Wattch: a framework for architectural-level power analysis and optimizations
Proceedings of the 27th annual international symposium on Computer architecture
Runtime Power Monitoring in High-End Processors: Methodology and Empirical Data
Proceedings of the 36th annual IEEE/ACM International Symposium on Microarchitecture
Power prediction for intel XScale® processors using performance monitoring unit events
ISLPED '05 Proceedings of the 2005 international symposium on Low power electronics and design
Energy consumption in mobile phones: a measurement study and implications for network applications
Proceedings of the 9th ACM SIGCOMM conference on Internet measurement conference
Proceedings of the 42nd Annual IEEE/ACM International Symposium on Microarchitecture
PowerPack: Energy Profiling and Analysis of High-Performance Systems and Applications
IEEE Transactions on Parallel and Distributed Systems
An integrated GPU power and performance model
Proceedings of the 37th annual international symposium on Computer architecture
CODES/ISSS '10 Proceedings of the eighth IEEE/ACM/IFIP international conference on Hardware/software codesign and system synthesis
Statistical power modeling of GPU kernels using performance counters
GREENCOMP '10 Proceedings of the International Conference on Green Computing
Fine-grained power modeling for smartphones using system call tracing
Proceedings of the sixth conference on Computer systems
Where is the energy spent inside my app?: fine grained energy accounting on smartphones with Eprof
Proceedings of the 7th ACM european conference on Computer Systems
Statistical GPU power analysis using tree-based methods
IGCC '11 Proceedings of the 2011 International Green Computing Conference and Workshops
Energy based performance tuning for large scale high performance computing systems
Proceedings of the 2012 Symposium on High Performance Computing
Energy-Efficient High Performance Computing: Measurement and Tuning
Energy-Efficient High Performance Computing: Measurement and Tuning
GPUWattch: enabling energy optimizations in GPGPUs
Proceedings of the 40th Annual International Symposium on Computer Architecture
A Simplified and Accurate Model of Power-Performance Efficiency on Emergent GPU Architectures
IPDPS '13 Proceedings of the 2013 IEEE 27th International Symposium on Parallel and Distributed Processing
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GPU-accelerated programs are becoming increasingly common in HPC, personal computers, and even handheld devices, making it important to optimize their energy efficiency. However, accurately profiling the power consumption of GPU code is not straightforward. In fact, we have identified multiple anomalies when using the on-board power sensor of K20 GPUs. For example, we have found that doubling a kernel's runtime more than doubles its energy usage, that kernels consume energy after they have stopped executing, and that running two kernels in close temporal proximity inflates the energy consumption of the later kernel. Moreover, we have observed that the power sampling frequency varies greatly and that the GPU sensor only performs power readings once in a while. We present a methodology to accurately compute the instant power and the energy consumption despite these issues.