Lectures:
Introduction. Motivation and historical remarks. Basic concepts. Assumed knowledge.
Parallel computer systems. Flynn's classification. Interconnection subsystems.
Examples of state-of-the-art (super-)computers.
Loosely coupled multiprocessors. Computer networks and massively parallel systems. IBM
RS/6000 Scalable Powerparallel System (SP). Introduction to the AIX operating system.
Parallel programming models. The message passing model. Design of a parallel algorithm: decomposition
(functional, domain), communication analysis, agglomeration, mapping to processors. Examples.
Evaluation of parallel algorithms. Speedup, efficiency, cost. Amdahl's law. Scalability.
Parallel Virtual Machine (PVM). Basic characteristics. Application programming interface. Example.
PVM (continued). Overview of library routines: process control, information retrieval, message passing,
etc.
PVM (continued). Collective communication. Debugging issues. Visualization of a parallel execution
(XPVM).
Parallel Environment for AIX (PE). Parallel Operating Environment (POE). Another SP tools.
Selected parallel algorithms. Graph algorithms, sorting and other applications.
Introduction to the Message Passing Interface (MPI). Comparison with PVM, advanced features.
Alternatives to the message passing. Programming of symmetric multiprocessors.
Support of parallelism in programming languages. High Performance Fortran.
Parallelization of sequential algorithms. Examples from the field of numerical computations.
Review. Future trends.
Introduction. Motivation and historical remarks. Basic concepts. Assumed knowledge.
Parallel computer systems. Flynn's classification. Interconnection subsystems.
Examples of state-of-the-art (super-)computers.
Loosely coupled multiprocessors. Computer networks and massively parallel systems. IBM
RS/6000 Scalable Powerparallel System (SP). Introduction to the AIX operating system.
Parallel programming models. The message passing model. Design of a parallel algorithm: decomposition
(functional, domain), communication analysis, agglomeration, mapping to processors. Examples.
Evaluation of parallel algorithms. Speedup, efficiency, cost. Amdahl's law. Scalability.
Parallel Virtual Machine (PVM). Basic characteristics. Application programming interface. Example.
PVM (continued). Overview of library routines: process control, information retrieval, message passing,
etc.
PVM (continued). Collective communication. Debugging issues. Visualization of a parallel execution
(XPVM).
Parallel Environment for AIX (PE). Parallel Operating Environment (POE). Another SP tools.
Selected parallel algorithms. Graph algorithms, sorting and other applications.
Introduction to the Message Passing Interface (MPI). Comparison with PVM, advanced features.
Alternatives to the message passing. Programming of symmetric multiprocessors.
Support of parallelism in programming languages. High Performance Fortran.
Parallelization of sequential algorithms. Examples from the field of numerical computations.
Review. Future trends.