| Time: | Tuesdays and Thursdays, 11:00-12:15 | |||||||||||||||
| Place: | Olsson 228E | |||||||||||||||
| Instructor: | Greg Humphreys,
humper@cs.virginia.edu Office Hours: MW 10-12 in Olsson 216 |
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| Assignments: |
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| Format: | Reading and discussion oriented, with one assignment and a final project. | |||||||||||||||
| Prerequisites: | Previous computer graphics course experience, or consent of instructor. Familiarity with parallel computing concepts will be very helpful. Good programming skills or a very tolerant project partner a must. | |||||||||||||||
| Description: |
This course will cover a variety of issues that arise when trying to interact
with or visualize big datasets. The definition of "big" always varies with the
application, but similar issues arise again and again, such as bandwidth
constraints, latency requirements, scalability limits, parallel load balancing,
visual fidelity, and output device characteristics. These issues are
particularly critical when it is important to build a system that is
interactive.
In this class, we will look at recent research results related to these topics. The focus will mostly be on scalable systems, but we will also consider the use of levels of detail, tone mapping, and alternate rendering architectures. Topics to be covered include but are not limited to:
All students in this course will be expected to read all the assigned research papers. In addition, each student will be required to present one or more (depending on enrollment) topics to the class. This will typically require presenting background material on the topic, summarizing a small number of papers, and leading a class discussion on the topic. Students will also complete one small assignment on probing the capabilities of graphics hardware. Finally, there will be an open-ended project that can relate to any of the material covered in this course (or really any material at all with instructor's permission). The project may be done in small groups. Although these projects need not show new results, they will be "publication quality"; that is, students will be expected to explore a topic in sufficient depth (including a high quality write-up) for publication. Each group will present its results to the class at the end of the semester. Ambitious students are encouraged to use this project as an opportunity to begin new research projects, and I will be happy to assist any group wishing to continue their project after the semester ends and submit their work for publication. |
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| Texts: | None | |||||||||||||||
| Software: | None of these software packages are required for the course, but they
might be useful starting places for projects. Chromium. Software for manipulating streams of OpenGL commands, as well as support for routing those streams over networks. Particularly useful for doing scalability experiments on clusters. glsim/gltrace: A simple software implementation of (part of) the OpenGL pipeline, and an OpenGL trace/playback program. Written by Ian Buck and Kekoa Proudfoot. Students who wish to experiment with modifications to the graphics pipeline for their project may start here or use Mesa. HDRShop: High dynamic range image processing and manipulation | |||||||||||||||
| Honor Code: | The honor code applies to all work turned in for this course. In particular, all code and documentation should be entirely your own work. You may consult with other students about high-level design strategies, but you many not copy code or use the structure or organization of another students program. Said another way, you may talk with one another about your programs, but you cannot ever look at another student's code nor let another student look at your own code. Obviously, you may collaborate freely with your project partner. | |||||||||||||||
| Grading: | Why does everyone worry so much about grades? Grading will be determined based on four criteria: class participation, the benchmarking assignment, presentation quality/discussion leadership, and the final project. Of these, your project is the most important, followed by your presentation. Extra credit will be awarded depending on how "novel" your project is. Risky projects will be rewarded, but remember that you still have to turn in a writeup at the end of the semester, even if the writeup is called "Several reasons why our fantastic new algorithm for mesh simplification was a terrible idea". | |||||||||||||||
| Meetings: |