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

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-paralle...

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Main Authors: Kapre, Nachiket, Kumar, Jayakrishnan Selva, Gupta, Parjanya, Masuti, Sagar, Barbot, Sylvain
Other Authors: School of Computer Engineering
Format: Conference or Workshop Item
Language:English
Published: 2015
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Online Access:https://hdl.handle.net/10356/81212
http://hdl.handle.net/10220/39186
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-812122020-09-26T21:24:16Z Limits of FPGA acceleration of 3D Green's Function computation for geophysical applications Kapre, Nachiket Kumar, Jayakrishnan Selva Gupta, Parjanya Masuti, Sagar Barbot, Sylvain School of Computer Engineering 2015 25th International Conference on Field Programmable Logic and Applications (FPL) Earth Observatory of Singapore Earth Observatory of Singapore Computer Science and Engineering 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. Accepted version 2015-12-21T06:25:04Z 2019-12-06T14:23:46Z 2015-12-21T06:25:04Z 2019-12-06T14:23:46Z 2015 Conference Paper 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. https://hdl.handle.net/10356/81212 http://hdl.handle.net/10220/39186 10.1109/FPL.2015.7293942 en © 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]. 8 p. application/pdf
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic Computer Science and Engineering
spellingShingle Computer Science and Engineering
Kapre, Nachiket
Kumar, Jayakrishnan Selva
Gupta, Parjanya
Masuti, Sagar
Barbot, Sylvain
Limits of FPGA acceleration of 3D Green's Function computation for geophysical applications
description 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.
author2 School of Computer Engineering
author_facet School of Computer Engineering
Kapre, Nachiket
Kumar, Jayakrishnan Selva
Gupta, Parjanya
Masuti, Sagar
Barbot, Sylvain
format Conference or Workshop Item
author Kapre, Nachiket
Kumar, Jayakrishnan Selva
Gupta, Parjanya
Masuti, Sagar
Barbot, Sylvain
author_sort Kapre, Nachiket
title Limits of FPGA acceleration of 3D Green's Function computation for geophysical applications
title_short Limits of FPGA acceleration of 3D Green's Function computation for geophysical applications
title_full Limits of FPGA acceleration of 3D Green's Function computation for geophysical applications
title_fullStr Limits of FPGA acceleration of 3D Green's Function computation for geophysical applications
title_full_unstemmed Limits of FPGA acceleration of 3D Green's Function computation for geophysical applications
title_sort limits of fpga acceleration of 3d green's function computation for geophysical applications
publishDate 2015
url https://hdl.handle.net/10356/81212
http://hdl.handle.net/10220/39186
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