A Multilevel Parallelization Framework for High-Order Stencil Computations

Stencil based computation on structured grids is a common kernel to broad scientific applications. The order of stencils increases with the required precision, and it is a challenge to optimize such high-order stencils on multicore architectures. Here, we propose a multilevel parallelization framework that combines: (1) inter-node parallelism by spatial decomposition; (2) intra-chip parallelism through multithreading; and (3) data-level parallelism via single-instruction multiple-data (SIMD) techniques. The framework is applied to a 6 th order stencil based seismic wave propagation code on a suite of multicore architectures. Strong-scaling scalability tests exhibit superlinear speedup due to increasing cache capacity on Intel Harpertown and AMD Barcelona based clusters, whereas weak-scaling parallel efficiency is 0.92 on 65,536 BlueGene/P processors. Multithreading+SIMD optimizations achieve 7.85-fold speedup on a dual quad-core Intel Clovertown, and the data-level parallel efficiency is found to depend on the stencil order.