MixFX-SCORE: Heterogeneous Fixed-Point Compilation of Dataflow Computations

Mixed-precision implementation of computation can deliver area, throughput and power improvements for dataflow computations over homogeneous fixed-precision circuits without any loss in accuracy. When designing circuits for reconfigurable hardware, we can exercise independent control over bitwidth s...

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Main Authors: Ye, Deheng, Kapre, Nachiket
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/10356/81246
http://hdl.handle.net/10220/39194
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-812462020-05-28T07:18:12Z MixFX-SCORE: Heterogeneous Fixed-Point Compilation of Dataflow Computations Ye, Deheng Kapre, Nachiket School of Computer Engineering 2014 IEEE 22nd Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM) Computer Science and Engineering Mixed-precision implementation of computation can deliver area, throughput and power improvements for dataflow computations over homogeneous fixed-precision circuits without any loss in accuracy. When designing circuits for reconfigurable hardware, we can exercise independent control over bitwidth selection of each variable in the computation. However, selecting the best precision for each variable is an NP-hard problem. While traditional solutions use automated heuristics like simulated annealing or integer linear programming, they still rely on the manual formulation of resource models, which can be tedious, and potentially inaccurate due to the unpredictable interactions between different stages of the FPGA CAD flow. We develop MixFX-SCORE, an automated tool-flow based on FX-SCORE fixed-point compilation framework and simulated annealing, to address this challenge. We outsource error analysis (Gappa++) and resource model generation (Vivado HLS, Logic Synthesis, Xilinx Place-and-Route) to external tools that offer a more accurate representation of error behavior (backed by proofs) and resource usage (based on actual utilization). We demonstrate 1.1-3.5x LUTs count savings, 1-1.8x DSP count reductions, and 1-3.9x dynamic power improvements while still satisfying the accuracy constraints when compared to homogeneous fixed-point implementations. Accepted version 2015-12-21T07:19:31Z 2019-12-06T14:26:27Z 2015-12-21T07:19:31Z 2019-12-06T14:26:27Z 2014 Conference Paper Ye, D., & Kapre, N. (2014). MixFX-SCORE: Heterogeneous Fixed-Point Compilation of Dataflow Computations. 2014 IEEE 22nd Annual International Symposium on Field-Programmable Custom Computing Machines, 206-209. https://hdl.handle.net/10356/81246 http://hdl.handle.net/10220/39194 10.1109/FCCM.2014.64 en © 2014 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/FCCM.2014.64]. 4 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
Ye, Deheng
Kapre, Nachiket
MixFX-SCORE: Heterogeneous Fixed-Point Compilation of Dataflow Computations
description Mixed-precision implementation of computation can deliver area, throughput and power improvements for dataflow computations over homogeneous fixed-precision circuits without any loss in accuracy. When designing circuits for reconfigurable hardware, we can exercise independent control over bitwidth selection of each variable in the computation. However, selecting the best precision for each variable is an NP-hard problem. While traditional solutions use automated heuristics like simulated annealing or integer linear programming, they still rely on the manual formulation of resource models, which can be tedious, and potentially inaccurate due to the unpredictable interactions between different stages of the FPGA CAD flow. We develop MixFX-SCORE, an automated tool-flow based on FX-SCORE fixed-point compilation framework and simulated annealing, to address this challenge. We outsource error analysis (Gappa++) and resource model generation (Vivado HLS, Logic Synthesis, Xilinx Place-and-Route) to external tools that offer a more accurate representation of error behavior (backed by proofs) and resource usage (based on actual utilization). We demonstrate 1.1-3.5x LUTs count savings, 1-1.8x DSP count reductions, and 1-3.9x dynamic power improvements while still satisfying the accuracy constraints when compared to homogeneous fixed-point implementations.
author2 School of Computer Engineering
author_facet School of Computer Engineering
Ye, Deheng
Kapre, Nachiket
format Conference or Workshop Item
author Ye, Deheng
Kapre, Nachiket
author_sort Ye, Deheng
title MixFX-SCORE: Heterogeneous Fixed-Point Compilation of Dataflow Computations
title_short MixFX-SCORE: Heterogeneous Fixed-Point Compilation of Dataflow Computations
title_full MixFX-SCORE: Heterogeneous Fixed-Point Compilation of Dataflow Computations
title_fullStr MixFX-SCORE: Heterogeneous Fixed-Point Compilation of Dataflow Computations
title_full_unstemmed MixFX-SCORE: Heterogeneous Fixed-Point Compilation of Dataflow Computations
title_sort mixfx-score: heterogeneous fixed-point compilation of dataflow computations
publishDate 2015
url https://hdl.handle.net/10356/81246
http://hdl.handle.net/10220/39194
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