Focusing on algorithms for distributed-memory parallel
architectures, Parallel Algorithms presents a rigorous yet
accessible treatment of theoretical models of parallel computation,
parallel algorithm design for homogeneous and heterogeneous
platforms, complexity and performance analysis, and essential
notions of scheduling. The book extracts fundamental ideas and
algorithmic principles from the mass of parallel algorithm
expertise and practical implementations developed over the last few
decades.
In the first section of the text, the authors cover two
classical theoretical models of parallel computation (PRAMs and
sorting networks), describe network models for topology and
performance, and define several classical communication primitives.
The next part deals with parallel algorithms on ring and grid
logical topologies as well as the issue of load balancing on
heterogeneous computing platforms. The final section presents basic
results and approaches for common scheduling problems that arise
when developing parallel algorithms. It also discusses advanced
scheduling topics, such as divisible load scheduling and
steady-state scheduling.
With numerous examples and exercises in each chapter, this text
encompasses both the theoretical foundations of parallel algorithms
and practical parallel algorithm design.
General
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