Description
Taylor & Francis Ltd Parallel Computingmethods Algorithms And Applications 1989 Edition by D.J Evans, C.N Sutti
Parallel Computing: Methods, Algorithms and Applications presents a collection of original papers presented at the international meeting on parallel processing, methods, algorithms, and applications at Verona, Italy in September 1989. Parallel algorithm design (D J Evans). Tools for parallel algorithms development (J J Dongarra and D Levine). Parallel computation and supercomputers (U Schendel). Parallel iterative methods for solving sparse sets of linear equations (L C W Dixon). Parallel algorithms for sparse matrix solutions (I S Duff). Vectorizing the modified Huang algorithm of the ABS class on the IBM 3090 (M Bertocchi and E Speditcato). Solving linear systems of equations on message passing multiprocessors - complexity and integration (M Consard). A vector implementation of conjugate gradient-like algorithms for general sparsity substructures (G Radicati di Brozolo and T Robert). Substructure technique for parallel solution in linear systems in finite element analysis ( L Brusa and F Riccio). The arithmetic mean method for solving large systems of linear ordinary differential equations on a vector computer (I Galligani and V Ruggiero). Domain decomposition methods for partial differential equations (A Quarteroni). Highly accurate parallel algorithms in fluid dynamics (C Canuto). Fluid dynamics models for inertial confinement fusion on vector multiprocessors (S Atzeni). Applications of highly parallel computers ( H M Lidell and D Parkinson). New and advanced computing tools for constrained optimization of large scale complex systems - a case study on the parallel vector supercomputers CRAY X MP/48 and IBM 3090 VF 200 (L Grandinetti). Vector and parallel processing applications of nonlinear optimization algorithms (G Patrizi and C Spera). Vector and parallel processing performances of minimization algorithms based on homogeneous models (A Peretti and C Sutti). Parallel algorithms in numerical optimization (F Zirilli). Expert systems for numerical optimization - parallel computation (J J McKeown). Complexity of parallel polynomial computations (D Bini). Toeplitz matrices and least square approximation (F Sloboda). Parallel computation and computers for coupled numerical and symbolic applications (J S Kowalik). Parallel Fortran. Why you can't. How you can (C Arnold).