A Study of Memory Consumption and Execution Performance of the cuFFT Library

Jodra, Jose Luis; Gurrutxaga, Ibai; Muguerza, Javier

doi:10.1109/3pgcic.2015.66

Cited by 8 publications

(4 citation statements)

References 12 publications

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“…Recently, the CUDA(Compute Unified Device Architecture) parallel computing technique has been developing at a remarkable speed. With the cuFFT library, a discrete fast Fourier transform can be performed at a much faster speed than CPU parallelization [34], and we actively utilize this library to perform the existing technique. Microstructure change modeling for a ternary system, which has not yet been performed, was performed here in 3D.…”

Section: Introductionmentioning

confidence: 99%

Effect of Al Concentration on the Microstructural Evolution of Fe-Cr-Al Systems: A Phase-Field Approach

Lee

Park

Chang

2020

Metals

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In this study, the microstructural evolution of an Fe-Cr-Al system was simulated in two-dimensional (2D) and three-dimensional (3D) systems using the phase-field method. We investigated the effect of Al concentration on the microstructural evolution of the systems, with a focus on the nucleation and growth of the Cr-rich α′ phase. In addition, we quantitatively analyzed the mechanism of the effect of Al concentration on the microstructural characteristics of the 2D and 3D systems, such as the number of precipitates, average precipitate area (volume), and α′ phase fraction. In particular, we analyzed the effect of Al concentration and the dimensions of the system cell on the formation of the interconnected structure at high Cr concentrations, such as 35 Crat% and 40 Crat%. To enhance the performance of the simulations, we applied a semi-implicit Fourier spectral method for the ternary system and a parallel graphics processing unit computing technique. The results revealed that the initiation of phase separation in the 2D and 3D simulations was enhanced with an increase in the average Al concentration in the system. In addition, with an increase in the average Al concentration in both systems, the α′ phase fraction increased, while the change in the phase fraction decreased.

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Section: Introductionmentioning

confidence: 99%

Effect of Al Concentration on the Microstructural Evolution of Fe-Cr-Al Systems: A Phase-Field Approach

Lee

Park

Chang

2020

Metals

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“…The power consumed by the GPU in the domain of radio astronomy was investigated by Romein [45]. The performance of the cuFFT library was investigated by Jondra et al [46] along with its power consumption. However, increases in energy efficiency due to frequency scaling were not investigated.…”

Section: Related Workmentioning

confidence: 99%

Efficiency Near the Edge: Increasing the Energy Efficiency of FFTs on GPUs for Real-Time Edge Computing

Adámek¹,

Novotný²,

Thiyagalingam³

et al. 2021

IEEE Access

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The Square Kilometre Array (SKA) is an international initiative for developing the world's largest radio telescope with a total collecting area of over a million square meters. The scale of the operation, combined with the remote location of the telescope, requires the use of energy-efficient computational algorithms. This, along with the extreme data rates that will be produced by the SKA and the requirement for a real-time observing capability, necessitates in-situ data processing in an edge style computing solution. More generally, energy efficiency in the modern computing landscape is becoming of paramount concern. Whether it be the power budget that can limit some of the world's largest supercomputers, or the limited power available to the smallest Internet-of-Things devices. In this paper, we study the impact of hardware frequency scaling on the energy consumption and execution time of the Fast Fourier Transform (FFT) on NVIDIA GPUs using the cuFFT library. The FFT is used in many areas of science and it is one of the key algorithms used in radio astronomy data processing pipelines. Through the use of frequency scaling, we show that we can lower the power consumption of the NVIDIA A100 GPU when computing the FFT by up to 47% compared to the boost clock frequency, with less than a 10% increase in the execution time. Furthermore, using one common core clock frequency for all tested FFT lengths, we show on average a 43% reduction in power consumption compared to the boost core clock frequency with an increase in the execution time still below 10%. We demonstrate how these results can be used to lower the power consumption of existing data processing pipelines. These savings, when considered over years of operation, can yield significant financial savings, but can also lead to a significant reduction of greenhouse gas emissions.

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“…The power consumed by the GPU in the domain of radio astronomy was investigated by Romein [32]. The performance of the cuFFT library was investigated by Jondra et al [19] along with its power consumption. However, increases in energy efficiency due to frequency scaling were not investigated.…”

Section: Related Workmentioning

confidence: 99%

Efficiency Near the Edge: Increasing the Energy Efficiency of FFTs on GPUs for Real-time Edge Computing

Adámek,

Novotný,

Thiyagalingam

et al. 2020

Preprint

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The Square Kilometre Array (SKA) is an international initiative for developing the world's largest radio telescope with a total collecting area of over a million square meters. The scale of the operation, combined with the remote location of the telescope, requires the use of energyefficient computational algorithms. This, along with the extreme data rates that will be produced by the SKA and the requirement for a real-time observing capability, necessitates in-situ data processing in an edge style computing solution. More generally, energy efficiency in the modern computing landscape is becoming of paramount concern. Whether it be the power budget that can limit some of the world's largest supercomputers, or the limited power available to the smallest Internet-of-Things devices. In this paper, we study the impact of hardware frequency scaling on the energy consumption and execution time of the Fast Fourier Transform (FFT) on NVIDIA GPUs using the cuFFT library. The FFT is used in many areas of science and it is one of the key algorithms used in radio astronomy data processing pipelines. Through the use of frequency scaling, we show that we can lower the power consumption of the NVIDIA V100 GPU when computing the FFT by up to 60% compared to the boost clock frequency, with less than a 10% increase in the execution time. Furthermore, using one common core clock frequency for all tested FFT lengths, we show on average a 50% reduction in power consumption compared to the boost core clock frequency with an increase in the execution time still below 10%. We demonstrate how these results can be used to lower the power consumption of existing data processing pipelines. These savings, when considered over years of operation, can yield significant financial savings, but can also lead to a significant reduction of greenhouse gas emissions.

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A Study of Memory Consumption and Execution Performance of the cuFFT Library

Cited by 8 publications

References 12 publications

Effect of Al Concentration on the Microstructural Evolution of Fe-Cr-Al Systems: A Phase-Field Approach

Effect of Al Concentration on the Microstructural Evolution of Fe-Cr-Al Systems: A Phase-Field Approach

Efficiency Near the Edge: Increasing the Energy Efficiency of FFTs on GPUs for Real-Time Edge Computing

Efficiency Near the Edge: Increasing the Energy Efficiency of FFTs on GPUs for Real-time Edge Computing

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