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This course will develop competency in high-end computing while focusing on relevant applications.

When: Tu 3:00 - 4:10 PM,   Fr 2:00 - 3:10 PM,   NY time.

Where: href=https://columbiauniversity.zoom.us/j/9515413977 (subject to change).

What you need: Access to command-line under Linux, or Macos (i.e., Terminal), or Windows (Cygwin or WSL).

Lectures:

    Lecture 1 materials.   Lecture 1 video.

    Lecture 2 materials.   Lecture 2 video.

    Lecture 3 materials.   Lecture 3 video.

    Lecture 4 materials.   Lecture 4 video.

    Lecture 5 materials.   Lecture 5 video.

    Lecture 6 materials.   Lecture 6 video.

    Lecture 7 materials.   Lecture 7 video, part 1,   Lecture 7 video, part 2.

    Lecture 8 materials.   Lecture 8 video.

    Lecture 9 materials.   Lecture 9 video.

    Lecture 10 materials.   Lecture 10 video.

    Lecture 11 materials.   Lecture 11 video.

    Lecture 12 materials.   Lecture 12 video.

    Lecture 13 materials.   Lecture 13 video.

    Lecture 14 materials.   Lecture 14 video.

    Lecture 15a materials.   Lecture 15a video.

    Lecture 16 materials.   Lecture 16 video.

    Lecture 17 materials.   Lecture 17 video.

    Lecture 18 materials.   Lecture 18 video.

    Lecture 19 materials.   Lecture 19 video.

    Lecture 20 video.

    Lecture 21 materials.   Lecture 21 video.

    Lecture 22 materials.   Lecture 22 video.

    Lecture 23 materials.   Lecture 23 transcript (vtt).

    Lecture 24 materials.   Lecture 24 video.

    Lecture 25 materials.

    Lecture 26 materials.   Lecture 26 video.

Computing-related topics

1. C programming: syntax, data types, addresses, memory management and troubleshooting.

2. Makefiles (Cmake if time allows).

3. Multithreaded computing.

4. Building C-DLLs that can be called from Python.

5. CUDA, i.e., GPU programming (in C).

Application-oriented topics

1. Analysis of large-scale streaming data: first, the power method, then the noisy power method.

2. First-order method for high-dimensional nonlinear optimization, including momentum. BFGS. Example: pairs-based portfolio optimization with nonstandard risk measures.

3. Computing all-pairs shortest paths between all cities in the world.

... more to come


Textbook: The C Programming Language, by Kernighan and Ritchie. ISBN 978-0131103627.

Textbook: The Bug: A Novel, by Ellen Ullman. ISBN 978-1250002495.


Resources

If you are taking part in this course, please send me an email.