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Limits of FPGA acceleration of 3D Green's Function computation for geophysical applications

机译:用于地球物理应用的3D Green函数计算的FPGA加速限制

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FPGA-based accelerators can outperform multi-core, GPU and Xeon Phi based platforms by at as much as 2.8× for 3D Green's Function processing in geophysics while delivering superior energy efficiency. FPGAs can efficiently implement a complex mixture of compute patterns that include data-parallelism, reductions, dataflow and streaming computations using spatial parallelism to deliver these speedups and power benefits. Since 3D Green's Function is highly-parallel but communication bound, we optimize the FPGA implementation by considering loop restructuring and tiling optimizations to minimize and regularize off-chip accesses. Furthermore, we configure the FPGA to implement the key compute intensive kernels at double-precision as well as single-precision to exploit the uncertainty in measurements of earthquake monitoring sensors. For 512×512×512 problem size, the Xilinx SX475T (Maxeler MAX3) outperforms the fastest architecture by 1.1–1.4× (double-precision), 2.2–2.8× (single-precision) with 1.2× better energy efficiency.
机译:基于FPGA的加速器在地球物理中实现3D Green的功能处理时,性能可比基于多核,GPU和至强融核的平台高出2.8倍,同时还具有出色的能源效率。 FPGA可以有效地实现复杂的计算模式混合,包括使用空间并行性来实现这些加速和功耗优势的数据并行性,约简,数据流和流式计算。由于3D Green的功能是高度并行的,但受到通信的限制,因此我们通过考虑环路重构和切片优化来最小化和规范化片外访问,从而优化了FPGA的实现。此外,我们将FPGA配置为以双精度和单精度实施关键计算密集型内核,以利用地震监测传感器测量中的不确定性。对于512×512×512的问题尺寸,Xilinx SX475T(Maxeler MAX3)的性能比最快的架构高1.1–1.4×(双精度),2.2–2.8×(单精度)和1.2倍的能效。

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