Summary
We present the parallelization of a commercial streamline simulator to multicore architectures based on the OpenMP programming model and its performance on various field examples. This work is a continuation of recent work by Gerritsen et al. (2009) in which a research streamline simulator was extended to parallel execution.
We identified that the streamline-transport step represents approximately 40-80% of the total run time. It is exactly this step that is straightforward to parallelize owing to the independent solution of each streamline that is at the heart of streamline simulation. Because we are working with an existing large serial code, we used specialty software to quickly and easily identify variables that required particular handling for implementing the parallel extension. Minimal rewrite to existing code was required to extend the streamline-transport step to OpenMP. As part of this work, we also parallelized additional run-time code, including the gravity-line solver and some simple routines required for constructing the pressure matrix. Overall, the run-time fraction of code parallelized ranged from 0.50 to 0.83, depending on the transport physics being considered.
We tested our parallel simulator on a variety of large models including SPE 10, Forties-a UK oil/water model, Judy Creek-a Canadian waterflood/water-alternating-gas (WAG) model, and a South American black-oil model. We noted overall speedup factors from 1.8 to 3.3x for eight threads. In terms of real time, this implies that large-scale streamline simulation models as tested here can be simulated in less than 4 hours. We found speedup results to be reasonable when compared with Amdahl's ideal scaling law. Beyond eight threads, we observed minimal speedups because of memory bandwidth limits on our test machine.
An Efficient and Balanced Graph Partition Algorithm for the Subgraph-Centric Programming Model on Large-scale Power-law Graphs
