9600-0003/02 – HPC libraries and tools (HPCKN)

Gurantor departmentIT4InnovationsCredits10
Subject guarantorprof. Ing. Tomáš Kozubek, Ph.D.Subject version guarantorprof. Ing. Tomáš Kozubek, Ph.D.
Study levelpostgraduateRequirementChoice-compulsory
YearSemesterwinter + summer
Study languageEnglish
Year of introduction2015/2016Year of cancellation
Intended for the facultiesFS, FAST, USP, FEIIntended for study typesDoctoral
Instruction secured by
LoginNameTuitorTeacher giving lectures
KOZ75 prof. Ing. Tomáš Kozubek, Ph.D.
Extent of instruction for forms of study
Form of studyWay of compl.Extent
Full-time Examination 2+0
Combined Examination 10+0

Subject aims expressed by acquired skills and competences

The aim of the subject is to introduce students to the existence as well as use of selected libraries and tools for HPC. The use of these libraries while developing parallel applications and algorithms leads to substantial acceleration of the development as well as running of applications.

Teaching methods

Lectures
Individual consultations

Summary

The course consists of deeper introduction to currently used libraries and tools for the development of parallel applications. The libraries are mainly selected from fields such as linear algebra, accelerated computations including the tools accelerating the development of applications. With respect to the computational technologies, the selected libraries will cover programming for the distributed memory systems, systems with shared memory and multi-core processors, and systems with accelerators. - Libraries for linear algebra: BLAS, LAPACK, ScaLAPACK, Plasma - Libraries for accelerators: MAGMA, Nvidia CUDA libraries - Tools for accelerating the development of applications: PETSc, Intel MKL

Compulsory literature:

1. Gene H. Golub and Charles F. Van Loan, Matrix Computations (Johns Hopkins Studies in the Mathematical Sciences), Dec 27, 2012

Recommended literature:

1. Scientific articles describing computational methods used in selected libraries

Way of continuous check of knowledge in the course of semester

E-learning

Další požadavky na studenta

No other requirements.

Prerequisities

Subject has no prerequisities.

Co-requisities

Subject has no co-requisities.

Subject syllabus:

The course consists of deeper introduction to currently used libraries and tools for the development of parallel applications. The libraries are mainly selected from fields such as linear algebra, accelerated computations including the tools accelerating the development of applications. With respect to the computational technologies, the selected libraries will cover programming for the distributed memory systems, systems with shared memory and multi-core processors, and systems with accelerators. - Libraries for linear algebra: BLAS, LAPACK, ScaLAPACK, Plasma - Libraries for accelerators: MAGMA, Nvidia CUDA libraries - Tools for accelerating the development of applications: PETSc, Intel MKL

Conditions for subject completion

Full-time form (validity from: 2015/2016 Winter semester)
Task nameType of taskMax. number of points
(act. for subtasks)
Min. number of points
Examination Examination  
Mandatory attendence parzicipation:

Show history

Occurrence in study plans

Academic yearProgrammeField of studySpec.FormStudy language Tut. centreYearWSType of duty
2019/2020 (P2658) Computational Sciences (2612V078) Computational Sciences P English Ostrava Choice-compulsory study plan
2019/2020 (P2658) Computational Sciences (2612V078) Computational Sciences K English Ostrava Choice-compulsory study plan
2018/2019 (P2658) Computational Sciences (2612V078) Computational Sciences P English Ostrava Choice-compulsory study plan
2018/2019 (P2658) Computational Sciences (2612V078) Computational Sciences K English Ostrava Choice-compulsory study plan
2017/2018 (P2658) Computational Sciences (2612V078) Computational Sciences P English Ostrava Choice-compulsory study plan
2017/2018 (P2658) Computational Sciences (2612V078) Computational Sciences K English Ostrava Choice-compulsory study plan
2016/2017 (P2658) Computational Sciences (2612V078) Computational Sciences P English Ostrava Choice-compulsory study plan
2016/2017 (P2658) Computational Sciences (2612V078) Computational Sciences K English Ostrava Choice-compulsory study plan
2015/2016 (P2658) Computational Sciences (2612V078) Computational Sciences P English Ostrava Choice-compulsory study plan
2015/2016 (P2658) Computational Sciences (2612V078) Computational Sciences K English Ostrava Choice-compulsory study plan

Occurrence in special blocks

Block nameAcademic yearForm of studyStudy language YearWSType of blockBlock owner