Limits of FPGA acceleration of 3D Green's Function computation for geophysical applications - Kapre, Nachiket (2015)
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.