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Terabyte Sort on FPGA-Accelerated Flash Storage

机译:TB级加速FPGA闪存存储

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摘要

Sorting is one of the most fundamental and useful applications in computer science, and continues to be an important tool in analyzing large datasets. An important and challenging subclass of sorting problems involves sorting terabyte scale datasets with hundreds of billions of records. The conventional method of sorting such large amounts of data is to distribute the data and computation over a cluster of machines. Such solutions can be fast but are often expensive and power-hungry. In this paper, we propose a solution based on flash storage connected to a collection of FPGA-based sorting accelerators that perform large-scale merge-sort in storage. The accelerators include highly efficient sorting networks and merge trees that use bitonic sorting to emit multiple sorted values every cycle. We show that by appropriate use of accelerators we can remove all the computation bottlenecks so that the end-to-end sorting performance is limited only by the flash storage bandwidth. We demonstrate that our flash-based system matches the performance of existing distributed-cluster solutions of much larger scale. More importantly, our prototype is able to show almost twice the power efficiency compared to the existing Joulesort record holder. An optimized system with less wasteful components is projected to be four times more efficient compared to the current record holder, sorting over 200,000 records per joule of energy.
机译:排序是计算机科学中最基本和最有用的应用之一,并且仍然是分析大型数据集的重要工具。排序问题的一个重要且具有挑战性的子类涉及对具有数千亿条记录的TB级数据集进行排序。排序如此大量数据的常规方法是在一组机器上分布数据和进行计算。这样的解决方案可能很快,但通常很昂贵且耗电。在本文中,我们提出了一种基于闪存的解决方案,该解决方案连接到一组基于FPGA的排序加速器,这些加速器在存储中执行大规模合并排序。加速器包括高效的排序网络和合并树,这些树使用双音排序在每个循环中发出多个排序值。我们表明,通过适当地使用加速器,我们可以消除所有计算瓶颈,从而使端到端排序性能仅受闪存存储带宽的限制。我们证明了基于闪存的系统与现有规模更大的分布式集群解决方案的性能相匹配。更重要的是,与现有的Joulesort唱片保持器相比,我们的原型能够显示几乎两倍的功率效率。经过优化的系统,与现有的记录保持器相比,具有更少浪费的组件的效率将提高四倍,每焦耳能量可分类200,000条记录。

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