CS2013-final-report

• Grama, A., Gupta, A., Kumar V. (2003, 2nd edn.). Introduction to Parallel Computing. Harlow, England:
Addison-Wesley.
• To develop parallel programs C/C++ is used, MS Visual Studio, Intel Parallel Studio, cluster under MS HPC
Server 2008.
Why do you teach the course this way
The goal of the course is to study the mathematical models, methods and technologies of parallel programming for
multiprocessor systems. Learning the course is sufficient for a successful start to practice in the area of parallel
programming.
The course has a good reputation among students. The students that are studied this course were the winner in the
track “Max Linpack performance” of the Cluster Student Competition at Supercomputing 2011. The course was a
part of the proposal that was the winner of the contest “Curriculum Best Practices: Parallelism and Concurrence”
of European Association “Informatics Europe” (2011) – see. http://www.informaticseurope.org/services/curriculum-award/105-curriculum-award-2011.html
Body of Knowledge coverage
KA Knowledge Unit Topics Covered Hours
PD
Parallelism
Fundamentals
Overview: Information dependencies analysis, decomposition,
synchronization, message passing
2
PD
Parallel
Decomposition
Data and task decomposition, Domain specific (geometric)
decomposition 0.5
PD
Communication and
Coordination
Basic communication operations, Evaluating communication overhead
2
PD
Parallel Algorithms,
Analysis, and
Programming
Characteristics of parallel efficiency,
Spectrum of parallel algorithms (Matrix calculation, System of linear
equations, Sorting, Graph algorithms, Solving PDE, Optimization)
OpenMP, MPI, MS VS, Intel Parallel Studio 10
PD Parallel Architecture Structure of the MIMD class of Flynn’s taxonomy,
SMP, Clusters, NUMA 1.5
PD Parallel Performance Characteristics of parallel efficiency: speed-up, cost, scalability,
isoefficiency. Theoretical prediction of parallel performance and
comparing with computational results 2
PD
Formal Models and
Semantics
Information dependencies analysis, Evaluating characteristics of
parallel efficiency (superlinear and linear speed-up, max possible
speed up for a given problem, speed-up of a given parallel algorithm),
Equivalent transformation of parallel programs 2
Additional topics
Isoefficiency,
Redundancy of parallel computations,
Classic illustrative parallel problems (readers-writers, dining philosophers, sleeping barbarian, etc.),
Tools for development of parallel programs,
Formal models based on Information dependencies analysis
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