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Power- and area-efficient Approximate Wallace Tree Multiplier for error-resilient systems

机译:功率和面积效率高的近似华莱士树乘法器,用于抗错系统

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Today in sub-nanometer regime, chip/system designers add accuracy as a new constraint to optimize Latency-Power-Area (LPA) metrics. In this paper, we present a new power and area-efficient Approximate Wallace Tree Multiplier (AWTM) for error-tolerant applications. We propose a bit-width aware approximate multiplication algorithm for optimal design of our multiplier. We employ a carry-in prediction method to reduce the critical path. It is further augmented with hardware efficient precomputation of carry-in. We also optimize our multiplier design for latency, power and area using Wallace trees. Accuracy as well as LPA design metrics are used to evaluate our approximate multiplier designs of different bit-widths, i.e. 4 × 4, 8 × 8 and 16 × 16. The simulation results show that we obtain a mean accuracy of 99.85% to 99.965%. Single cycle implementation of AWTM gives almost 24% reduction in latency. We achieve significant reduction in power and area, i.e. up to 41.96% and 34.49% respectively that clearly demonstrates the merits of our proposed AWTM design. Finally, AWTM is used to perform a real time application on a benchmark image. We obtain up to 39% reduction in power and 30% reduction in area without any loss in image quality.
机译:如今,在亚纳米范围内,芯片/系统设计人员将准确性作为优化延迟功耗区域(LPA)指标的新约束。在本文中,我们针对容错应用提出了一种新的功率和面积有效的近似华莱士树乘法器(AWTM)。我们提出了一种位宽感知的近似乘法算法,用于乘法器的优化设计。我们采用一种随身携带的预测方法来减少关键路径。随身携带的硬件有效的预计算功能进一步增强了该功能。我们还使用华莱士树针对延迟,功耗和面积优化了乘法器设计。精度以及LPA设计指标用于评估我们不同位宽(即4×4、8×8和16×16)的近似乘法器设计。仿真结果表明,我们获得了99.85%至99.965%的平均精度。 。 AWTM的单周期实施可将延迟降低近24%。我们显着降低了功率和面积,即分别降低了41.96%和34.49%,这清楚地证明了我们提出的AWTM设计的优点。最后,AWTM用于对基准图像执行实时应用。我们获得了多达39%的功耗降低和30%的面积缩减,而没有图像质量的损失。

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