This text provides one of the broadest presentations of parallelprocessing available, including the structure of parallelprocessors and parallel algorithms. The emphasis is on mappingalgorithms to highly parallel computers, with extensive coverage ofarray and multiprocessor architectures. Early chapters provideinsightful coverage on the analysis of parallel algorithms andprogram transformations, effectively integrating a variety ofmaterial previously scattered throughout the literature. Theory andpractice are well balanced across diverse topics in this concisepresentation. For exceptional clarity and comprehension, the authorpresents complex material in geometric graphs as well as algebraicnotation. Each chapter includes well-chosen examples, tablessummarizing related key concepts and definitions, and a broad rangeof worked exercises.
* Overview of common hardware and theoretical models, including algorithm characteristics and impediments to fast performance * Analysis of data dependencies and inherent parallelism through program examples, building from simple to complex * Graphic and explanatory coverage of program transformations * Easy-to-follow presentation of parallel processor structures and interconnection networks, including parallelizing and restructuring compilers * Parallel synchronization methods and types of parallel operating systems * Detailed descriptions of hypercube systems * Specialized chapters on dataflow and on AI architectures
This text provides one of the broadest presentations of parallel
processing available, including the structure of parallel
processors and parallel algorithms. The emphasis is on mapping
algorithms to highly parallel computers, with extensive coverage of
array and multiprocessor architectures. Early chapters provide
insightful coverage on the analysis of parallel algorithms and
program transformations, effectively integrating a variety of
material previously scattered throughout the literature. Theory and
practice are well balanced across diverse topics in this concise
presentation. For exceptional clarity and comprehension, the author
presents complex material in geometric graphs as well as algebraic
notation. Each chapter includes well-chosen examples, tables
summarizing related key concepts and definitions, and a broad range
of worked exercises.
Features:
- Overview of common hardware and theoretical models, including
algorithm characteristics and impediments to fast performance
- Analysis of data dependencies and inherent parallelism through
program examples, building from simple to complex
- Graphic and explanatory coverage of program transformations
- Easy-to-follow presentation of parallel processor structures
and interconnection networks, including parallelizing and
restructuring compilers
- Parallel synchronization methods and types of parallel
operating systems
- Detailed descriptions of hypercube systems
- Specialized chapters on dataflow and on AI architectures
