Implementation of GPU parallel equilibrium reconstruction for plasma control in EAST

Huang, Yao; Xiao, Bingjia; Luo, Z.P.; Yuan, Q.P.; Pei, X.; Yue, Xie

doi:10.1016/j.fusengdes.2016.02.048

Cited by 28 publications

(20 citation statements)

References 15 publications

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“…For this MIMO, the accurate recontruction of the flux expansion or the secondary X point requires finer grid which can not been done by RTEFIT [11], we used PEFIT [12] which is faster and more accurate and meets the demands for the real time reconstruction. Details of PEFIT can be found in [12,13] and real time implementation with IOSFLUX in EAST PCS can be found in [14]. Detailed implementation of this MIMO algorithm can be found in [15].…”

Section: Divertor Heat Load Controlmentioning

confidence: 99%

Integrated plasma control for long pulse advanced plasma discharges on EAST

Xiao

Luo

Yuan

et al. 2018

Fusion Engineering and Design

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Section: Divertor Heat Load Controlmentioning

confidence: 99%

Integrated plasma control for long pulse advanced plasma discharges on EAST

Xiao

Luo

Yuan

et al. 2018

Fusion Engineering and Design

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“…During the elimination, every accumulation step has to use the results from the prior step as shown in Eq. (10).…”

Section: Tri-diagonal Solvermentioning

confidence: 99%

“…When the rectangle grid is settled, the coefficients, such as k i−1 , m i , and b in Eq. (10), can be calculated before hand, only coefficients d i and results x i need to be solved. As shown in Eqs.…”

Section: Tri-diagonal Solvermentioning

confidence: 99%

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Fast parallel Grad–Shafranov solver for real-time equilibrium reconstruction in EAST tokamak using graphic processing unit

2017

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To achieve real-time control of tokamak plasmas, the equilibrium reconstruction has to be completed sufficiently quickly. For the case of an EAST tokamak experiment, real-time equilibrium reconstruction is generally required to provide results within 1ms. A graphic processing unit (GPU) parallel Grad-Shafranov (G-S) solver is developed in P-EFIT code, which is built with the CUDA™ architecture to take advantage of massively parallel GPU cores and significantly accelerate the computation. Optimization and implementation of numerical algorithms for a block tri-diagonal linear system are presented. The solver can complete a calculation within 16 µs with 65×65 grid size and 27 µs with 129×129 grid size, and this solver supports that P-EFIT can fulfill the time feasibility for real-time plasma control with both grid sizes.

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“…There has been an attempt to satisfy such a requirement of acquiring a more accurate, i.e., closer to the off-line EFIT results compared to the rt-EFIT results, magnetic equilibrium in real-time using graphics processing units (GPUs) [19] by parallelizing equilibrium reconstruction algorithms. The GPU based EFIT (P-EFIT) [19] enabled one to calculate a well-converged equilibrium in much less time; however, the benchmark test showed similar results to the rt-EFIT rather than the off-line results [20].…”

Section: Introductionmentioning

confidence: 99%

Deep neural network Grad–Shafranov solver constrained with measured magnetic signals

et al. 2019

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A neural network solving Grad-Shafranov equation constrained with measured magnetic signals to reconstruct magnetic equilibria in real time is developed. Database created to optimize the neural network's free parameters contain off-line EFIT results as the output of the network from 1, 118 KSTAR experimental discharges of two different campaigns. Input data to the network constitute magnetic signals measured by a Rogowski coil (plasma current), magnetic pick-up coils (normal and tangential components of magnetic fields) and flux loops (poloidal magnetic fluxes). The developed neural networks fully reconstruct not only the poloidal flux function ψ (R, Z) but also the toroidal current density function j φ (R, Z) with the off-line EFIT quality. To preserve robustness of the networks against a few missing input data, an imputation scheme is utilized to eliminate the required additional training sets with large number of possible combinations of the missing inputs.

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Implementation of GPU parallel equilibrium reconstruction for plasma control in EAST

Cited by 28 publications

References 15 publications

Integrated plasma control for long pulse advanced plasma discharges on EAST

Integrated plasma control for long pulse advanced plasma discharges on EAST

Fast parallel Grad–Shafranov solver for real-time equilibrium reconstruction in EAST tokamak using graphic processing unit

Deep neural network Grad–Shafranov solver constrained with measured magnetic signals

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