Presents the state of the art in parallel numerical algorithms, applications, architectures, and system software, with contributions from an international selection of world-class authorities
Reviews emerging applications of numerical methods in information retrieval and data mining
Presents outstanding challenges and developing technologies, and puts these in their historical context
This book presents the state of the art in parallel numerical algorithms, applications, architectures, and system software. The book examines various solutions for issues of concurrency, scale, energy efficiency, and programmability, which are discussed in the context of a diverse range of applications. Features: includes contributions from an international selection of world-class authorities; examines parallel algorithm-architecture interaction through issues of computational capacity-based codesign and automatic restructuring of programs using compilation techniques; reviews emerging applications of numerical methods in information retrieval and data mining; discusses the latest issues in dense and sparse matrix computations for modern high-performance systems, multicores, manycores and GPUs, and several perspectives on the Spike family of algorithms for solving linear systems; presents outstanding challenges and developing technologies, and puts these in their historical context.|
Advances in the development of parallel algorithms and system software now enable the ever-increasing power of scalable high-performance computers to be harnessed for scientific computing applications at fidelities that rival – and in many cases exceed – experimental methodologies.
This comprehensive text/reference, inspired by the visionary work of Prof. Ahmed H. Sameh, represents the state of the art in parallel numerical algorithms, applications, architectures, and system software. Articles in this collection address various challenges arising from concurrency, scale, energy efficiency, and programmability, and associated solutions that have shaped the current high-performance computing landscape. These solutions are discussed in the context of diverse applications, ranging from scientific simulations to large-scale data analysis and mining.
Topics and features: includes contributions from an international selection of world-class authorities, inspired by the work of Prof. Ahmed H. Sameh and his involvement in parallel numerical algorithm design since Illiac IV and the University of Illinois Cedar multiprocessor; examines various aspects of parallel algorithm-architecture interaction through articles on computational capacity-based codesign and automatic restructuring of programs using compilation techniques; reviews emerging applications of numerical methods in information retrieval and data mining; discusses the latest issues in dense and sparse matrix computations for modern high-performance systems, multicores, manycores and GPUs, and several perspectives on the Spike family of algorithms for solving linear systems; presents outstanding challenges and developing technologies, and puts these in their historical context.
This authoritative reference is a must-read for researchers and graduate students in disciplines as diverse as computational fluid dynamics, signal processing, and structural mechanics. Professionals involved in applications that rely on high-performance computers will also find the text an essential resource.
Parallel Numerical Computing from Illiac IV to Exascale: The Contributions of Ahmed H. Sameh
K. Gallivan, E. Gallopoulos, A. Grama, B. Philippe, E. Polizzi, Y. Saad, F. Saied, and D. Sorensen
Computational Capacity-Based Co-design of Computer Systems
David J. Kuck
Measuring Computer Performance
William Jalby, David C. Wong, David J. Kuck, Jean-Thomas Acquaviva, and Jean-Christophe Beyler
A Compilation Framework for the Automatic Restructuring of Pointer-Linked Data Structures
Harmen L.A. van der Spek, C.W. Mattias Holm, and Harry A.G. Wijshoff
Dense Linear Algebra on Accelerated Multicore Hardware
Jack Dongarra, Jakub Kurzak, Piotr Luszczek, and Stanimire Tomov
The Explicit SPIKE Algorithm: Iterative Solution of the Reduced System
Carl Christian Kjelgaard Mikkelsen
The SPIKE Factorization as Domain Decomposition Method: Equivalent and Variant Approaches
Victor Eijkhout, and Robert van de Geijn
Parallel Solution of Sparse Linear Systems
Murat Manguoglu
Parallel Block-Jacobi SVD Methods
Martin Becka, Gabriel Okša, and Marián Vajteršic
Robust and Efficient Multifrontal Solver for Large Discretized PDEs
Jianlin Xia
A Preconditioned Scheme for Nonsymmetric Saddle-Point Problems
Abdelkader Baggag
Effect of Ordering for Iterative Solvers in Structural Mechanics Problems
Sami A. Kilic
Scaling Hypre´s Multigrid Solvers to 100,000 Cores
Allison H. Baker, Robert D. Falgout, Tzanio V. Kolev, and Ulrike Meier Yang
A Riemannian Dennis-Moré Condition
K.A. Gallivan, C. Qi, and P.-A. Absil
A Jump-Start of Non-Negative Least Squares Solvers
Mu Wang, and Xiaoge Wang
Fast Nonnegative Tensor Factorization with an Active-Set-Like Method
Jingu Kim, and Haesun Park
Knowledge Discovery Using Nonnegative Tensor Factorization with Visual Analytics
Andrey A. Puretskiy and Michael W. Berry
Advances in the development of parallel algorithms and system software now enable the ever-increasing power of scalable high-performance computers to be harnessed for scientific computing applications at fidelities that rival – and in many cases exceed – experimental methodologies.
This comprehensive text/reference, inspired by the visionary work of Prof. Ahmed H. Sameh, represents the state of the art in parallel numerical algorithms, applications, architectures, and system software. Articles in this collection address solutions to various challenges arising from concurrency, scale, energy efficiency, and programmability. These solutions are discussed in the context of diverse applications, ranging from scientific simulations to large-scale data analysis and mining.
Topics and features:
- Includes contributions from an international selection of world-class authorities, inspired by the work of Prof. Ahmed H. Sameh
- Examines various aspects of parallel algorithm-architecture interaction through articles on computational capacity-based codesign and automatic restructuring of programs using compilation techniques
- Reviews emerging applications of numerical methods in information retrieval and data mining
- Discusses the latest issues in dense and sparse matrix computations for modern high-performance systems, multicores, manycores and GPUs, and several perspectives on the Spike family of algorithms for solving linear systems
- Presents outstanding challenges and developing technologies, and puts these in their historical context
This authoritative reference is a must-read for researchers and graduate students in disciplines as diverse as computational fluid dynamics, signal processing, and structural mechanics. Professionals involved in applications that rely on high-performance computers will also find the text an essential resource.
Presenting the state of the art in parallel numerical algorithms, applications, architectures and system software, this book examines solutions for issues of concurrency, scale, energy efficiency and programmability, in a diverse range of applications.
Parallel Numerical Computing from Illiac IV to Exascale.- Computational Capacity-Based Co-design of Computer Systems.- Measuring Computer Performance.- A Compilation Framework for the Automatic Restructuring of Pointer-Linked Data Structures.- Dense Linear Algebra on Accelerated Multicore Hardware.- The Explicit SPIKE Algorithm.- The SPIKE Factorization as Domain Decomposition Method.- Parallel Solution of Sparse Linear Systems.- Parallel Block-Jacobi SVD Methods.- Robust and Efficient Multifrontal Solver for Large Discretized PDEs.- A Preconditioned Scheme for Nonsymmetric Saddle-Point Problems.- Effect of Ordering for Iterative Solvers in Structural Mechanics Problems.- Scaling Hypre's Multigrid Solvers to 100,000 Cores.- A Riemannian Dennis-Moré Condition.- A Jump-Start of Non-Negative Least Squares Solvers.- Fast Nonnegative Tensor Factorization with an Active-Set-Like Method.- Knowledge Discovery Using Nonnegative Tensor Factorization with Visual Analytics.
Inhaltsverzeichnis
Parallel Numerical Computing from Illiac IV to Exascale: The Contributions of Ahmed H. SamehK. Gallivan, E. Gallopoulos, A. Grama, B. Philippe, E. Polizzi, Y. Saad, F. Saied, and D. SorensenComputational Capacity-Based Co-design of Computer SystemsDavid J. KuckMeasuring Computer PerformanceWilliam Jalby, David C. Wong, David J. Kuck, Jean-Thomas Acquaviva, and Jean-Christophe BeylerA Compilation Framework for the Automatic Restructuring of Pointer-Linked Data StructuresHarmen L.A. van der Spek, C.W. Mattias Holm, and Harry A.G. WijshoffDense Linear Algebra on Accelerated Multicore HardwareJack Dongarra, Jakub Kurzak, Piotr Luszczek, and Stanimire TomovThe Explicit SPIKE Algorithm: Iterative Solution of the Reduced SystemCarl Christian Kjelgaard MikkelsenThe SPIKE Factorization as Domain Decomposition Method: Equivalent and Variant ApproachesVictor Eijkhout, and Robert van de GeijnParallel Solution of Sparse Linear SystemsMurat ManguogluParallel Block-Jacobi SVD MethodsMartin Becka, Gabriel OkSa, and Marián VajterSicRobust and Efficient Multifrontal Solver for Large Discretized PDEsJianlin XiaA Preconditioned Scheme for Nonsymmetric Saddle-Point ProblemsAbdelkader BaggagEffect of Ordering for Iterative Solvers in Structural Mechanics ProblemsSami A. KilicScaling Hypre's Multigrid Solvers to 100,000 CoresAllison H. Baker, Robert D. Falgout, Tzanio V. Kolev, and Ulrike Meier YangA Riemannian Dennis-Moré ConditionK.A. Gallivan, C. Qi, and P.-A. AbsilA Jump-Start of Non-Negative Least Squares SolversMu Wang, and Xiaoge WangFast Nonnegative Tensor Factorization with an Active-Set-Like MethodJingu Kim, and Haesun ParkKnowledge Discovery Using Nonnegative Tensor Factorization with Visual AnalyticsAndrey A. Puretskiy and Michael W. Berry
Klappentext
This book presents the state of the art in parallel numerical algorithms, applications, architectures, and system software. The book examines various solutions for issues of concurrency, scale, energy efficiency, and programmability, which are discussed in the context of a diverse range of applications. Features: includes contributions from an international selection of world-class authorities; examines parallel algorithm-architecture interaction through issues of computational capacity-based codesign and automatic restructuring of programs using compilation techniques; reviews emerging applications of numerical methods in information retrieval and data mining; discusses the latest issues in dense and sparse matrix computations for modern high-performance systems, multicores, manycores and GPUs, and several perspectives on the Spike family of algorithms for solving linear systems; presents outstanding challenges and developing technologies, and puts these in their historical context.
Presents the state of the art in parallel numerical algorithms, applications, architectures, and system software, with contributions from an international selection of world-class authorities
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Reviews emerging applications of numerical methods in information retrieval and data mining
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Presents outstanding challenges and developing technologies, and puts these in their historical context
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Includes supplementary material: sn.pub/extras
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