Graph partitioning for dynamic, adaptive and multi-phase scientific simulations
Graph partitioning for dynamic, adaptive and multi-phase scientific simulations
复制标题
用于动态、自适应和多阶段科学模拟的图形分区
DOI：
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发表时间：
2001
期刊：
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通讯作者：
Vipin Kumar
中科院分区：
文献类型：
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作者：
K. Schloegel;G. Karypis;Vipin Kumar
在 HPC 系统上高效执行科学模拟需要对处理器之间的底层网格进行分区，以便平衡负载并最大限度地减少处理器间通信。图划分算法已为此目的得到了巨大成功的应用。然而，多阶段和多物理计算的并行化提出了新的挑战，需要图分区技术的根本性进步。此外，大多数现有的图划分算法不适合较新的异构高性能计算平台。本次演讲将描述我们小组的研究工作，重点是开发新颖的多约束和多目标图划分算法，这些算法可以支持先进的数值模拟技术。此外，我们还将介绍我们关于非常适合异构架构的新分区算法的初步工作。
The efficient execution of scientific simulations on HPC systems requires a partitioning of the underlying mesh among the processors such that the load is balanced and the inter-processor communication is minimized. Graph partitioning algorithms have been applied with much success for this purpose. However, the parallelization of multi-phase and multi-physics computations poses new challenges that require fundamental advances in graph partitioning technology. In addition, most existing graph partitioning algorithms are not suited for the newer heterogeneous high-performance computing platforms. This talk will describe research efforts in our group that are focused on developing novel multi-constraint and multi-objective graph partitioning algorithms that can support the advancing state-of-the-art in numerical simulation technologies. In addition, we will present our preliminary work on new partitioning algorithms that are well suited for heterogeneous architectures.