470-2211/03 – Numerical linear algebra 2 (NLA2)

Gurantor departmentDepartment of Applied MathematicsCredits3
Subject guarantordoc. Ing. David Horák, Ph.D.Subject version guarantordoc. Ing. David Horák, Ph.D.
Study levelundergraduate or graduateRequirementCompulsory
Year2Semesterwinter
Study languageCzech
Year of introduction2020/2021Year of cancellation
Intended for the facultiesFEIIntended for study typesBachelor
Instruction secured by
LoginNameTuitorTeacher giving lectures
HOR33 doc. Ing. David Horák, Ph.D.
Extent of instruction for forms of study
Form of studyWay of compl.Extent
Full-time Credit 0+2
Part-time Credit 0+8

Subject aims expressed by acquired skills and competences

Linear algebra is behind the solution of large-scale engineering problems. In Numerical linear algebra 2 students get familiar with modern software libraries with efficient sequential and parallel implementations of linear algebra algorithms and with their applications.

Teaching methods

Tutorials
Project work

Summary

The subject's core consists in effiecient parallel linear algebra algorithms exploiting fully the computational power of nowadays supercomputers.

Compulsory literature:

- G. H. Golub, C. F. Van Loan - Matrix computations. Johns Hopkins University Press, 2012. - PETSc Users Manual, http://www.mcs.anl.gov/petsc/petsc-current/docs/manual.pdf

Recommended literature:

- Y. Saad - Iterative methods for sparse linear systems. SIAM, 2003.

Way of continuous check of knowledge in the course of semester

Continuous study verification: • Test - max. 60 points. • Individual project on parallel implementation of chosen algorithm - max. 40 points. Requirements for passing the subject: • Writing the test. • Submitting and successful defense of a project.

E-learning

Other requirements

Successful defense of a semestral project. Students are familiar with fundamentals of linear algebra.

Prerequisities

Subject has no prerequisities.

Co-requisities

Subject has no co-requisities.

Subject syllabus:

Outline: 1. Numerical libraries overview 2. Basic operations with parallel objects in PETSc - vectors, matrices, index sets 3. Direct solvers and their parallelization - multifrontal vs. supernodal methods 4. Iterative solvers in PETSc - KSP 5. Spectral analysis using SLEPc 6. Preconditioning

Conditions for subject completion

Part-time form (validity from: 2020/2021 Winter semester)
Task nameType of taskMax. number of points
(act. for subtasks)
Min. number of pointsMax. počet pokusů
Credit Credit 100  51 3
Mandatory attendence participation: Recommended attendance at tutorials is 80%.

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Conditions for subject completion and attendance at the exercises within ISP: Completion of all mandatory tasks within individually agreed deadlines.

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Occurrence in study plans

Academic yearProgrammeBranch/spec.Spec.ZaměřeníFormStudy language Tut. centreYearWSType of duty
2024/2025 (B0541A170008) Computational and Applied Mathematics VMI P Czech Ostrava 2 Compulsory study plan
2024/2025 (B0541A170008) Computational and Applied Mathematics VMI K Czech Ostrava 2 Compulsory study plan
2023/2024 (B0541A170008) Computational and Applied Mathematics VMI P Czech Ostrava 2 Compulsory study plan
2023/2024 (B0541A170008) Computational and Applied Mathematics VMI K Czech Ostrava 2 Compulsory study plan
2022/2023 (B0541A170008) Computational and Applied Mathematics VMI K Czech Ostrava 2 Compulsory study plan
2022/2023 (B0541A170008) Computational and Applied Mathematics VMI P Czech Ostrava 2 Compulsory study plan
2021/2022 (B0541A170008) Computational and Applied Mathematics VMI P Czech Ostrava 2 Compulsory study plan
2021/2022 (B0541A170008) Computational and Applied Mathematics VMI K Czech Ostrava 2 Compulsory study plan
2020/2021 (B0541A170008) Computational and Applied Mathematics VMI P Czech Ostrava 2 Compulsory study plan
2020/2021 (B0541A170008) Computational and Applied Mathematics VMI K Czech Ostrava 2 Compulsory study plan

Occurrence in special blocks

Block nameAcademic yearForm of studyStudy language YearWSType of blockBlock owner

Assessment of instruction



2023/2024 Winter
2022/2023 Winter
2021/2022 Winter
2020/2021 Winter