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In den WarenkorbTaschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This project had its beginnings in the Fall of 1980. At that time Robert Wagner suggested that I investigate compiler optimi zation of data organization, suitable for use in a parallel or vector machine environment. We developed a scheme in which the compiler, having knowledge of the machine's access patterns, does a global analysis of a program's operations, and automatically determines optimum organization for the data. For example, for certain architectures and certain operations, large improvements in performance can be attained by storing a matrix in row major order. However a subsequent operation may require the matrix in column major order. A determination must be made whether or not it is the best solution globally to store the matrix in row order, column order, or even have two copies of it, each organized differently. We have developed two algorithms for making this determination. The technique shows promise in a vector machine environ ment, particularly if memory interleaving is used. Supercomputers such as the Cray, the CDC Cyber 205, the IBM 3090, as well as superminis such as the Convex are possible environments for implementation.
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Verlag: Springer US, Springer New York Dez 2011, 2011
ISBN 10: 1461291941 ISBN 13: 9781461291947
Sprache: Englisch
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In den WarenkorbTaschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This project had its beginnings in the Fall of 1980. At that time Robert Wagner suggested that I investigate compiler optimi zation of data organization, suitable for use in a parallel or vector machine environment. We developed a scheme in which the compiler, having knowledge of the machine's access patterns, does a global analysis of a program's operations, and automatically determines optimum organization for the data. For example, for certain architectures and certain operations, large improvements in performance can be attained by storing a matrix in row major order. However a subsequent operation may require the matrix in column major order. A determination must be made whether or not it is the best solution globally to store the matrix in row order, column order, or even have two copies of it, each organized differently. We have developed two algorithms for making this determination. The technique shows promise in a vector machine environ ment, particularly if memory interleaving is used. Supercomputers such as the Cray, the CDC Cyber 205, the IBM 3090, as well as superminis such as the Convex are possible environments for implementation.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 156 pp. Englisch.
Verlag: Springer-Verlag New York Inc., 2011
ISBN 10: 1461291941 ISBN 13: 9781461291947
Sprache: Englisch
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In den WarenkorbPaperback / softback. Zustand: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 257.
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In den WarenkorbZustand: New. PRINT ON DEMAND pp. 156.
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In den WarenkorbZustand: New. Print on Demand pp. 156 49:B&W 6.14 x 9.21 in or 234 x 156 mm (Royal 8vo) Perfect Bound on White w/Gloss Lam.
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In den WarenkorbTaschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This project had its beginnings in the Fall of 1980. At that time Robert Wagner suggested that I investigate compiler optimi zation of data organization, suitable for use in a parallel or vector machine environment. We developed a scheme in which the compiler, having knowledge of the machine's access patterns, does a global analysis of a program's operations, and automatically determines optimum organization for the data. For example, for certain architectures and certain operations, large improvements in performance can be attained by storing a matrix in row major order. However a subsequent operation may require the matrix in column major order. A determination must be made whether or not it is the best solution globally to store the matrix in row order, column order, or even have two copies of it, each organized differently. We have developed two algorithms for making this determination. The technique shows promise in a vector machine environ ment, particularly if memory interleaving is used. Supercomputers such as the Cray, the CDC Cyber 205, the IBM 3090, as well as superminis such as the Convex are possible environments for implementation. 156 pp. Englisch.