Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/81212
Title: Limits of FPGA acceleration of 3D Green's Function computation for geophysical applications
Authors: Kapre, Nachiket
Kumar, Jayakrishnan Selva
Gupta, Parjanya
Masuti, Sagar
Barbot, Sylvain
Keywords: Computer Science and Engineering
Issue Date: 2015
Source: Kapre, N., Kumar, J. S., Gupta, P., Masuti, S., & Barbot, S. (2015). Limits of FPGA acceleration of 3D Green's Function computation for geophysical applications. 2015 25th International Conference on Field Programmable Logic and Applications (FPL), 1-8.
Abstract: 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.
URI: https://hdl.handle.net/10356/81212
http://hdl.handle.net/10220/39186
DOI: 10.1109/FPL.2015.7293942
Rights: © 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: [http://dx.doi.org/10.1109/FPL.2015.7293942].
Fulltext Permission: open
Fulltext Availability: With Fulltext
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