Books > Computing & IT > Computer hardware & operating systems > Computer architecture & logic design > Parallel processing
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Graph Algorithms in the Language of Linear Algebra (Hardcover)
Loot Price: R3,693
Discovery Miles 36 930
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Graph Algorithms in the Language of Linear Algebra (Hardcover)
Series: Software, Environments and Tools
Expected to ship within 12 - 17 working days
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Graphs are among the most important abstract data types in computer
science, and the algorithms that operate on them are critical to
modern life. Graphs have been shown to be powerful tools for
modeling complex problems because of their simplicity and
generality. Graph algorithms are one of the pillars of mathematics,
informing research in such diverse areas as combinatorial
optimization, complexity theory, and topology. Algorithms on graphs
are applied in many ways in today's world - from Web rankings to
metabolic networks, from finite element meshes to semantic graphs.
The current exponential growth in graph data has forced a shift to
parallel computing for executing graph algorithms. Implementing
parallel graph algorithms and achieving good parallel performance
have proven difficult. This book addresses these challenges by
exploiting the well-known duality between a canonical
representation of graphs as abstract collections of vertices and
edges and a sparse adjacency matrix representation. This linear
algebraic approach is widely accessible to scientists and engineers
who may not be formally trained in computer science. The authors
show how to leverage existing parallel matrix computation
techniques and the large amount of software infrastructure that
exists for these computations to implement efficient and scalable
parallel graph algorithms. The benefits of this approach are
reduced algorithmic complexity, ease of implementation, and
improved performance. Graph Algorithms in the Language of Linear
Algebra is the first book to cover graph algorithms accessible to
engineers and scientists not trained in computer science but having
a strong linear algebra background, enabling them to quickly
understand and apply graph algorithms. It also covers array-based
graph algorithms, showing readers how to express canonical graph
algorithms using a highly elegant and efficient array notation and
how to tap into the large range of tools and techniques that have
been built for matrices and tensors; parallel array-based
algorithms, demonstrating with examples how to easily implement
parallel graph algorithms using array-based approaches, which
enables readers to address much larger graph problems; and
array-based theory for analyzing graphs, providing a template for
using array-based constructs to develop new theoretical approaches
for graph analysis.
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