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Fast In-Memory Key-Value Cache System with RDMA

机译:具有RDMA的快速内存中键值缓存系统

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摘要

The quick advances of Cloud and the advent of Fog computing impose more and more critical demand for computing and data transfer of low latency onto the underlying distributed computing infrastructure. Remote direct memory access (RDMA) technology has been widely applied for its low latency of remote data access. However, RDMA gives rise to a host of challenges in accelerating in-memory key-value stores, such as direct remote memory writes, making the remote system more vulnerable. This study presents an in-memory key-value system based on RDMA, named Craftscached, which enables: (1) buffering remote memory writes into a communication cache memory to eliminate direct remote memory writes to the data memory area; (2) dividing the communication cache memory into RDMA-writable and RDMA-readable memory zones to reduce the possibility of data corruption due to stray memory writes and caching data into an RDMA-readable memory zone to improve the remote memory read performance; and (3) adopting remote out-of-place direct memory write to achieve high performance of remote read and write. Experimental results in comparison with Memcached indicate that Craftscached provides a far better performance: (1) in the case of read-intensive workloads, the data access of Craftscached is about 7-43x and 18-72.4% better than those of TCP/IP-based and RDMA-based Memcached, respectively; (2) the memory utilization of small objects is more efficient with only about 3.8% memory compaction overhead.
机译:Cloud的飞速发展和Fog计算的出现对低延迟到底层分布式计算基础架构的计算和数据传输提出了越来越关键的要求。远程直接内存访问(RDMA)技术因其低延迟的远程数据访问而被广泛应用。但是,RDMA在加速内存中键值存储(例如直接远程内存写入)方面带来了许多挑战,使远程系统更容易受到攻击。这项研究提出了一个基于RDMA的内存中键值系统,名为Craftscached,它可以:(1)将远程内存写缓冲到通信高速缓存中,以消除对数据存储区的直接远程写操作。 (2)将通信高速缓冲存储器划分为RDMA可写和RDMA可读存储区,以减少由于杂散存储器写入而造成数据损坏的可能性,并将数据高速缓存到RDMA可读存储区中,以提高远程存储器的读取性能; (3)采用远程异地直接存储写,以实现高性能的远程读写。与Memcached相比的实验结果表明,Craftscached提供了更好的性能:(1)在读取密集型工作负载的情况下,Craftscached的数据访问性能比TCP / IP-大约高7-43倍和18-72.4%,基于Memcached和基于RDMA的Memcached; (2)小对象的内存利用率更高,只有大约3.8%的内存压缩开销。

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