Locality of computation is key to obtaining high performance on a broad variety of parallel architectures and applications. It is moreover an essential component of strategies for energy-efficient computing. OpenMP is a widely available industry standard for shared memory programming. With the pervasive deployment of multi-core computers and the steady growth in core count, a productive programming model such as OpenMP is increasingly expected to play an important role in adapting applications to this new hardware. However, OpenMP does not provide the programmer with explicit means to program for locality. Rather it presents the user with a “flat” memory model. In this paper, we discuss the need for explicit programmer control of locality within the context of OpenMP and present some ideas on how this might be accomplished. We describe potential extensions to OpenMP that would enable the user to manage a program's data layout and to align tasks and data in order to minimize the cost of data accesses. We give examples showing the intended use of the proposed features, describe our current implementation and present some experimental results. Our hope is that this work will lead to efforts that would help OpenMP to be a major player on emerging, multi- and many-core architectures.

中文翻译：

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在OpenMP中启用位置感知计算

计算的局部性是在各种并行架构和应用程序上获得高性能的关键。此外，它是节能计算策略的重要组成部分。OpenMP是用于共享内存编程的广泛可用的行业标准。随着多核计算机的广泛部署以及核数的稳定增长，人们越来越期望像OpenMP这样的高效编程模型在使应用程序适应这种新硬件方面起重要作用。但是，OpenMP并没有为程序员提供用于本地编程的明确方法。相反，它为用户提供了一个“扁平”存储模型。在本文中，我们讨论了在OpenMP上下文中对程序员进行显式控制局部性的需求，并提出了一些有关如何实现这一点的想法。我们描述了OpenMP的潜在扩展，这些扩展将使用户能够管理程序的数据布局以及对齐任务和数据，以最大程度地降低数据访问成本。我们提供了一些示例，这些示例显示了拟议功能的预期用途，描述了我们当前的实现方式并提供了一些实验结果。我们希望这项工作将导致有助于OpenMP成为新兴，多核和多核体系结构的主要参与者的努力。