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首页> 外文期刊>International Journal of High Performance Computing Applications >PARTIAL DIFFERENTIAL EQUATION-BASED APPLICATIONS AND SOLVERS AT EXTREME SCALE
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PARTIAL DIFFERENTIAL EQUATION-BASED APPLICATIONS AND SOLVERS AT EXTREME SCALE

机译：基于偏微分方程的应用和极值求解

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摘要

Partial differential equation-based applications of multi-scale, multiphysics phenomena have driven the quest for extreme architectural scales since the foundation of modern digital computing and will continue to be principal among a broader set of science drivers for the foreseeable future. However, scientific and engineering drivers ceased long ago to dominate the computing industry and any commercially viable path to the petascale would seem to be through architectures that are assembled from components designed without the balance of resources required by scientific and engineering simulations foremost in mind. Concurrency will be massive and will involve many cores sharing common memory at the finest scales and severely dividing available memory bandwidth. As a result, algorithm designers will have to look beyond the message-passing-based SPMD paradigm that dominates today's most successful large-scale applications and solver frameworks, with stronger than ever emphasis on locality or operands and synchronization avoidance.
机译：自从现代数字计算的基础以来，基于偏微分方程的多尺度，多物理学现象的应用推动了对极端建筑尺度的追求，并且在可预见的未来，它将继续成为众多科学驱动因素中的主要因素。但是，很早以前，科学和工程驱动程序就停止了在计算行业的统治，并且任何通往商业规模的商业途径似乎都是通过从设计的组件组装而来的体系结构，而没有考虑到科学和工程仿真所需的资源平衡。并发将是巨大的，将涉及许多内核以最大规模共享公共内存并严重划分可用内存带宽。结果，算法设计人员将不得不超越基于消息传递的SPMD范式，该范式在当今最成功的大规模应用程序和求解器框架中占据主导地位，并且比以往任何时候都更加强调局部性或操作数以及避免同步。

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