460-6008/02 – Parallel Algorithms (PA)

Gurantor departmentDepartment of Computer ScienceCredits10
Subject guarantorprof. Ing. Pavel Krömer, Ph.D.Subject version guarantorprof. Ing. Pavel Krömer, Ph.D.
Study levelpostgraduateRequirementChoice-compulsory type B
YearSemesterwinter + summer
Study languageEnglish
Year of introduction2015/2016Year of cancellation
Intended for the facultiesFEI, FS, HGFIntended for study typesDoctoral
Instruction secured by
LoginNameTuitorTeacher giving lectures
KRO080 prof. Ing. Pavel Krömer, Ph.D.
PLA06 prof. Ing. Jan Platoš, Ph.D.
SNA57 prof. RNDr. Václav Snášel, CSc.
Extent of instruction for forms of study
Form of studyWay of compl.Extent
Full-time Examination 26+0
Part-time Examination 26+0
Distance Examination 10+0

Subject aims expressed by acquired skills and competences

The aim of the course is to provide students a general overview of the design, implementation and evaluation of parallel algorithms and HPC (High Performance Computing) in general. In addition, this knowledge and skills will be further enhanced in a direction that is in line with the specific focus of its Ph.D. studies and dissertation work.

Teaching methods

Seminars
Individual consultations
Project work
Other activities

Summary

The course covers both theoretical and practical elements of parallel programming and algorithms, to help the students make efficient use of modern multiprocessor and multicomputer hardware (including supercomputers) for solution of computationally demanding task from various application fields. A variety of algorithms and hardware and software tools for parallel and High Performance Computing are introduced, but the focus lies on the so-called loosely coupled systems (without shared memory), where the interaction of parallel activities is based on message passing. Individual approach, allowing application and intensification of the gained knowledge in the student's specific field of Ph.D. study, is supposed.

Compulsory literature:

• I. Foster: Designing and Building Parallel Programs. Addisson-Wesley, 1995. Standardizační dokumentace k MPI, OpenMP

Recommended literature:

• A. Grama et al.: Introduction to Parallel Computing, Second Edition. Pearson, 2003. • C. Lyn, L. Snyder: Principles of Parallel Programming. Pearson, 2009. • J. JáJá: An Introduction to Parallel Algorithms. Addison-Wesley, 1992.

Additional study materials

Way of continuous check of knowledge in the course of semester

Continuous monitoring of study activities and assigned tasks during regular consultations. If some publication activity will be a part of the student's tasks, the relevant article would be presented in the course. Oral exam.

E-learning

Ústní zkouška.

Other requirements

The student prepares and presents the work on a given topic.

Prerequisities

Subject has no prerequisities.

Co-requisities

Subject has no co-requisities.

Subject syllabus:

• Introduction to parallel programming. Processes and threads. Processes and threads from the operating system perspective. • Sequential vs. parallel programming. Parallel programming caveats. Deadlock (definition, properties, conditions, detection, elimination). • Parallel vs. distributed applications. Classification of parallel systems. Shared memory systems and distributed memory systems. Flynn's taxonomy. • Shared memory systems programming. Programming with threads. The pthreads library, Threads in Java and C#. Synchronization and exclusion, deadlock. • The OpenMP interface. OpenMP support in modern compilers. OpenMP directives and functions. Reduction in OpenMP.- R and its packages for parallel programming • Grid and cloud programming. Web services and distributed applications using web services. Map-reduce paradigm and Hadoop framework. • Overview of environments for parallel programming. SIMD instructions. • Introduction to accelerator programming. GPGPU architecture (program organization, memory organization). Data parallelism. CUDA platform and CUDA-C language.

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 pointsMax. počet pokusů
Examination Examination   3
Mandatory attendence participation:

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