The course consists of the following four parts.
• Part A. A 75-minute lecture on every Thursday (9:10-10:25) from 2017/9/14 to 2017/12/7.
• Part B. A 75-minute hands-on session on every Thursday (10:35-11:50) from 2017/9/14 to 2017/12/7.
• Part C. An online course that consists of twelve 75-minute lectures by Prof. Edmond Chow. This online course should be self-studied from 2017/9/14 to 2017/11/2.
• Part D. Twelve 75-minute lectures (12:10-13:25) on selected days from 2017/12/18 to 2018/1/5.

The tentative schedule for Parts A, B, C is listed below. The online course of Part C is available on the web page https://sites.google.com/site/school4scicomp/previous/2016-b-spring.

• Week 1 (2017/9/14)
o Lecture
♣ a. Introduction to course
♣ b. Graph Laplaician
♣ c. Applications in 3D face animation and data network analysis
o Hands-on session
♣ a. Download data from http://konect.uni-koblenz.de/
♣ b. Construct the matrices by Matlab or GPU
♣ c. Check the sparsity of the matrices
♣ d. Learn mathematical software tool (web)
o Online course
♣ a. [0503-1], [0503-2], [0505-1]
• Week 2 (2017/9/21)
o Lecture
♣ a. power method for EVP
♣ b. inverse power method for EVP
o Hands-on session
♣ a. Practice mathematical software tools
♣ b. Learn basic CUDA programming
♣ c. Use csreigvsi in cuSolverSP to compute the target eigenvalues
♣ d. Try other problems by using csreigvsi
o Online course
♣ [0505-2], [0506-1], [0506-2]
• Week 3 (2017/9/28)
o Lecture
♣ a. None
o Hands-on session
♣ a. Solve the linear system (A + 1.0e-5 I) y = b by using the direct solvers (LU and Cholesky) in cuSolverSP package to solve the linear systems from http://konect.uni-koblenz.de/ with various dimensions
♣ b. Discuss the results in direct solvers
o On-line course
♣ [0509-1], [0509-2], [0510-1]
• Week 4 (2017/10/5)
o Lecture
♣ a. Conjugate gradient method
o Hnads-on session
♣ a. Learn how to use magma_dcg (Conjugate Gradient method) in MAGMA
o Online course
♣ [0510-2], [0511-1], [0511-2]
• Week 5 (2017/10/12)
o Lecture
♣ a. Conjugate gradient method
o Hands-on session
♣ a. Use magma_dcg type functions in MAGMA to solve linear system from 3D face animation
♣ b. Use magma_dcg type functions in MAGMA to solve linear system from http://konect.uni-koblenz.de/ with various dimensions
o Online course
♣ [0512-1], [0512-2], [0516-1]
• Week 6 (2017/10/19)
o Lecture
♣ a. Preconditioning conjugate gradient method
o Hands-on session
♣ a. Learn how to use PCG with preconditioners in MAGMA
o Online course
♣ [0516-2], [0517-1], [0517-2]
• Week 7 (2017/10/26)
o Lecture
♣ a. Preconditioner
o Hands-on session
♣ a. Use CG method in MAGMA with ICC (magma_dapplycumicc_l) and ILU (magma_dapplycumilu_l and magma_dapplycumilu_r) preconditioners
o Online course
♣ [0518-1], [0518-2], [0519-1], [0519-2]
• Week 8 (2017/11/2)
o Lecture
♣ a. Preconditioner
o Hands-on session
♣ a. Compare the results of CG method in MAGMA with ICC, ILU, and other preconditioners
♣ b. Run AmgX to solve linear systems
• Week 9 (2017/11/9)
o Lecture
♣ a. BiCGSTAB
o Hands-on session
♣ a. Learn how to use un-symmetric linear solvers in MAGMA
• Week 10 (2017/11/16)
o Lecture
♣ a. BiCGSTAB
o Hands-on session
♣ a. Use BiCGSTAB (magma_dbicgstab) with ILU preconditioner to solve linear system (A - 1.0e-5) y = b
• Week 11 (2017/11/23)
o Lecture
♣ a. Lanczos method
o Hands-on session
♣ a. Learn how to use sparse eigensolver in MAGMA
• Week 12 (2017/11/30)
o Lecture
♣ a. Lanczos method
o Hands-on session
♣ a. Use LOBPCG (magma_dlobpcg) to compute the target eigenvalues
• Week 13 (2017/12/7)
o Midterm

The outline of Part D is listed below. See https://sites.google.com/site/school4scicomp/2017-d-chow for more information.
• Krylov subspace methods
o Projection method viewpoint and unifying framework
o Specialized methods
o Avoiding communication and synchronization
o Restarting for eigenvalue solvers
• Hierarchical matrix methods
o Physical intuition and relation to fast multipole methods
o Hierarchical matrix construction and solution methods
• Domain decomposition methods
o Optimized Schwarz methods
o FETI and related methods
• Multigrid methods
o Convergence theory
o Algebraic multigrid
• Parallel Preconditioning
o Advanced ideas on incomplete factorizations
o Advanced ideas on sparse approximate inverses
o Other recent developments