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Distributed In-GPU Data Cache for Document-Oriented Data Store via PCIe over 10 Gbit Ethernet

机译:通过PCIe在10 Gbit以太网上分布于面向文档数据存储的GPU数据库中的内部数据库

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As one of NOSQL data stores, a document-oriented data store manages data as documents in a scheme-less manner. Various string match queries, such as a perfect match, begins-with (prefix) match, partial match, and regular expression based match, are performed for the documents. To accelerate such string match queries, we propose DistGPU Cache (Distributed In-GPU Data Cache), in which data store server and GPU devices are connected via a PCI-Express (PCIe) over 10 Gbit Ethernet (10GbE), so that GPU devices that store and search documents can be added and removed dynamically. We also propose a partitioning method that distributes ranges of cached documents to GPU devices based on a hash function. The distributed cache over GPU devices can be dynamically divided and merged when the GPU devices are added and removed, respectively. We evaluate the proposed DistGPU Cache in terms of regular expression match query throughput with up to three NVIDIA GeForce GTX 980 devices connected to a host via PCIe over 10 GbE. We demonstrate that the communication overhead of remote GPU devices is small and can be compensated by a great flexibility to add more GPU devices via a network. We also show that DistGPU Cache with the remote GPU devices significantly outperforms the original data store.
机译:作为NoSQL数据存储之一,面向文档的数据存储以更少的方案的方式管理数据作为文档。为文档执行各种字符串匹配查询,例如完美匹配,开始与(前缀)匹配,部分匹配和基于正则表达式的匹配。为了加速如此字符串匹配查询,我们提出了Distgpu高速缓存(分布式的GPU数据缓存),其中数据存储服务器和GPU设备通过超过10 Gbit以太网(10GBE)的PCI-Express(PCIe)连接,因此GPU设备可以动态地添加和删除该商店和搜索文档。我们还提出了一种分区方法,该方法基于散列函数将缓存文档的范围分配给GPU设备。在添加和移除GPU设备时,可以动态地分割和合并GPU设备上的分布式缓存。我们在正则表达式匹配查询吞吐量方面评估所提出的Distgpu缓存,该吞吐量最多可通过PCIe连接到主机10 GBE连接到主机的GTX 980设备。我们证明远程GPU设备的通信开销很小,可以通过网络通过网络添加更多GPU设备来补偿。我们还表明,具有远程GPU设备的Distgpu缓存显着优于原始数据存储。

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