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High-Throughput Parallel SRAM-Based Hash Join Architecture on FPGA

机译:基于高吞吐量的并行SRAM的哈希在FPGA上加入架构

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The hash join operator is one of the most important relational operations used in database. The offloading and acceleration of this operation on hardware has been a technique of growing interest for a long time. However, the non-uniform distribution of data caused by hash collisions negatively affects the throughput of the hash join algorithm, owing the variation in the number of hash table accesses required for each lookup. To resolve this issue, a non-collision parallel static random-access memory (SRAM)-based hash join architecture is presented. This architecture utilizes multiple hash functions and content addressable memories (CAMs) to eliminate hash collision, thereby ensuring a worst constant memory access for each phase in the hash join algorithm and consequently improving the hash join throughput. The proposed architecture was implemented on a Xilinx field programmable gate array (FPGA), and the experimental results show that our design achieved a high hash join throughput of 153.6 million tuples per second, and a speedup factor of at least 2.5 with the best existing FPGA-based hash join architecture and a match rate of 50%.
机译:哈希加入运算符是数据库中使用的最重要的关系操作之一。这种在硬件上运行的卸载和加速已经是很长一段时间生长兴趣的技术。然而,由散列碰撞引起的数据的不均匀分布对散列连接算法的吞吐量产生负面影响,这是每个查找所需散列表访问数的变化。要解决此问题,介绍了非碰撞并行静态随机存取存储器(SRAM)的哈希连接架构。该架构利用多个哈希函数和内容可寻址存储器(CAM)来消除散列碰撞,从而确保散列连接算法中的每个阶段的最差常数存储器访问,从而改善散列连接吞吐量。所提出的架构在Xilinx现场可编程门阵列(FPGA)上实现,实验结果表明,我们的设计达到了每秒153.6百万元组的高哈希吞吐量,以及最佳现有FPGA的加速因子至少为2.5基于哈希连接架构和匹配率为50%。

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