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This is an artifact for the MICRO'21 paper titled "AccelWattch: A Power Modeling Framework for Modern GPUs" AccelWattch v1.0 has been officially released and integrated with Accel-Sim v1.2.0. Please look at the AccelWattch webpage here: https://accel-sim.github.io/accelwattch.html and AccelWattch manual here: https://github.com/accel-sim/accel-sim-framework/blob/release-accelwattch/README.md
This work was partially funded by NSF awards CCF-1453853, CNS-1763743 and by a Discovery Grant from the Natural Sciences and Engineering Research Council of Canada. Tor M. Aamodt provides consulting services to Huawei Canada.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
| views | 33 | |
| downloads | 14 |

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