PVM: Parallel virtual machine: a users' guide and tutorial for networked parallel computing
PVM: Parallel virtual machine: a users' guide and tutorial for networked parallel computing
Optimizing Supercompilers for Supercomputers
Optimizing Supercompilers for Supercomputers
Dependence Analysis for Supercomputing
Dependence Analysis for Supercomputing
Structure of Computers and Computations
Structure of Computers and Computations
A survey of distributed shared memory systems
HICSS '95 Proceedings of the 28th Hawaii International Conference on System Sciences
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A complex compressible Navier-Stokes equation using a time-accurate implicit difference scheme is parallelized using domain decomposition (DD) and loop parallelization methods. The numerical scheme used is a lower-upper alternating direction implicit (LU-ADI) factorization method with a Baldwin-Lomax (1978) turbulence model. This paper gives a preliminary result on the performance of the code on a distributed shared memory machine. The convergence rate and computational speed-up of these two methods are illustrated in the described numerical experiment. Generally, the loop parallelization shows better convergence and scaled speed-up than the domain decomposition method.