Course detail
High Performance Computations (in English)
FIT-VNVeAcad. year: 2021/2022
The course is aimed at practical methods of solving sophisticated problems encountered in science and engineering. Serial and parallel computations are compared with respect to a stability of a numerical computation. A special methodology of parallel computations based on differential equations is presented. A new original method based on direct use of Taylor series is used for numerical solution of differential equations. There is the TKSL simulation language with an equation input of the analysed problem at disposal. A close relationship between equation and block representation is presented. The course also includes design of special architectures for the numerical solution of differential equations.
Language of instruction
Number of ECTS credits
Mode of study
Guarantor
Department
Offered to foreign students
Learning outcomes of the course unit
Ability to transform a sophisticated technical problem to a system of differential equations. Ability to solve sophisticated systems of differential equations using simulation language TKSL.
Ability to create parallel and quasiparallel computations of large tasks.
Prerequisites
Co-requisites
Planned learning activities and teaching methods
Assesment methods and criteria linked to learning outcomes
Half-term and Final exams. The minimal number of points which can be obtained from the final exam is 27. Otherwise, no points will be assigned to a student.
Course curriculum
Work placements
Aims
To provide overview and basics of practical use of parallel and quasiparallel methods for numerical solutions of sophisticated problems encountered in science and engineering.
Specification of controlled education, way of implementation and compensation for absences
During the semester, there will be evaluated computer laboratories. Any laboratory should be replaced in the final weeks of the semester.
Recommended optional programme components
Prerequisites and corequisites
Basic literature
Corliss, G. F.: Automatic differentiation of algorithms, Springer-Verlag New York Inc., 2002
Duff, I. S.: Direct Methods for Sparse Matrices (Numerical Mathematics and Scientific Computation), Oxford University Press, 2017
Golub, G. H.: Matrix computations, Hopkins Uni. Press, 2013
Griewank, A.: Evaluating Derivatives: Principles and Techniques of Algorithmic Differentiation, Society for Industrial and Applied Mathematics, 2008
Hairer, E., Norsett, S. P., Wanner, G.: Solving Ordinary Differential Equations I, vol. Nonstiff Problems. Springer-Verlag Berlin Heidelberg, 1987.
Hairer, E., Wanner, G.: Solving Ordinary Differential Equations II, vol. Stiff And Differential-Algebraic Problems. Springer-Verlag Berlin Heidelberg, 1996.
Kunovský, J.: Modern Taylor Series Method, habilitation thesis, VUT Brno, 1995
LeVeque, R. J.: Finite Difference Methods for Ordinary and Partial Differential Equations: Steady-State and Time-dependent Problems (Classics in Applied Mathematics), 2007
Meurant, G.: Computer Solution of Large Linear System, North Holland, 1999
Press, W. H.: Numerical recipes : the art of scientific computing, Cambridge University Press, 2007
Saad, Y.: Iterative methods for sparse linear systems, Society for Industrial and Applied Mathematics, 2003
Shampine, L. F.: Numerical Solution of ordinary differential equations, Chapman and Hall/CRC, 1994
Strang, G.: Introduction to applied mathematics, Wellesley-Cambridge Press, 1986
Strikwerda, J. C.: Finite Difference Schemes and Partial Differential Equations, Society for Industrial and Applied Mathematics, 2004
Recommended reading
Hairer, E., Norsett, S. P., Wanner, G.: Solving Ordinary Differential Equations I, vol. Nonstiff Problems. Springer-Verlag Berlin Heidelberg, 1987.
Hairer, E., Wanner, G.: Solving Ordinary Differential Equations II, vol. Stiff And Differential-Algebraic Problems. Springer-Verlag Berlin Heidelberg, 1996.
Lecture notes written in PDF format,
Source codes of all computer laboratories
Elearning
Classification of course in study plans
Type of course unit
Lecture
Teacher / Lecturer
Syllabus
- Methodology of sequential and parallel computation (feedback stability of parallel computations)
- Extremely precise solutions of differential equations by the Taylor series method
- Parallel properties of the Taylor series method
- Basic programming of specialised parallel problems by methods using the calculus (close relationship of equation and block description)
- Parallel solutions of ordinary differential equations with constant coefficients, library subroutines for precise computations
- Adjunct differential operators and parallel solutions of differential equations with variable coefficients
- Methods of solution of large systems of algebraic equations by transforming them into ordinary differential equations
- The Bairstow method for finding the roots of high-order algebraic equations
- Fourier series and parallel FFT
- Simulation of electric circuits
- Solution of practical problems described by partial differential equations
- Control circuits
- Conception of the elementary processor of a specialised parallel computation system.
Exercise in computer lab
Teacher / Lecturer
Syllabus
- Simulation system TKSL
- Exponential functions test examples
- First order homogenous differential equation
- Second order homogenous differential equation
- Time function generation
- Arbitrary variable function generation
- Adjoint differential operators
- Systems of linear algebraic equations
- Electronic circuits modeling
- Heat conduction equation
- Wave equation
- Laplace equation
- Control circuits
Elearning