Introduction to Parallel Programming Udacity class code
Includes student notes for entire course, solutions to all Problem sets, completed code segments of the Final Assessment.
These instructions are for OS X 10.9 "Mavericks", and have also been successfully tested on Ubuntu 14.10.
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Step 1. Build and install OpenCV. The best way to do this is with Homebrew. However, you must slightly alter the Homebrew OpenCV installation; you must build it with libstdc++ (instead of the default libc++) so that it will properly link against the nVidia CUDA dev kit. This entry in the Udacity discussion forums describes exactly how to build a compatible OpenCV.
- NOTE: as of cuda 7.0 this is no longer necessary. See my script for opencv installation details.
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Step 2. You can now create 10.9-compatible makefiles, which will allow you to build and run your homework on your own machine:
mkdir build
cd build
cmake ..
make
Key:
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📕 = link to a book
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📖 = link to online/free book
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Other courses
- Saraviensis ws1213
- UC Davis EEC 171
- taught by John Owens
- 📕 Computer Architecture: A Quantitative Approach, 4th Ed
- UC Davis EEC 277
- taught by John Owens
- 📕 Real time rendering
- 📕 Texture and Modeling, a procedural approach
- 📕 Cg tutorial
- UPenn CIS 565
- UC Davis ECS 223
- guest lectures by John Owens
- 📕 Introduction to Parallel Algorithms
- Coursera heterogeneous parallel programming
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Software
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Additional Books
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Conferences