Standardizing Power Monitoring and Control at Exascale

Grant, Ryan E.; Levenhagen, Michael J.; Olivier, Stephen Lecler; DeBonis, David; Pedretti, Kevin; Laros, James H.

doi:10.1109/mc.2016.308

Cited by 35 publications

(12 citation statements)

References 10 publications

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“…At the processor level, the Marvell ThunderX2 Arm processors used in the system provide extensive on-die voltage, power, frequency, and temperature measurements on a per-core basis. These measurements can be accessed in-band by users by instrumenting their code using the PowerAPI [8] or by using vendor supplied tools. At the node and chassis levels, the HPE Apollo 70 server architecture provides out-of-band interfaces for measuring per-node power usage and a range of environmental sensors.…”

Section: Measuring Power On Astramentioning

confidence: 99%

Understanding Power and Energy Utilization in Large Scale Production Physics Simulation Codes

Ryujin¹,

Vargas²,

Karlin³

et al. 2022

Preprint

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Power is an often-cited reason for moving to advanced architectures on the path to Exascale computing. This is due to the practical concern of delivering enough power to successfully site and operate these machines, as well as concerns over energy usage while running large simulations. Since accurate power measurements can be difficult to obtain, processor thermal design power (TDP) is a possible surrogate due to its simplicity and availability. However, TDP is not indicative of typical power usage while running simulations. Using commodity and advance technology systems at Lawrence Livermore National Laboratory (LLNL) and Sandia National Laboratory, we performed a series of experiments to measure power and energy usage in running simulation codes. These experiments indicate that large scale LLNL simulation codes are significantly more efficient than a simple processor TDP model might suggest.

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Section: Measuring Power On Astramentioning

confidence: 99%

Understanding Power and Energy Utilization in Large Scale Production Physics Simulation Codes

Ryujin¹,

Vargas²,

Karlin³

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…The developers can therefore make a tradeoff on configurability by the user, for ease of use and can take advantage of special hardware features. As an example, at present, there is no standard interface to measure energy use or input and output utilization (although there are efforts towards this such as Power API [20], the Global Extensible Open Power Manager [14], Energy Aware Runtime systems [11] and PowerAPI [10]) but Craypat can provide this information to the user while the open source tools that can do this, TAU and Extrae, need to be configured to do so.…”

Section: Profiling Tools Fft Library and Test Platforms 31 The Profiling Toolsmentioning

confidence: 99%

A Comparison of Parallel Profiling Tools for Programs utilizing the FFT

Leu

Aseeri

Muite³

2021

The International Conference on High Performance Computing in Asia-Pacific Region Companion

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Performance monitoring is an important component of code optimization. Performance monitoring is also important for the beginning user, but can be difficult to configure appropriately. The overhead of the performance monitoring tools Craypat, FPMP, mpiP, Scalasca and TAU, are measured using default configurations likely to be choosen by a novice user and shown to be small when profiling Fast Fourier Transform based solvers for the Klein Gordon equation based on 2decomp&FFT and on FFTE. Performance measurements help explain that despite FFTE having a more efficient parallel algorithm, it is not always faster than 2decom&FFT because the complied single core FFT is not as fast as that in FFTW which is used in 2decomp&FFT. CCS CONCEPTS• Computing methodologies → Massively parallel algorithms; • Networks → Network measurement.

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“…We believe that PoLiMEr-with its ability to set power caps during application runtime-will further research in this area beyond single-node applications. Two notable projects take a global perspective on power monitoring and control: Power API [6] and GEOPM [4]. Both aim to standardize system-wide power monitoring and control protocols.…”

Section: Related Workmentioning

confidence: 99%

PoLiMEr

Marincic

Vishwanath

Hoffmann

2017

Proceedings of the 5th International Workshop on Energy Efficient Supercomputing

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Power and energy consumption are now key design concerns in HPC. To develop software that meets power and energy constraints, scientific application developers must have a reliable way to measure these values and relate them to applicationspecific events. Scientists face two challenges when measuring and controlling power: (1) diversity-power and energy measurement interfaces differ between vendors-and (2) distribution-power measurements of MPI simulations should be unaffected by the mapping of MPI processes to physical hardware nodes. While some prior work defines standardized software interfaces for power management, these efforts do not support distributed environments. The result is that the current state-of-the-art requires scientists interested in power optimization to write tedious, error-prone applicationand system-specific code. To make power measurement and management easier for scientists, we propose PoLiMEr, a user-space library that supports fine-grained application-level power monitoring and capping. We evaluate PoLiMEr by deploying it on Argonne National Laboratory's Theta system and using it to measure and cap power, scaling the performance and power of several applications on up to 1024 nodes. We find that PoLiMEr requires only a few additional lines of code, but easily allows users to detect energy anomalies, apply power caps, and evaluate Theta's unique architectural features.

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Standardizing Power Monitoring and Control at Exascale

Cited by 35 publications

References 10 publications

Understanding Power and Energy Utilization in Large Scale Production Physics Simulation Codes

Understanding Power and Energy Utilization in Large Scale Production Physics Simulation Codes

A Comparison of Parallel Profiling Tools for Programs utilizing the FFT

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