论文标题
浸入边界方法的细粒平行化
A fine-grained parallelization of the immersed boundary method
论文作者
论文摘要
我们提出了新算法，用于在浸入边界方法中并行化Eulerian-Lagrangian相互作用操作。我们的算法依赖于两个经过良好研究的平行原语：键值排序和分割减少。这些平行原始图的使用使我们能够在两个图形处理单元（GPU）和其他共享内存体系结构上实现算法。我们在涉及分散点和弹性结构的问题上提出了强烈和弱的缩放测试。我们的测试表明，我们的算法在多核CPU和GPU上都显示出近乎理想的缩放。
We present new algorithms for the parallelization of Eulerian-Lagrangian interaction operations in the immersed boundary method. Our algorithms rely on two well-studied parallel primitives: key-value sort and segmented reduce. The use of these parallel primitives allows us to implement our algorithms on both graphics processing units (GPUs) and on other shared memory architectures. We present strong and weak scaling tests on problems involving scattered points and elastic structures. Our tests show that our algorithms exhibit near-ideal scaling on both multicore CPUs and GPUs.
