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Course Number: CSCI 596
Section: 30280D (lecture); 30146R (hands-on)
Session: 048
Instructor:
Aiichiro Nakano;
office: VHE 610; email: anakano@usc.edu
TA: Taufeq Razakh (razakh@usc.edu)
Lecture: 3:30-4:50pm M W, SOS B2
Hands-on: 3:30-4:20pm F, ZHS 159
Office Hour: 4:30-5:20pm F, VHE 610
Assignment Submission and Grade Posting: Blackboard
CARC (Center for Advanced Research Computing) Office Hour:
2:30-5:00 pm T
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.
Textbooks:
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.