Unstructured scientific computation on scalable multiprocessors
Author(s)
Bibliographic Information
Unstructured scientific computation on scalable multiprocessors
（Scientific and engineering computation）
MIT Press, c1992
Available at 12 libraries
Note
Papers presented at a workshop held by ICASE in Nags Head, N.C. in Oct. 1990
Includes bibliographical references and index
Description and Table of Contents
Description
This book focuses on the implementation of such algorithms on parallel computers, such as hypercubes and the Connection Machine (R), that can be scaled up to incredible performances. Unstructured and dynamically varying algorithms are playing an increasingly important role in the solution of large-scale scientific problems on large-scale computers. This book focuses on the implementation of such algorithms on parallel computers, such as hypercubes and the Connection Machine (R), that can be scaled up to incredible performances. The algorithms covered include those for partial differential equations and sparse linear algebra.The nineteen contributions describe methods to effectively map fluids and structural mechanics codes that employ unstructured and/or adaptive meshes, scalable algorithms for problems in sparse linear algebra, scalable tools and compilers designed to handle irregular scientific computations, mapping methods for adaptive fast multipole methods, and parallelized grid generation and problem partitioning.
Table of Contents
- The free-lagrance method on the connection machine, Harold E. Trease and John H. Cerutti
- mapping unstructured grid problems to the connection machine, Steven W. Hammond and Robert Schreiber
- parallel unstructured grid generation, Reinald Lohner, et al
- unstructured three dimensional finite element simulations in data parallel architectures, Kapil K. Mathur
- the incremental scheduler, Raja Das, et al
- automated run-time scheduling of unstructured scientific computation on scalable multiprocessors, Tin-Fook Ngai, et al
- hardware and software architectures for irregular problem architectures, Geoffrey C. Fox
- mapping the adaptive fast multipole algorithm onto MIMD systems, James F. Leathrum, Jr and John A. Board, Jr
- massively parallel sparse-matrix computations, Steven G. Kratzer
- semi-structured refinement and parallel domain decomposition methods, William D. Gropp and David E. Keyes
- a moving mesh scheme for adaptive domain decomposition, Calvin J. Ribbens
- a hybrid spectral element-finite difference method for parallel computers, Ron Henderson and George Em Karniadakis
- some aspects of single-zone structured-grid CFD for a hypercube MIMD computer, Sukumar R. Chakravarthy and Sampath Palaniswamy
- mixed finite volume/finite element massively parallel computations - Euler flows, unstructured grids, and upwind approximations, Charbel Farhat, et al
- dynamic mapping of adaptive computations onto linear arrays, Kirk R. Pruhs, et al
- centralized and distributed dynamic scheduling for adaptive, parallel algorithms, Sharon L. Smith and Robert B. Schnabel
- random-access bandwidth and grid-based algorithms on massively parallel computers, William Celmaster
- performance of PDE sparse solvers on hypercubes, Mo Mu and John R. Rice
- scan directed load balancing for highly-parallel mesh-connected computers, Edoardo S. Biagioni and Jan F. Prins
- load balancing algorithms on the connection machine and their use in Monte-Carlo methods, Robert Frye and Jacek Myczkowski.
by "Nielsen BookData"