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Implementation of a performance optimized database join operation on FPGA-GPU platforms using OpenCL

机译:使用OpenCL实现FPGA-GPU平台上的性能优化数据库连接操作

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The growing trend toward heterogeneous platforms is crucial to meet time and power consumption constraints for high-performance computing applications. The OpenCL parallel programming language and framework enable programming CPU, GPU and recently FPGAs using the same source code. This eases software developers to implement applications on various devices supported by heterogeneous HPC platforms. This work presents two very different FPGA implementations of a database join operation, one using a direct O(n2) algorithm, and the other using a bitonic sort network to speed up the join operation. Comparison of performance and energy consumption for both FPGA and GPUs is provided which suggests a 40% performance/watt improvement by using an FPGA instead of a GPU.
机译:异构平台的日益增长的趋势对于满足高性能计算应用的时间和功耗限制至关重要。 OpenCL并行编程语言和框架使用相同的源代码启用编程CPU,GPU和最近FPGA。这缓解了软件开发人员在异构HPC平台支持的各种设备上实现应用程序。这项工作具有数据库连接操作的两个非常不同的FPGA实现,一个使用Direct O(n 2 )算法,另一个使用BitOnic排序网络来加速连接操作。提供了FPGA和GPU的性能和能耗的比较,其表明通过使用FPGA而不是GPU来改善40 %的性能/瓦特。

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