Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/81246
Title: MixFX-SCORE: Heterogeneous Fixed-Point Compilation of Dataflow Computations
Authors: Ye, Deheng
Kapre, Nachiket
Keywords: Computer Science and Engineering
Issue Date: 2014
Source: 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.
Abstract: 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.
URI: https://hdl.handle.net/10356/81246
http://hdl.handle.net/10220/39194
DOI: 10.1109/FCCM.2014.64
Rights: © 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].
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Conference Papers

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