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Course Number: CSCI 596
Section: 30280D (lecture); 30146R (hands-on)
Session: 048
Instructor: Aiichiro Nakano; office: VHE 610; email:
TA: Taufeq Razakh (
Lecture: 3:30-4:50pm M W, SOS B2
Hands-on: 3:30-4:20pm F, ZHS 159
Office Hour: 4:30-5:50pm F, VHE 610
CARC (Center for Advanced Research Computing) Office Hour: 2:30-5:00 pm T
Assignment Submission and Grade Posting: TBA
Prerequisites: Basic knowledge of programming, data structures, linear algebra, and calculus; A nice introduction for a non-computer science student to fill the gap: Y. Patt and S. Patel, Introduction to Computing Systems: From Bits and Gates to C and beyond; A fun reading about the whole computer-science discipline: T. Hey and G. Papay, The Computing Universe; A survival guide for daily computational research: A. Scopatz and K. D. Huff, Effective Computation in Physics -- USC students have free access through Safari Online; Introductory courses on mathematical methods: Methods of Computational Physics & part I of Deep Learning book.
W. D. Gropp, E. Lusk, and A. Skjellum, "Using MPI, 3rd Ed." (MIT Press, 2014)--recommended
M. Woo, et al., "OpenGL Programming Guide, Version 4.5, 9th Ed." (Addison-Wesley, 2016)--recommended
A. Grama, A. Gupta, G. Karypis, and V. Kumar, "Introduction to Parallel Computing, 2nd Ed." (Addison-Wesley, 2003)--recommended

Course Description
Particle and continuum simulations are used as a vehicle to learn basic elements of high performance scientific computing and visualization. Students will obtain hands-on experience in: 1) formulating a mathematical model to describe a physical phenomenon; 2) discretizing the model, which often consists of continuous differential or integral equations, into algebraic forms in order to allow numerical solution on computers; 3) designing/analyzing numerical algorithms to solve the algebraic equations efficiently on parallel computers; 4) translating the algorithms into a program; 5) performing a computer experiment by executing the program; 6) visualizing simulation data in an immersive and interactive virtual environment; and 7) managing/mining large datasets. For details, please see course information sheet.

Visualization of 112 million-atom reactive molecular dynamics simulation to study high-temperature oxidation of a silicon-carbide nanoparticle on 786,432 IBM Blue Gene/Q cores.


Class Schedule