Graphical fluid simulations are CPU‐bound. Parallelizing simulations on hundreds of cores in the computing cloud would make them faster, but requires evenly balancing load across nodes. Good load balancing depends on manual decisions from experts, which are time‐consuming and error prone, or dynamic approaches that estimate and react to future load, which are non‐deterministic and hard to debug.

中文翻译：

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使用微分区加速分布式图形流体模拟

图形流体模拟受 CPU 限制。在计算云中的数百个内核上并行模拟将使它们更快，但需要跨节点均衡负载。良好的负载平衡取决于专家的手动决策，这是耗时且容易出错的，或者依赖于估计和响应未来负载的动态方法，这些方法是不确定的且难以调试。