How a single chip causes massive power bills GPUSimPow: A GPGPU power simulator

Start Page
97
End Page
106
Article Number
6557150
Citation
IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS 2013)
Contribution to Conference
IEEE International Symposium on Performance Analysis of Systems and Software, ISPASS 2013  
Publisher DOI
10.1109/ISPASS.2013.6557150
Scopus ID
2-s2.0-84881440334
Modern GPUs are true power houses in every meaning of the word: While they offer general-purpose (GPGPU) compute performance an order of magnitude higher than that of conventional CPUs, they have also been rapidly approaching the infamous 'power wall', as a single chip sometimes consumes more than 300W. Thus, the design space of GPGPU microarchitecture has been extended by another dimension: power. While GPU researchers have previously relied on cycle-accurate simulators for estimating performance during design cycles, there are no simulation tools that include power as well. To mitigate this issue, we introduce the GPUSimPow power estimation framework for GPGPUs consisting of both analytical and empirical models for regular and irregular hardware components. To validate this framework, we build a custom measurement setup to obtain power numbers from real graphics cards. An evaluation on a set of well-known benchmarks reveals an average relative error of 11.7% between simulated and hardware power for GT240 and an average relative error of 10.8% for GTX580. The simulator has been made available to the public [1].
DDC Class
600: Technology