SIMD-Based Large-Scale Transient Stability Simulation on the Graphics Processing Unit

Jalili-Marandi, Vahid; Dinavahi, Venkata

doi:10.1109/tpwrs.2010.2042084

Cited by 107 publications

(61 citation statements)

References 29 publications

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“…Time domain EMT simulation is carried out using the following commonly known Nodal equation [1], [17], [12], [18]:…”

Section: Overview Of Emt Simulationmentioning

confidence: 99%

“…Using several different test cases, the authors' earlier work [9], showed that GPU-based EMT simulation produces exactly the same result as the commercial tools. Other researchers also used this approach for creating large test cases [5], [12], [13], [30].…”

Section: Test Cases Used For Gpu Based Emt Simulationmentioning

confidence: 99%

“…These approaches have improved the performance of EMT simulations. The approach presented in this paper, uses Graphics Processing Units (GPUs) [7], [8], as a high performance and potentially cost effective alternative [9], [10], [11], [12] for EMT simulation of large power systems. The authors of this paper first reported GPU-based EMT simulation in 2011 [9] and further developments of the work were reported in [10], [11].…”

Section: Introductionmentioning

confidence: 99%

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Graphics-Processing-Unit-Based Acceleration of Electromagnetic Transients Simulation

Debnath

Gole

Fung

2016

IEEE Trans. Power Delivery

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“…Time domain EMT simulation is carried out using the following commonly known Nodal equation [1], [17], [12], [18]:…”

Section: Overview Of Emt Simulationmentioning

confidence: 99%

Section: Test Cases Used For Gpu Based Emt Simulationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Graphics-Processing-Unit-Based Acceleration of Electromagnetic Transients Simulation

Debnath

Gole

Fung

2016

IEEE Trans. Power Delivery

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“…Therefore, the obtained comparison results prove the correctness of computations performed by author's own program. The speed-up of computations (S) done with application of the graphics processing unit (GPU) is defined according to the following relation [32]:…”

Section: Verification Of Numerical Solutionmentioning

confidence: 99%

GPU-based parallel method of temperature field analysis in a floor heater with a controller

Forenc

2016

Open Engineering

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A parallel method enabling acceleration of the numerical analysis of the transient temperature field in an air floor heating system is presented in this paper. An initial-boundary value problem of the heater regulated by an on/off controller is formulated. The analogue model is discretized using the implicit finite difference method. The BiCGStab method is used to compute the obtained system of equations. A computer program implementing simultaneous computations on CPU and GPU (GPGPU technology) was developed. CUDA environment and linear algebra libraries (CUBLAS and CUSPARSE) are used by this program. The time of computations was reduced eight times in comparison with a program executed on the CPU only. Results of computations are presented in the form of time profiles and temperature field distributions. An influence of a model of the heat transfer coefficient on the simulation of the system operation was examined. The physical interpretation of obtained results is also presented. Results of computations were verified by comparing them with solutions obtained with the use of a commercial program -COMSOL Mutiphysics.

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“…On the basis of the results, the speed-up S is determined. It is assigned according to the following equation [12]:…”

Section: Efficiency Of Computations Conducted On a Graphics Processinmentioning

confidence: 99%

Parallel computations of the step response of a floor heater with the use of a graphics processing unit. Part 2: results and their evaluation

Gołębiowski¹,

Forenc²

2013

Bulletin of the Polish Academy of Sciences: Technical Sciences

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Abstract. Using models and algorithms presented in the first part of the article, a spatio-temporal distribution of the step response of a floor heater was determined. The results have been presented in the form of heating curves and temperature profiles of the heater in the selected time moments. The computations results were verified through comparing them with the solution obtained with the use of a commercial program -NISA. Additionally, the distribution of the average time constant of thermal processes occurring in the heater was determined. The analysis of the use of a graphics processing unit in numerical computations based on the conjugate gradient method was done. It was proved that the use of a graphics processing unit is profitable in the case of solving linear systems of equations with dense coefficient matrices. In the case of a sparse matrix, the speed-up depends on the number of its non-zero elements.Key words: air floor heating, step response computation, parallel computations, GPGPU. Computational program parameters, material properties of the model, computing platformThe construction of the analyzed model of the heater was described in the first part of this paper ( Fig. 2 in [1], where L = 0.15 m). In order to conduct the discrete approximation of the model, an appropriate fragment of the floor slab was covered with a finite difference mesh of an identical step along x, y axes which equal ∆x = ∆y = 2.34375 · 10 −3 m. The mesh has 65×97 nodes. However, the number of nodes taken into consideration (and thus the number of unknown quantities of the obtained system of equations) is smaller and equals to 4289. As 2016 nodes, which are placed in the crosssection of the duct of the given temperature T H , should be omitted. The step response was determined with the assumed time step ∆t = 2 s and the N = 27000 number of steps. As a result, the considered time interval equals to 54 000 s (15 hours from letting the hot air into the ducts).Denotations of material properties were explained in the first part of the article (chapter 2 in [1]). The following set of data was assumed:Computations were done with the use of a personal computer equipped with an Intel Core 2 Quad CPU Q9650 3.00 GHz processor, RAM memory of 4 GB and a 64-bit Windows 7 Professional operating system. A Gigabyte Nvidia GeForce GTX480 graphics card equipped with 480 streaming processors, and 1536 MB of GDDR5 memory were installed in the computer. It also contained the CUDA parallel computing environment [2,3] Step responses and their computational verificationThe computations of the step response were done according to the algorithm described in the first part of the article [1]. The obtained curves can be presented in a graph for selected points of the analyzed model of a floor heater. Characteristic points (A-J) were marked in Fig. 1, and the obtained graphs of the step response are presented in Fig. 2. Fig. 1. Analyzed fragment of the heater with the characteristic points and adiabats *

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SIMD-Based Large-Scale Transient Stability Simulation on the Graphics Processing Unit

Cited by 107 publications

References 29 publications

Graphics-Processing-Unit-Based Acceleration of Electromagnetic Transients Simulation

Graphics-Processing-Unit-Based Acceleration of Electromagnetic Transients Simulation

GPU-based parallel method of temperature field analysis in a floor heater with a controller

Parallel computations of the step response of a floor heater with the use of a graphics processing unit. Part 2: results and their evaluation

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