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In this paper, we provide a fine-grained parallel scheme for anisotropic mesh adaptation on NUMA 1 architectures. Data dependencies are expressed by a graph for each kernel, and concurrency is extracted through fine-grained graph coloring. Tasks are structured into bulk-synchronous steps to avoid data races and to aggregate shared-data accesses. To ensure performance prediction, time cost and load imbalance are theoretically characterized. The devised scheme was evaluated on a 4 NUMA nodedoi:10.1016/j.proeng.2016.11.035 fatcat:zom63bc53bc43mn42dbsnebvuq