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A multilevel approach that combines different parallel models is used for large-scale simulations on computing systems with massively-parallel accelerators.
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In addition, we explore different parallel programming models via programming assignments.
ELE 585 Parallel Computation The class reads seminal papers on different parallel programming models and computer architectures.
A study is presented of the implementation of four different parallel programming models in a code that solves the fluid flow equations on block structured meshes.
This paper presents a novel algorithm that automatically uses Servet for mapping parallel applications on multicore systems and analyzes its impact on three testbeds using three different parallel programming models: message-passing, shared memory and partitioned global address space (PGAS).
Different input variables lead to (3*2*4*3=72) parallel models were obtained by combining the variables as different scenarios.
Activation chain and parallel models describe two different mechanisms for generating sequential behavior.
Thus, simple modifications to the infrastructure underlying parallel models could produce different types of transition dynamics between modules (i.e., sequential progression and oscillatory dynamics).
The finding that grooming behavior displays both sequential and cyclic transitions between modules offers an extension to our understanding of the flexibility of parallel models in producing different types of serial behavior.
Three different parallel implementations of the proposed mathematical model have been developed; two of these implementations, i.e., the MPI and the PETSc codes, are based on a message passing paradigm, while the third one, i.e., the OpenMP code, is based on a shared space address paradigm.
Regarding the latter, two different approaches can be adopted: "model merging" and "parallel models".
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