor
RICHARD WICENTOWSKI, Associate Professor and Associate Provost
ANDREW DANNER, Assistant Professor
AMEET SONI, Assistant Professor
KEVIN WEBB, Assistant Professor
JOSHUA BRODY, Visiting Assistant Professor
JASON WATERMAN, Visiting Assistant Professor
BENJAMIN YLVISAKER, Visiting Assistant Professor
FRANCES RUIZ, Academic Support Coordinator
JEFFREY KNERR, System Administrator and Visiting Instructor
BRIDGET M. ROTHERA, Administrative Assistant
TIA NEWHALL, Associate Professor
RICHARD WICENTOWSKI, Associate Professor and Associate Provost
ANDREW DANNER, Assistant Professor
AMEET SONI, Assistant Professor
KEVIN WEBB, Assistant Professor
JOSHUA BRODY, Visiting Assistant Professor
JASON WATERMAN, Visiting Assistant Professor
BENJAMIN YLVISAKER, Visiting Assistant Professor
FRANCES RUIZ, Academic Support Coordinator
JEFFREY KNERR, System Administrator and Visiting Instructor
BRIDGET M. ROTHERA, Administrative Assistant
Computer science is the study of algorithms and their implementation.
This includes the study of computer systems; methods to specify
algorithms (for people and computer systems); and the formulation of
theories and models to aid in the understanding and analysis of the
properties of algorithms, computing systems, and their
interrelationship.
The computer science curriculum is designed to provide students with a flexible set of computing choices that can be tailored to satisfy various interests and depths of study. All courses emphasize the fundamental concepts of computer science, treating today’s languages and systems as current examples of the underlying concepts. The computer science laboratory provides up-to-date software and hardware facilities.
The Computer Science Department offers course majors and minors and
honors majors and minors. Students interested in any of these options
are encouraged to meet with the chair of the Computer Science
Department as early as possible in their college career. Students who
are interested in a computer science major or minor are encouraged to
take CPSC 021, CPSC 031 and CPSC 035
sometime in their first four semesters at Swarthmore. The minor in
computer science is designed for students who desire a coherent
introduction to the core topics in the field. Students completing the
minor will possess intellectual skills that are useful in many
disciplines.
CPSC 031: Introduction to Computer Systems assumes that the student has completed CPSC 021 or its equivalent. It is the best entry point for students intending to be Computer Science majors or minors who already have extensive computing experience.
CPSC 035: Data Structures and Algorithms assumes that the student has completed CPSC 021 or its equivalent. It is an appropriate entry point for students with extensive computing experience.
Students who think they may qualify for CPSC 031 or CPSC 035 and have not taken CPSC 021 should see the instructor or department chair. Students or advisers who want more advice on placement in computer science courses should feel free to contact any computer science faculty member by phone or in person.
The Computer Science department offers three courses approved as cognitive science courses: CPSC 063 (Artificial Intelligence), CPSC 065 (Natural Language Processing) and CPSC 081 (Adaptive Robotics). Students with an interest in Cognitive Science are encouraged to consider COGS 001 (Introduction to Cognitive Science).
In addition to courses offered by computer science faculty, the department recommends that students with an interest in computer engineering consider courses offered by the Engineering department, including three courses that are cross-listed by the Computer Science department: CPSC 052 (Computer Architecture), CPSC 072 (Computer Vision) and CPSC 082 (Mobile Robotics).
The following are the requirements for a major in computer science:
The minor in computer science provides students with a well-rounded
background in computer science sufficient to develop significant,
creative applications and to keep up with the rapid changes in the
field.
The following are the requirements for a minor in computer science:
Honors Major
An honors major in computer science will consist of completion of the course major, two 2-credit preparations, one 2-credit research report or thesis.
The following will be submitted to external examiners for evaluation:
Two 2-credit preparations to be selected from the combinations of courses listed under Approved Preparations. Each of these 2-credit preparations will be examined by a 3-hour written examination and an oral examination.
The two 2-credit preparations must include four distinct courses. In certain circumstances, the Computer Science Department may be willing to consider other groupings of courses, seminars, or courses with attachments. If the required courses and preparations would not satisfy a course major, additional computer science courses must be taken to meet course major requirements. In all cases, the Computer Science Department must approve the student’s plan of study.
One research report or thesis to be read by an external examiner and examined in an oral examination.
At a minimum, this will involve a review of scholarly papers from the primary literature of computer science and the writing of a scholarly, scientific paper. The paper will report on a research experience involving the student and faculty (here or elsewhere). It is expected that most of the research or scholarly groundwork will be completed before the fall semester of the senior year, either by 1 credit of work in the spring semester of the junior year or full-time summer work. Students will register for at least 1 credit of thesis work to complete the work and write the paper in the fall of the senior year. It is recommended that the paper be completed by the end of the fall semester.
An honors minor in computer science will consist of completion of the course minor and one 2-credit preparation.
The following will be submitted to external examiners for evaluation:
One 2-credit preparation to be selected from the combinations of courses listed under Approved Preparations. This 2-credit preparation will be examined by a 3-hour written examination and an oral examination.
The 2-credit preparation must include two distinct courses. In certain circumstances, the Computer Science Department may be willing to consider other groupings of courses, seminars, or courses with attachments. If the required courses and preparations would not satisfy a course minor, additional computer science courses must be taken to meet course minor requirements. In all cases, the Computer Science Department must approve the student’s plan of study.
The computer science curriculum is designed to provide students with a flexible set of computing choices that can be tailored to satisfy various interests and depths of study. All courses emphasize the fundamental concepts of computer science, treating today’s languages and systems as current examples of the underlying concepts. The computer science laboratory provides up-to-date software and hardware facilities.
The Academic Program
First course recommendations
CPSC 021: Introduction to Computer Science presents fundamental ideas in computer science while building skill in software development. No previous experience with computers is necessary. This course is appropriate for all students who want to write programs. It is the usual first course for computer science majors and minors. Students with Advanced Placement credit or extensive programming experience may be able to place out of this course.CPSC 031: Introduction to Computer Systems assumes that the student has completed CPSC 021 or its equivalent. It is the best entry point for students intending to be Computer Science majors or minors who already have extensive computing experience.
CPSC 035: Data Structures and Algorithms assumes that the student has completed CPSC 021 or its equivalent. It is an appropriate entry point for students with extensive computing experience.
Students who think they may qualify for CPSC 031 or CPSC 035 and have not taken CPSC 021 should see the instructor or department chair. Students or advisers who want more advice on placement in computer science courses should feel free to contact any computer science faculty member by phone or in person.
Interdisciplinary recommendations
The department recommends that students with an interest in computer science should consider using MATH 027 (Linear Algebra) and/or MATH 029 (Discrete Math) to satisfy the math requirement for the major and minor. Statistics courses at the level of STAT 031 (Data Analysis and Visualization) or above can also be used to satisfy the math requirement.The Computer Science department offers three courses approved as cognitive science courses: CPSC 063 (Artificial Intelligence), CPSC 065 (Natural Language Processing) and CPSC 081 (Adaptive Robotics). Students with an interest in Cognitive Science are encouraged to consider COGS 001 (Introduction to Cognitive Science).
In addition to courses offered by computer science faculty, the department recommends that students with an interest in computer engineering consider courses offered by the Engineering department, including three courses that are cross-listed by the Computer Science department: CPSC 052 (Computer Architecture), CPSC 072 (Computer Vision) and CPSC 082 (Mobile Robotics).
The following are the requirements for a major in computer science:
- Nine courses in computer science:
- Two MATH/STAT courses at the level of Linear Algebra or above (Discrete Math and Linear Algebra are recommended).
Course Minor
The following are the requirements for a minor in computer science:
- Six courses in computer science.
- CPSC 021. (If exempted from CPSC 021 without AP credit, substitute one course from any Group listed below.)
- CPSC 031 or CPSC 033.
- CPSC 035.
- Two upper-level courses drawn from different groups:
- Group 1: CPSC 041 or CPSC 046.
- Group 2: CPSC 043, CPSC 044, CPSC 045, CPSC 075, or CPSC 087.
- Group 3: CPSC 037, CPSC 040, CPSC 063, CPSC 065, CPSC 068, CPSC 071, CPSC 081
- One CPSC course numbered above CPSC 035 (must be different than the choices in part c).
- One MATH/STAT course at the level of Linear Algebra or above (Discrete Math recommended).
Honors Major
An honors major in computer science will consist of completion of the course major, two 2-credit preparations, one 2-credit research report or thesis.
The following will be submitted to external examiners for evaluation:
Two 2-credit preparations to be selected from the combinations of courses listed under Approved Preparations. Each of these 2-credit preparations will be examined by a 3-hour written examination and an oral examination.
The two 2-credit preparations must include four distinct courses. In certain circumstances, the Computer Science Department may be willing to consider other groupings of courses, seminars, or courses with attachments. If the required courses and preparations would not satisfy a course major, additional computer science courses must be taken to meet course major requirements. In all cases, the Computer Science Department must approve the student’s plan of study.
One research report or thesis to be read by an external examiner and examined in an oral examination.
At a minimum, this will involve a review of scholarly papers from the primary literature of computer science and the writing of a scholarly, scientific paper. The paper will report on a research experience involving the student and faculty (here or elsewhere). It is expected that most of the research or scholarly groundwork will be completed before the fall semester of the senior year, either by 1 credit of work in the spring semester of the junior year or full-time summer work. Students will register for at least 1 credit of thesis work to complete the work and write the paper in the fall of the senior year. It is recommended that the paper be completed by the end of the fall semester.
Acceptance Criteria
To be eligible for an honors major in computer science, students must complete the following:- Have a B+ average in all computer science courses completed by the end of junior year. These must include CPSC 021 and CPSC 035, and at least two of, CPSC 031, CPSC 037, CPSC 041, CPSC 046 or CPSC 075.
- Have demonstrated proficiency in mathematical argument and
reasoning by the end of the junior year. Ordinarily, this proficiency
will be assumed if the student has done one of the following:
- Completed Discrete Mathematics and Linear Algebra with a grade of B+ or better
- Completed Linear Algebra Honors with a grade of B or better
- Completed Introduction to Real Analysis or Introduction to Modern Algebra with a grade of B- or better
- Completed by the end of the senior year a set of courses that would qualify for an ordinary computer science major as well as CPSC 180 (Thesis).
Honors Minor
The following will be submitted to external examiners for evaluation:
One 2-credit preparation to be selected from the combinations of courses listed under Approved Preparations. This 2-credit preparation will be examined by a 3-hour written examination and an oral examination.
The 2-credit preparation must include two distinct courses. In certain circumstances, the Computer Science Department may be willing to consider other groupings of courses, seminars, or courses with attachments. If the required courses and preparations would not satisfy a course minor, additional computer science courses must be taken to meet course minor requirements. In all cases, the Computer Science Department must approve the student’s plan of study.
Acceptance Criteria
To be eligible for an honors minor in computer science, a student must satisfy course requirements for a regular minor in computer science and in addition:- Have a B+ average in all computer science courses completed by the end of the junior year.
- Take one 2-credit preparation to be selected from the combinations of courses listed under Approved Preparations. An examiner will set both a 3-hour written examination and an oral examination for the preparation.
Approved Preparations for the Honors Major and Minor
The following are the approved preparations. These may not all be available to all students because of the faculty’s schedules.Preparation |
Course Combinations |
|
Algorithms and Theory |
CPSC 041. Algorithms CPSC 046. Theory of Computation |
|
Intelligent Systems |
CPSC 063. Artificial Intelligence CPSC 081. Adaptive Robotics |
|
Parallel and Distributed Systems |
CPSC 045. Operating Systems CPSC 087. Parallel and Distributed Computing |
|
Natural Language Models |
CPSC 063. Artificial Intelligence CPSC 065. Natural Language Processing |
|
High-performance Computing |
CPSC 40. Computer Graphics CPSC 87. Parallel and Distributed Computing |
| Network Systems |
CPSC 43. Computer Networks CPSC 45. Operating Systems |
| Distributed Computing |
CPSC 43. Computer Networks CPSC 87. Parallel and Distributed Computing |
| Data Systems |
CPSC 44. Database Systems CPSC 45. Operating Systems |
| Statistical Machine Learning |
CPSC 65. Natural Language Processing CPSC 68. Bioinformatics |
| Bioinformatics |
CPSC 63. Artificial Intelligence CPSC 65. Natural Language Processing |
|
Programming Languages and Compilers |
CPSC 037. Structure and Interpretation of Computer Programs CPSC 075. Compiler Design and Construction |
|
Parallel Systems and Algorithms |
CPSC 041. Algorithms CPSC 087. Parallel and Distributed Computing |
Thesis / Culminating Exercise
Senior Conference is the comprehensive requirement for computer science course and honors majors. It provides an opportunity to delve more deeply into a particular topic in computer science, synthesizing material from previous courses.Application Process and Acceptance Criteria for Majors/Minors
Advanced Placement
Off-Campus Study
Life After Swarthmore
Graduate School
Students interested in graduate study in computer science will be well prepared with a computer science major. Some graduate programs will also accept students who have majored in mathematics or engineering and completed a sufficient number and selection of computer science courses. The choice of the appropriate major and computing courses will depend on the student’s interests and should be made in consultation with the chair of the Computer Science Department. Other majors are also reasonable for students with special interests. For example, a major in linguistics or psychology might be appropriate for a student interested in artificial intelligence or cognitive science. In such cases, students should consult with the chair of the department as early as possible to ensure that they take the necessary mathematics and computing courses for graduate work in computer science.Courses
CPSC 021. Introduction to Computer Science
This course presents fundamental ideas in computer science while building skills in software development. Students implement algorithms as programs in a high-level programming language. Introducing object-oriented programming and data structures allows students to construct correct, understandable, and efficient algorithms. CPSC 031 and CPSC 035 present a deeper coverage of these topics. CPSC 021 is appropriate for all students who want to be able to write programs. It is the usual first course for computer science majors and minors. Students with Advanced Placement credit or extensive programming experience may be able to place out of this course. Students who think that they may fall into this latter category should consult with any computer science faculty member.Lab work required, programming intensive. No prerequisites.
Natural sciences and engineering practicum.
1 credit.
Each semester. Staff.
CPSC 031. Introduction to Computer Systems
This course is a broad introduction to computer science that focuses on how a computer works and how programs run on computers. We examine the hardware and software components required to go from a program expressed in a high-level programming language like C or Python to the computer actually running the program. This course takes a bottom-up approach to discovering how a computer works. Topics include theoretical models of computation, data representation, machine organization, assembly and machine code, memory, I/O, the stack, the operating system, compilers and interpreters, processes and threads, and synchronization. This course also introduces parallel and distributed computing with a specific focus on shared memory parallelism for multicore and SMP systems.Prerequisites: CPSC 021 or equivalent.
Lab work required.
Natural sciences and engineering practicum.
1 credit.
Each semester. Staff.
CPSC 035. Data Structures and Algorithms
This course completes the broad introduction to computer science begun in CPSC 021. It provides a general background for further study in the field. Topics to be covered include object-oriented programming in C++, advanced data structures (trees, priority queues, hash tables, graphs, etc.) and algorithms, and software design and verification. Students will be expected to complete several programming projects illustrating the concepts presented.Prerequisite: CPSC 021 or equivalent. Discrete Mathematics is recommended.
Lab work required.
Natural sciences and engineering practicum.
1 credit.
Each semester. Staff.
CPSC 037. Structure and Interpretation of Computer Programs
This course is a serious introduction to the study of computer programs and, through programs, some central ideas in computer science. By studying programs that make repeated and deep use of abstraction, students will learn how to generate precise specifications from vaguely formulated and perhaps partially understood descriptions. Topics to be covered include programming idioms and paradigms, recursion, information retrieval, binding and scope, interpreters, and compilers.Prerequisite: CPSC 035.
Lab work required.
1 credit.
Not offered 2013–2014.
CPSC 040. Computer Graphics
(Cross-listed as ENGR 026)Computer graphics focuses on the creation and manipulation of digital imagery. We cover the modeling, rendering, and animating of geometric object in two (2D) and three (3D) dimensions. Topics include drawing algorithms for 2D geometric primitives (points, lines, polygons), geometric matrix transformations, projective geometry, geometric object representations, hidden surface removal, hierarchical modeling, shading, lighting, shadows, ray-tracing, procedural (non-geometric) modeling, texture mapping, and animation. Labs will explore various tools for rendering graphics, including pixel buffers, OpenGL, shading languages, and general purpose GPU computing.
Prerequisites: CPSC 031, CPSC 035 and Linear Algebra required or permission of the instructor. (Linear Algebra may be taken concurrently.)
Lab work required.
Natural sciences and engineering practicum.
1 credit.
Spring 2015. Danner.
CPSC 041. Algorithms
The study of algorithms is useful in many diverse areas. As algorithms are studied, considerable attention is devoted to analyzing formally their time and space requirements and proving their correctness. Topics covered include abstract data types, trees (including balanced trees), graphs, searching, sorting, NP complete optimization problems, and the impact of several models of parallel computation on the design of algorithms and data structures.Prerequisites: CPSC 035 required. Mathematics background at the level of Linear Algebra or higher is required (may be taken concurrently).
Lab work required.
1 credit.
Fall 2013. Brody.
CPSC 043. Computer Networks
This course covers the design, implementation and applications of computer networks, primarily focused on the protocols that enable the Internet and network applications. Additionally, this course will cover network security, such as viruses, worms, and botnets. Topics will include: data communication theory; packet-switched routing; the Internet and its protocols; socket and network application programming; overlays and P2P networks; and network security.Prerequisite: CPSC 031 and CPSC 035 required.
Lab work required.
1 credit.
Fall 2013. Webb.
CPSC 044. Database Systems
This course provides an introduction to relational database management systems. Topics covered include data models (ER and relational model); data storage and access methods (files, indices); query languages (SQL, relational algebra, relational calculus, QBE); query evaluation; query optimization; transaction management; concurrency control; crash recovery; and some advanced topics (distributed databases, object-relational databases). A project that involves implementing and testing components of a relational database management system is a large component of the course.Prerequisite: CPSC 031 and CPSC 035 required.
Lab work required.
1 credit.
Spring 2014. Soni.
CPSC 045. Operating Systems
(Cross-listed as ENGR 022)This course is an introduction to the theory, design, and implementation of operating systems. An operating system is the software layer between user programs and the computer hardware. It provides abstractions of the underlying hardware that are easier to program, and it manages the machine’s resources. The following topics will be covered: processes (including synchronization, communication, and scheduling); memory (main memory allocation strategies, virtual memory, and page replacement policies); file systems (including naming and implementation issues); I/O (including devices, drivers, disks, and disk scheduling); and security.
Prerequisite: CPSC 031 and CPSC 035 required.
Lab work required.
Natural sciences and engineering practicum.
1 credit.
Spring 2014. Newhall.
CPSC 046. Theory of Computation
(Cross-listed as MATH 046)This study of various models of computation leads to a characterization of the kinds of problems that can and cannot be solved by a computer. Solvable problems will be classified with respect to their degree of difficulty. Topics to be covered include formal languages and finite state devices; Turing machines; and other models of computation, computability, and complexity.
Prerequisite: CPSC 035 required. Mathematics background at the level of Linear Algebra or higher is required (may be taken concurrently).
Lab work required.
1 credit.
Spring 2014. Danner.
CPSC 052. Principles of Computer Architecture
(See ENGR 025)Natural sciences and engineering practicum.
1 credit.
Next offered when staffing permits.
CPSC 063. Artificial Intelligence
Artificial intelligence (AI) can be defined as the branch of computer science that is concerned with the automation of intelligent behavior. Intelligent behavior encompasses a wide range of abilities; as a result, AI has become a very broad field that includes game playing, automated reasoning, expert systems, natural language processing, modeling human performance (cognitive science), planning, and robotics. This course will focus on a subset of these topics and specifically on machine learning, which is concerned with the problem of how to create programs that automatically improve with experience. Machine learning approaches studied will include neural networks, decision trees, genetic algorithms, and reinforcement techniques.Prerequisites: CPSC 035 required.
Lab work required.
Natural sciences and engineering practicum.
1 credit.
Fall 2013. Meeden.
CPSC 065. Natural Language Processing
(Cross-listed as LING 020)This course is an introduction to the fundamental concepts in natural language processing, the study of human language from a computational perspective. The focus will be on creating statistical algorithms used in the analysis and production of language. Topics to be covered include parsing, morphological analysis, text classification, speech recognition, and machine translation. No prior linguistics experience is necessary.
Prerequisite: CPSC 035 required.
Lab work required.
1 credit.
Fall 2014. Wicentowski.
CPSC 068. Bioinformatics
This course is an introduction to the fields of bioinformatics and computational biology, with a central focus on algorithms and their application to a diverse set of computational problems in molecular biology. Computational themes will include dynamic programming, greedy algorithms, supervised learning and classification, data clustering, trees, graphical models, data management, and structured data representation. Applications will include genetic sequence analysis, pairwise-sequence alignment, phylogenetic trees, motif finding, gene-expression analysis, and protein-structure prediction. No prior biology experience is necessary.Prerequisite: CPSC 035 required.
Lab work required.
1 credit.
Spring 2015. Soni.
CPSC 071. Software Engineering: iOS Development
This course is an introduction to software engineering, with a focus on iOS development. iOS is the name of the operating system that runs on many of Apple’s products including the iPhone, iPod Touch, and iPad. In this course, students will learn how to write iOS apps in Objective C using Apple’s Xcode IDE (integrated development environment). Topics will also include readings on user interface design, project implementation and unit testing. Students do not need to own an iOS device to take the course.Prerequisite: CPSC 035 required.
Lab work required.
1 credit.
Spring 2015.
CPSC 072. Computer Vision
(See ENGR 027)Natural sciences and engineering practicum.
1 credit.
Spring 2015. Zucker.
CPSC 075. Principles of Compiler Design and Construction
(Cross-listed as ENGR 023)This course introduces the design and construction of language translators for imperative, procedure-oriented programming languages. Topics covered include formal grammars, lexical analysis and finite automata, syntax analysis and pushdown automata, LL and LR parsing, semantic analysis and table handling, error detection and recovery, code generation and optimization, and compiler writing tools.
Prerequisite: CPSC 031 and CPSC 035 required. CPSC 031 may be taken concurrently.
Lab work required.
Natural sciences and engineering practicum.
1 credit.
Fall 2013. Waterman.
CPSC 081. Adaptive Robotics
This seminar addresses the problem of controlling robots that will operate in dynamic, unpredictable environments. In laboratory sessions, students will work in groups to program robots to perform a variety of tasks such as navigation to a goal, obstacle avoidance, and vision-based tracking. In discussion sessions, students will examine the major paradigms of robot control through readings from the primary literature with an emphasis on adaptive approaches.Eligible for Cognitive Science credit.
Prerequisite: CPSC 035 required. CPSC 063 is recommended.
Lab work required.
Natural sciences and engineering practicum.
1 credit.
Spring 2014. Meeden.
CPSC 082. Mobile Robotics
(See ENGR 028)Natural sciences and engineering practicum.
1 credit.
Fall 2014. Zucker.
CPSC 087. Parallel and Distributed Computing
This course covers a broad range of topics related to parallel and distributed computing, including parallel and distributed architectures and systems, parallel and distributed programming paradigms, parallel algorithms, and scientific and other applications of parallel and distributed computing. In lecture/discussion sections, students examine both classic results as well as recent research in the field. The lab portion of the course includes programming projects using different programming paradigms, and students will have the opportunity to examine one course topic in depth through an open-ended project of their own choosing. Course topics may include: multi-core, SMP, MPP, client-server, clusters, clouds, grids, peer-to-peer systems, GPU computing, scheduling, scalability, resource discovery and allocation, fault tolerance, security, parallel I/0, sockets, threads, message passing, MPI, RPC, distributed shared memory, data parallel languages, MapReduce, parallel debugging, and parallel and distributed applicationsPrerequisites: CPSC 031 and CPSC 035 required. CPSC 045 is recommended.
Lab work required.
1 credit.
Not offered 2013–2014.
CPSC 091. Special Topics in Computer Science
Subject matter for CPSC 091 is generally dependent on group need or individual interest. The course is normally restricted to upper-level students and offered only when interest and staff availability make it practicable to do so.Lab work required.
1 credit.
Staff.
CPSC 093. Directed Reading and/or Research Project
A qualified student may undertake a program of extra reading and/or a project in an area of computer science with the permission of a staff member who is willing to supervise.CPSC 097. Senior Conference
This course provides honors and course majors an opportunity to delve more deeply into a particular topic in computer science, synthesizing material from previous courses. Topics have included sensing for healthcare (2012), data management systems (2010, 2011), computer perception (2008, 2009), computational geometry and geographic information systems (2006, 2007), computer security (2005), natural language processing (2004); advanced algorithms (2003); networking (2001, 2002); distributed computing (2000); evolutionary computation (1998 and 1999); complexity, encryption, and compression (1996); and parallel processing (1995). CPSC 097 is the usual method used to satisfy the comprehensive requirement for a computer science major and the senior honors study requirement for a computer science honors major.Lab work required.
Writing course.
1 credit.
Fall 2013. Ylvisaker.
