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Combinatorial Scientific Computing explores the latest research on
creating algorithms and software tools to solve key combinatorial
problems on large-scale high-performance computing architectures.
It includes contributions from international researchers who are
pioneers in designing software and applications for
high-performance computing systems. The book offers a
state-of-the-art overview of the latest research, tool development,
and applications. It focuses on load balancing and parallelization
on high-performance computers, large-scale optimization,
algorithmic differentiation of numerical simulation code, sparse
matrix software tools, and combinatorial challenges and
applications in large-scale social networks. The authors unify
these seemingly disparate areas through a common set of
abstractions and algorithms based on combinatorics, graphs, and
hypergraphs. Combinatorial algorithms have long played a crucial
enabling role in scientific and engineering computations and their
importance continues to grow with the demands of new applications
and advanced architectures. By addressing current challenges in the
field, this volume sets the stage for the accelerated development
and deployment of fundamental enabling technologies in
high-performance scientific computing.
Combinatorial Scientific Computing explores the latest research on
creating algorithms and software tools to solve key combinatorial
problems on large-scale high-performance computing architectures.
It includes contributions from international researchers who are
pioneers in designing software and applications for
high-performance computing systems. The book offers a
state-of-the-art overview of the latest research, tool development,
and applications. It focuses on load balancing and parallelization
on high-performance computers, large-scale optimization,
algorithmic differentiation of numerical simulation code, sparse
matrix software tools, and combinatorial challenges and
applications in large-scale social networks. The authors unify
these seemingly disparate areas through a common set of
abstractions and algorithms based on combinatorics, graphs, and
hypergraphs. Combinatorial algorithms have long played a crucial
enabling role in scientific and engineering computations and their
importance continues to grow with the demands of new applications
and advanced architectures. By addressing current challenges in the
field, this volume sets the stage for the accelerated development
and deployment of fundamental enabling technologies in
high-performance scientific computing.
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