fpga上OpenCL数据库运算符的高效内核间通信

Tobias Drewes, J. Joseph, B. Gurumurthy, David Broneske, G. Saake, Thilo Pionteck
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引用次数: 2

摘要

许多现代数据库引擎使用OpenCL来瞄准异构硬件。查询通过执行低级操作符链来求值。OpenCL工作负载的通用范例使用片外内存中的缓冲区促进内核之间的通信。与cpu和gpu中可用的内存层次结构相比,由于fpga的内存系统较弱,这造成了严重的性能限制。为了克服这个瓶颈,我们建议对内核代码进行结构优化。分析了片上流水线和代码融合作为基于缓冲区的内核间通信的替代方案。我们评估了对资源利用率和系统吞吐量的影响,从而证明了结构合理的代码比默认范例实现了4倍以上的加速。这表明,对于内核链来说,不仅要考虑单个内核的优化技术,还要考虑内核间通信的优化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Efficient Inter-Kernel Communication for OpenCL Database Operators on FPGAs
Many modern database engines use OpenCL to target heterogeneous hardware. Queries are evaluated by execution of chains of low-level operators. The common paradigm for OpenCL workloads facilitates communication between kernels using buffers in off-chip memory. This poses a severe performance limitation due to weak memory systems of FPGAs in contrast to the memory hierarchy available in CPUs and GPUs. To overcome this bottleneck, we propose the use of structural optimizations of kernel code. On-chip pipelining and code fusion are analyzed as alternatives to buffer-based inter-kernel communication. We assess the impact on resource utilization and system throughput and thereby demonstrate that properly structured code achieves a speedup of more than 4x over the default paradigm. This shows that it is essential for chains of kernels to consider not only optimization techniques for individual kernels, but also optimization of inter-kernel communication.
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