Parallel supercomputing: methods, algorithms, and applications
Presents the state of the art in parallel processing methods applications and algorithms. Describes architectures for parallel processing and includes a wealth of examples in computational fluid dynamics, structural analysis, and other engineering applications.
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Performance Limits for Parallel Processors
Overview of Current Developments in Parallel Architectures
Machine Independent Parallel Numerical Algorithms
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Amdahl's Law applied approximation architecture block calculations Cholesky factor column communication complexity Computer Science concurrency conjugate gradient method convergence CRAY X-MP data structure defined diagonal discretization Dongarra efficiency elimination tree elliptic example execution Figure finite element Fortran function given global graph grid components hypercube implementation inner loop iterative methods iWarp LAPACK Linear Algebra linear system machines matrix matrix-vector product megaflops memory mesh MFLOPS microtasking minimum degree multiprocessor National Laboratory nested dissection node number of iterations number of processors obtained operation count ordering outer parallel algorithms Parallel Computing parallel processing performance PiSOR pivoting polynomial positive definite preconditioner preconditioning problem procedure reordering residual rithm routines scalar scheme Section sequential serial SIAM SIMD simulation SLAP solution solve solver Sparse Matrix sparse numerical factorization speedup step storage subdomain subroutines supercomputers symmetric synchronization flags Table Technical Report techniques tion uniprocessor update UTCHEM values vector processing
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