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Graph theoretic problems are representative of fundamental kernels in traditional and emerging scientific applications, such as complex network analysis, data mining, and computational biology, as well as applications in national security. Graph abstractions are also extensively used to understand and solve challenging problems in scientific computing. Real-world systems, such as the Internet, telephone networks, social interactions, and transportation networks, are analyzed by modeling them as graphs. To efficiently solve large-scale graph problems, it is necessary to design high performance computing systems and novel parallel algorithms. In this book, some of the world's most renowned experts explore the latest research and applications in this important area
List of contents
Theory. Benchmarks. Programming. Parallel Graph Algorithms. Applications. Architectures.
Summary
Graph theoretic problems are representative of fundamental kernels in traditional and emerging scientific applications, such as complex network analysis, data mining, and computational biology, as well as applications in national security. Graph abstractions are also extensively used to understand and solve challenging problems in scientific computing. Real-world systems, such as the Internet, telephone networks, social interactions, and transportation networks, are analyzed by modeling them as graphs. To efficiently solve large-scale graph problems, it is necessary to design high performance computing systems and novel parallel algorithms. In this book, some of the world’s most renowned experts explore the latest research and applications in this important area
