MixFX-SCORE:数据流计算的异构定点编译

João Paiva, L. Rodrigues
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引用次数: 7

摘要

混合精度计算实现可以在均匀固定精度电路上为数据流计算提供面积、吞吐量和功耗方面的改进,而不会损失任何精度。在为可重构硬件设计电路时,我们可以对计算中每个变量的位宽选择进行独立控制。然而,为每个变量选择最佳精度是一个np困难问题。虽然传统的解决方案使用自动启发式方法,如模拟退火或整数线性规划,但它们仍然依赖于手动制定资源模型,这可能是繁琐的,并且由于FPGA CAD流程的不同阶段之间不可预测的相互作用而可能不准确。我们开发了MixFX-SCORE,这是一个基于FX-SCORE定点编译框架和模拟退火的自动化工具流,以解决这一挑战。我们将错误分析(gappa++)和资源模型生成(Vivado HLS、Logic Synthesis、Xilinx Place-and-Route)外包给外部工具,这些工具可以更准确地表示错误行为(有证据支持)和资源使用(基于实际利用)。我们演示了1.1 - 3.5倍的lut计数节省,1 - 1.8倍的DSP计数减少,以及1 - 3.9倍的动态功率改进,同时与同质定点实现相比仍然满足精度限制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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 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.
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