Beyond 16GB: Out-of-Core Stencil Computations

Istán Z. Reguly, G. Mudalige, M. Giles
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引用次数: 9

Abstract

Stencil computations are a key class of applications, widely used in the scientific computing community, and a class that has particularly benefited from performance improvements on architectures with high memory bandwidth. Unfortunately, such architectures come with a limited amount of fast memory, which is limiting the size of the problems that can be efficiently solved. In this paper, we address this challenge by applying the well-known cache-blocking tiling technique to large scale stencil codes implemented using the OPS domain specific language, such as CloverLeaf 2D, CloverLeaf 3D, and OpenSBLI. We introduce a number of techniques and optimisations to help manage data resident in fast memory, and minimise data movement. Evaluating our work on Intel's Knights Landing Platform as well as NVIDIA P100 GPUs, we demonstrate that it is possible to solve 3 times larger problems than the on-chip memory size with at most 15% loss in efficiency.
超过16GB:核外模板计算
模板计算是应用程序的一个关键类别,在科学计算社区中广泛使用,并且该类特别受益于具有高内存带宽的体系结构的性能改进。不幸的是,这种架构的快速内存数量有限,这限制了可以有效解决的问题的大小。在本文中,我们通过将众所周知的缓存阻塞贴片技术应用于使用OPS领域特定语言(如CloverLeaf 2D, CloverLeaf 3D和OpenSBLI)实现的大规模模板代码来解决这一挑战。我们引入了许多技术和优化来帮助管理驻留在快速内存中的数据,并最大限度地减少数据移动。评估我们在英特尔骑士登陆平台和NVIDIA P100 gpu上的工作,我们证明有可能在效率损失最多15%的情况下解决比片上存储器大小大3倍的问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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