[IHASC] - [de] - [Hardware Aware Scientific Computing]


Hardware Aware Scientific Computing [2022 Sommer]
Code
IHASC
Name
Hardware Aware Scientific Computing
LP
8
Dauer
one semester
Angebotsturnus
irregular
Format
Lecture 4 SWS + Exercise Course 2 SWS
Arbeitsaufwand
240h;thereof
90h lecture
15h preparation for exam
135h self-study and working on assignments/projects (optionally in groups)
Verwendbarkeit
M.Sc. Angewandte Informatik
M.Sc. Data and Computer Science
M.Sc. Scientific Computing
Sprache
English
Lehrende
Peter Bastian
Prüfungsschema
Lernziele Students are familiar with different forms of parallelism in modern computer architectures. The can exploit this parallelism selecting an appropriate programming model. They are familiar with modelling of parallelism and know fundamental parallel algorithms from scientific computing.
Lerninhalte Parallel Computer Architecture
- Pipelining and super-scalar processors, SIMD vectorisation
- Caches
- Multicore architectures
- GPUs
- Communication networks
Programming Models
- Shared memory programming with OpenMP and C++ threads
- OpenCL or Cuda
- Task-based programming
- Message-passing, MPI
Parallel Algorithms
- Speedup & scalability
- Roofline model
- Linear Algebra: Matrix-Vector, Matrix multiplication, solving dense
systems, solving sparse systems
- Iterative Solution of Linear Systems
- High-Performance Libraries
- Differential equations
- Particle Methods
Teilnahme-
voraus-
setzungen
basic knowledge in computer architecture and numerical methods; good programming skills in C++
Vergabe der LP und Modulendnote The module is completed with a graded exam. The note of this exam gives the note for this module. Details for this exam as well as the requirements for the assignment of credits will be given by the lecturer an the beginning of this course.
Nützliche Literatur Frédéric Magoules, François-Xavier Roux, Guillaume Houzeaux: Parallel Scientific Computing, Wiley, 2016, doi: 10.1002/9781118761687