PIGO: A Parallel Graph Input/Output Library

Kasimir Gabert, Ümit V. Çatalyürek
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引用次数: 4

Abstract

Graph and sparse matrix systems are highly tuned, able to run complex graph analytics in fractions of seconds on billion-edge graphs. For both developers and researchers, the focus has been on computational kernels and not end-to-end runtime. Despite the significant improvements that modern hardware and operating systems have made towards input and output, these can still become application bottlenecks. Unfortunately, on high-performance shared-memory graph systems running billion-scale graphs, reading the graph from file systems easily takes over 2000× longer than running the computational kernel. This slowdown causes both a disconnect for end users and a loss of productivity for researchers and developers.We close the gap by providing a simple to use, small, header-only, and dependency-free C++11 library that brings I/O improvements to graph and matrix systems. Using our library, we improve the end-to-end performance for state-of-the-art systems significantly—in many cases by over 40×.
一个并行图形输入/输出库
图和稀疏矩阵系统是高度可调的,能够在几秒钟内对十亿边图运行复杂的图分析。对于开发人员和研究人员来说,重点是计算内核,而不是端到端运行时。尽管现代硬件和操作系统在输入和输出方面做出了重大改进,但这些仍然可能成为应用程序的瓶颈。不幸的是,在运行数十亿规模图形的高性能共享内存图形系统上,从文件系统读取图形所花费的时间很容易超过运行计算内核的2000倍。这种减速既会导致最终用户的脱节,也会导致研究人员和开发人员的生产力下降。我们提供了一个易于使用的、小型的、仅限头文件的、无依赖的c++ 11库,它为图形和矩阵系统带来了I/O改进,从而缩小了这一差距。使用我们的库,我们显著提高了最先进系统的端到端性能——在许多情况下提高了40倍以上。
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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