A Scalable Body Bias Optimization Method Toward Low-Power CGRAs
A Scalable Body Bias Optimization Method Toward Low-Power CGRAs
复制标题
DOI：
10.1109/mm.2022.3226739
复制
发表时间：
2023-01
期刊：
影响因子：
3.6
通讯作者：
Takuya Kojima;Hayate Okuhara;Masaaki Kondo;H. Amano
中科院分区：
文献类型：
--
作者：
Takuya Kojima;Hayate Okuhara;Masaaki Kondo;H. Amano
体偏置是利用可重构设备（例如粗粒度可重构架构）实现更节能计算的关键技术之一。它的好处取决于控制粒度，而由于优化问题的复杂性，细粒度控制使得为每个域找到最佳体偏置电压变得具有挑战性。这项工作重新表述了优化问题，并引入了连续松弛，以比之前基于整数线性程序的工作更快地解决该问题。实验结果表明，所提出的方法可以在任何条件下针对所有基准测试在 0.5 s 内解决问题。对于中级问题，与之前的方法相比，可实现高达 5.65 倍的加速和 2.06 倍几何平均加速，且精度损失可以忽略不计。此外，考虑到片上体偏置发生器的功耗和面积开销，我们探索了更精细的体偏置控制，并建议最合理的设计可节省 66% 的能耗。
Body biasing is one of the critical techniques to realize more energy-efficient computing with reconfigurable devices, such as coarse-grained reconfigurable architectures. Its benefit depends on the control granularity, whereas fine-grained control makes it challenging to find the best body bias voltage for each domain due to the complexity of the optimization problem. This work reformulates the optimization problem and introduces continuous relaxation to solve it faster than previous work based on an integer linear program. Experimental result shows the proposed method can solve the problem within 0.5 s for all benchmarks in any conditions. For a middle-class problem, up to 5.65× speedup and a geometric mean of 2.06× speedup are demonstrated compared to the previous method with negligible loss of accuracy. Besides, we explore finer body bias control considering the power- and area-overhead of an on-chip body bias generator and suggest the most reasonable design saves 66% of energy consumption.