The introduction of dynamic power management strategies such as clock gating and power gating in dataflow networks has been shown to provide significant energy savings when applied during idle times. However, these strategies can also degrade throughput due to shutdown and wake-up delays. Such throughput degradations might be particularly detrimental to signal processing systems that require a guaranteed throughput. As a solution, this paper first contributes a linear-program formulation for finding a periodic maximal-throughput schedule of a given so-called self-powering dataflow network where actors, realized in hardware, are allowed to go to sleep whenever not being enabled to fire. Depending on which actors are allowed to power down, tradeoffs between throughput and energy savings can be obtained. As a second contribution, we propose a mixed-integer-linear-program formulation to determine a periodic schedule that satisfies a given throughput while minimizing the overall energy per period by identifying a respective set of actors that is allowed to power down in phases of idleness and which rather not. Finally, as a third contribution, we propose a multi-objective design-space exploration strategy called "Hop and Skip" to efficiently explore the Pareto front of energy and throughput solutions. Experimental evaluations on a set of existing benchmarks and randomly generated graphs witness significant exploration time reductions over a brute-force sweep. Finally, a real-world case study is elaborated, and we report on achievable energy savings and throughputs of the related dataflow network where (a) all actors are always-active, (b) all actors are self-powered, and (c) all optimal energy and throughput tradeoff points as found by the proposed design-space exploration strategy.

翻译：在数据流网络中采用时钟门控和电源门控等动态功耗管理策略，已被证明在空闲期间能够显著节省能耗。然而，这些策略也可能因关断和唤醒延迟而降低吞吐量。这种吞吐量下降对于需要保证吞吐量的信号处理系统尤为不利。为解决此问题，本文首先提出一种线性规划方法，用于为给定的所谓自供电数据流网络寻找周期性最大吞吐量调度，其中以硬件实现的执行体在不被触发执行时可进入休眠状态。根据允许断电的执行体不同，可在吞吐量与能耗节省之间取得折衷。其次，我们提出一种混合整数线性规划方法，通过识别允许在空闲阶段断电以及不允许断电的执行体集合，确定满足给定吞吐量的周期性调度，同时最小化每周期总能耗。最后，作为第三项贡献，我们提出一种名为"HOP AND SKIP"的多目标设计空间探索策略，以高效探索能耗与吞吐量解的帕累托前沿。对现有基准测试集和随机生成图的实验评估表明，与暴力搜索相比，探索时间显著缩短。此外，我们通过对实际案例的研究，报告了在以下情况下相关数据流网络的可实现能耗节省与吞吐量：(a)所有执行体始终活跃，(b)所有执行体自供电，(c)采用所提出的设计空间探索策略找到的所有最优能耗与吞吐量权衡点。