AccelWattch: A Power Modeling Framework for Modern GPUs
AccelWattch: A Power Modeling Framework for Modern GPUs
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DOI：
10.1145/3466752.3480063
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发表时间：
2021-10
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通讯作者：
Vijay Kandiah;Scott Peverelle;Mahmoud Khairy;Junrui Pan;Amogh Manjunath;Timothy G. Rogers;Tor M. Aamodt;Nikolaos Hardavellas
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作者：
Vijay Kandiah;Scott Peverelle;Mahmoud Khairy;Junrui Pan;Amogh Manjunath;Timothy G. Rogers;Tor M. Aamodt;Nikolaos Hardavellas
图形处理单元（GPU）迅速统治了加速器空间，如其在数据分析和机器学习市场中的广泛采用所示。同时，每瓦的性能已成为至关重要的评估度量以及峰值性能。因此，GPU建筑师需要强大的工具，使其能够对现代GPU的性能和功耗进行建模。但是，尽管GPU性能建模取得了长足的进步，但功率建模却落后了。为了减轻这个问题，我们提出了Accelwattch，这是一种可配置的GPU功率模型，可以解决两个长期的需求：缺乏用于现代GPU体系结构的详细且准确的周期级功率模型，以及无法捕获其恒定和静态功率的现有电源工具。 Accelwattch可以由仿真和跟踪驱动的环境，硬件计数器或两个模型PTX和SASS ISA的组合来驱动，并说明了电源门控和控制流差异，并支持DVFS。我们将Accelwattch与GPGPU-SIM和Accel-SIM集成在一起，以促进其广泛使用。我们在NVIDIA Volta GPU上验证了Accelwattch，并表明它与硬件功率测量达到了牢固的相关性。最后，我们证明了Accelwattch可以启用可靠的设计空间探索：通过直接在类似于Nvidia Pascal和Turing GPU的GPU配置上使用AccelWattch调整为Volta，我们获得了这些架构的准确功率模型。
Graphics Processing Units (GPUs) are rapidly dominating the accelerator space, as illustrated by their wide-spread adoption in the data analytics and machine learning markets. At the same time, performance per watt has emerged as a crucial evaluation metric together with peak performance. As such, GPU architects require robust tools that will enable them to model both the performance and the power consumption of modern GPUs. However, while GPU performance modeling has progressed in great strides, power modeling has lagged behind. To mitigate this problem we propose AccelWattch, a configurable GPU power model that resolves two long-standing needs: the lack of a detailed and accurate cycle-level power model for modern GPU architectures, and the inability to capture their constant and static power with existing tools. AccelWattch can be driven by emulation and trace-driven environments, hardware counters, or a mix of the two, models both PTX and SASS ISAs, accounts for power gating and control-flow divergence, and supports DVFS. We integrate AccelWattch with GPGPU-Sim and Accel-Sim to facilitate its widespread use. We validate AccelWattch on a NVIDIA Volta GPU, and show that it achieves strong correlation against hardware power measurements. Finally, we demonstrate that AccelWattch can enable reliable design space exploration: by directly applying AccelWattch tuned for Volta on GPU configurations resembling NVIDIA Pascal and Turing GPUs, we obtain accurate power models for these architectures.