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Problem solving is an essential part of every scientific
discipline. It has two components: (1) problem identification and
formulation, and (2) the solution to the formulated problem. One
can solve a problem on its own using ad hoc techniques or by
following techniques that have produced efficient solutions to
similar problems. This requires the understanding of various
algorithm design techniques, how and when to use them to formulate
solutions, and the context appropriate for each of them.Algorithms:
Design Techniques and Analysis advocates the study of algorithm
design by presenting the most useful techniques and illustrating
them with numerous examples - emphasizing on design techniques in
problem solving rather than algorithms topics like searching and
sorting. Algorithmic analysis in connection with example algorithms
are explored in detail. Each technique or strategy is covered in
its own chapter through numerous examples of problems and their
algorithms.Readers will be equipped with problem solving tools
needed in advanced courses or research in science and engineering.
Problem solving is an essential part of every scientific
discipline. It has two components: (1) problem identification and
formulation, and (2) solution of the formulated problem. One can
solve a problem on its own using ad hoc techniques or follow those
techniques that have produced efficient solutions to similar
problems. This requires the understanding of various algorithm
design techniques, how and when to use them to formulate solutions
and the context appropriate for each of them. This book advocates
the study of algorithm design techniques by presenting most of the
useful algorithm design techniques and illustrating them through
numerous examples.
Problem solving is an essential part of every scientific
discipline. It has two components: (1) problem identification and
formulation, and (2) the solution to the formulated problem. One
can solve a problem on its own using ad hoc techniques or by
following techniques that have produced efficient solutions to
similar problems. This required the understanding of various
algorithm design techniques, how and when to use them to formulate
solutions, and the context appropriate for each of them.This book
presents a design thinking approach to problem solving in computing
- by first using algorithmic analysis to study the specifications
of the problem, before mapping the problem on to data structures,
then on to the situatable algorithms. Each technique or strategy is
covered in its own chapter supported by numerous examples of
problems and their algorithms. The new edition includes a
comprehensive chapter on parallel algorithms, and many
enhancements.
This book is an introduction to the field of parallel algorithms
and the underpinning techniques to realize the parallelization. The
emphasis is on designing algorithms within the timeless and
abstracted context of a high-level programming language. The focus
of the presentation is on practical applications of the algorithm
design using different models of parallel computation. Each model
is illustrated by providing an adequate number of algorithms to
solve some problems that quite often arise in many applications in
science and engineering.The book is largely self-contained,
presuming no special knowledge of parallel computers or particular
mathematics. In addition, the solutions to all exercises are
included at the end of each chapter.The book is intended as a text
in the field of the design and analysis of parallel algorithms. It
includes adequate material for a course in parallel algorithms at
both undergraduate and graduate levels.
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