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CS 6210: Advanced Scientific Computing I |
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News |
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9/26 Please check the updated syllabus regarding the midterm! |
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9/22 Supercomputing Miniseries: Aaron Knoll: Visualization for Supercomputing at TACC and Argonne |
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9/7 Lecture 4 posted with updated whiteboard summary! |
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9/1
Announcing Supercomputing Miniseries guest speakers! |
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Schedule (subject to change) |
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Introduction |
Lecture 1 Syllabus Homework 1 |
| H: 8/27 | Chapter 1: Numerical Algorithms |
Lecture 2 Author Slides Chapter 1 |
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Chapter 2: Rounding Errors |
Lecture 3 Supercomputing Miniseries: Mark Kim (SCI): Sequoia and Fixed-Rate Compressed Floating-Point Arrays Author Slides Chapter 2 Paper on the Impact of Non-Associativity of FP Numbers NVIDIA CUDA Rounding What Every Computer Scientist Should Know About Floating-Point Arithmetic Prof. Mike Heath's (UIUC) Floating Point Slides |
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Lecture 4 New! |
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Chapter 3: Nonlinear Equations in One Variable |
Homework 1 Due |
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Lecture Notes by Prof. Mark Embree (Rice University) Bracketing Algorithms / Newton's Method / Secant Method Root Finding Chapter from Cleve Moler's Book Numerical Computing in Matlab |
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Chapter 4: Linear Algebra Background |
Supercomputing Miniseries: Manas Pathak (EGI): Falcon and Molecular Simulation Author Slides Chapter 4 Eigenvalue and Singular Value Chapter from Cleve Moler's Book Numerical Computing in Matlab |
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H: 9/17 |
Supercomputing Miniseries: Chongke Bi (RIKEN)(9/18 Japan Time): K Computer, Parallel Compression and In-Situ Visualization Homework 2 Due Homework 3 Homework 2 (Example) Solution Set |
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Chapter 5: Linear Systems - Direct Methods |
Supercomputing Miniseries: Aaron Knoll: Visualization for
Supercomputing at
TACC and Argonne Author Slides Chapter 5 Prof. Tim Davis' (University of Florida) Sparse (Direct) Linear Algebra Page |
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Chapter 9from Karniadakis and Kirby's Book Parallel Scientific Computing in C++ and MPI | ||
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Chapter 6: Linear Systems - Least Squares Problems |
Author Slides Chapter 6 |
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Chapter 7: Linear Systems - Iterative Methods |
Author Slides Chapter 7 |
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Homework 4 | ||
10/11-10/18 |
Fall Break |
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T: 10/20 |
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Conjugage Gradient Methods (A Painless View) by Johnathan Shewchuk (Berkeley) Multigrid Tutorial by William Briggs (LLNL) Lecture Notes on Multigrid Methods by P.S. Vassilevski (LLNL) |
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Chapter 8: Eigenvalues and Singular Values |
Author Slides Chapter 8 Lecture Notes by Prof. Mark Embree (Rice University) SVD (Theory)/ SVD Examples, Norms and Compressions |
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Chapter 9: Nonlinear Systems and Optimization |
Homework 4 Due Homework 5 Author Slides Chapter 9 |
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Chapter 10: Polynomial Interpolation |
Author Slides Chapter 10 |
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H: 11/12 |
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Chapter 11: Piecewise-Linear Interpolation |
Author Slides Chapter 11
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Chapter 12: Best Approximation |
Author Slides Chapter 12 Lecture Notes by Prof. Mark Embree (Rice University) Continuous Least Squares and Orthogonal Polynomials Homework 5 Due Homework 6 |
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H: 11/26 |
No Class - Thanksgiving Break |
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Chapter 14: Numerical Differentiation |
Author Slides Chapter 14 Other Good (Book) References For Numerical Differentiation and Integration: Spectral Methods in Matlab by L.N. Trefethen Spectral Methods for Time-Dependent Problems by J. Hesthaven, S. Gottlieb and D. Gottlieb Spectral Methods by C. Canuto, Y. Hussaini, A. Quarteroni and T. Zang |
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"Is Gauss Quadrature Better than Clenshaw-Curtis?" by Lloyd N. Trefethen, SIAM Review, 2008. | ||
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Chapter 15: Numerical Integration |
Author Slides Chapter 15 Lecture Notes by Prof. Mark Embree (Rice University) Interpolatory Quadrature / Richardson Extrapolation and Romberg Integration / Gauss Quadrature |
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Review for Final Exam |
Homework 6 Due Final Review Lecture |
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Good luck! |
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