A Real-Time Disruption Prediction Tool for VDE on EAST

Bao, Nana; Huang, Yao; Xiao, Bingjia; Qin, Yuan; Zhuang, Hui; Luo, Z.P.; Wang, Y. H.; Zhang, R. R.

doi:10.1109/tps.2020.2972579

Cited by 16 publications

(14 citation statements)

References 22 publications

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“…Such a customization is needed since the performance of any existing VS system strongly depends on the so called plasma growth rate γ. However, the estimation of the unstable eigenvalue is based on the real-time reconstruction of the plasma equilibrium [80], which is a computationally demanding task, if compared with the time scale the VS system should react in. In order to guarantee the required level of performance, without heavily relying on the knowledge of a plant model, a possible alternative the approach proposed in [81], represents a possible option to implement an effective VS system.…”

Section: Implementation Detailsmentioning

confidence: 99%

“…A possible example is the one related to adaptive mechanism of the proposed VS algorithm. Such mechanism requires to run plasma equilibrium codes and the corresponding linearization procedure in real-time during the tokamak discharge [80], in order to periodically update the plasma model needed to adapt the Kalman filter parameters. Given the typical computational burden needed by such a task, and given its less demanding constraints in terms of real-time deadlines, this should be executed by the APU (possibly with the support of GPUs), without interfering with the hard real-time control task.…”

Section: Implementation Detailsmentioning

confidence: 99%

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WITHDRAWN: RPUGuard: a Building Block for Next-Generation MPSoCs Hypervisors toward Mixed-Criticality Systems

Ottaviano

Cinque

Tommasi

et al. 2023

Preprint

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The spread of cutting-edge virtualization methods for modern embedded architectures like MultiProcessor Systems on Chip (MPSoCs) opens the door to the development of powerful and dependable hypervisors which might help developers to deal with complexity and heterogeneity of modern technologies while maintaining real-time requirements for critical applications. Following the needs of industrial applications, virtualization has been proven to be among the best approaches for the realization of mixed criticality systems embracing the fog computing paradigm while lowering the space, weight, power and cost (SWaP-C) of the deployment. However, the virtualization support for important hardware accelerators presents on MPSoCs, such as Real-Time Processing Units (RPUs), used for real-time and/or safety-critical workloads, is still overlooked. In this paper we propose the concept of the Omnivisor a software layer that virtualize an entire MPSoC improving the resource utilization while simplifying the implementation of a mixed criticality system over these heterogeneous boards. We identify the RPU virtualization as a building block for its realization. Therefore, as a major contribution for this paper, we design and implement a component, named RPUGuard, which is able to guarantee isolated communication channels with a fixed bandwidth between virtual machines, running on regular Application Processing Units (APUs), and the RPU on the same MPSoC. We evaluated RPUGuard on the Zynq Ultrascale+ board, in the context of a challenging case study concerning the magnetic control system of the ITER experimental nuclear fusion reactor. Results demonstrate how our solution can mitigate the weaknesses of current asymmetric communication techniques, while providing isolation guarantees to critical communication channels.

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Section: Implementation Detailsmentioning

confidence: 99%

Section: Implementation Detailsmentioning

confidence: 99%

WITHDRAWN: RPUGuard: a Building Block for Next-Generation MPSoCs Hypervisors toward Mixed-Criticality Systems

Ottaviano

Cinque

Tommasi

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…With regard to real-time signal processing, the methods implemented have explored practically all known data analysis techniques for time series in the time domain, in the frequency domain, and in the combined time/frequency domains [18,19]. Machine learning predictors with various technologies have been developed for all the following Tokamaks: TCV [20], ADITYA [21], AUG [19,[22][23][24][25], DIII-D [26][27][28], J-TEXT [29], NSTX [30], EAST [28,31], ALCATOR C-MOD [27,28], JT-60 U [32,33] and JET [19,[34][35][36][37][38][39][40][41][42][43][44]. The advanced predictor of disruptions is the first disruption predictor that on JET obtained success rates >98%, false alarm rates <2% and average warning times of hundreds of ms [45].…”

Section: A Data-driven Physics-based Approach To Prediction For Proxi...mentioning

confidence: 99%

A hybrid physics/data-driven logic to detect, classify, and predict anomalies and disruptions in tokamak plasmas

Rossi,

Gelfusa,

Craciunescu

et al. 2024

Nucl. Fusion

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Disruptions are abrupt collapses of the configuration that have afflicted all tokamaks ever operated. Reliable observers are a prerequisite to the definition and the deployment of any realistic strategy of countermeasures to avoid or mitigate disruptions. Lacking first principle models of the dynamics leading to disruptions, in the past decades empirical predictors have been extensively studied and some were even installed in JET real-time network. Having been conceived as engineering tools, they were often very abstract. In this work, physics and data-driven methodologies are combined to identify the main macroscopic precursors of disruptions: magnetic instabilities, abnormal kinetic profiles and radiation patterns. Machine learning predictors utilising these observers can not only detect and classify these anomalies but also determine their probability of occurrence and estimate the time remaining before their onset. These tools have been applied to a database of about two thousand JET discharges with various isotopic compositions including DT, in conditions simulating in all respects real time deployment. Their performance would meet ITER requirements, and they are expected to be easily transferrable to larger devices, because they rely only on normalised quantities, form factors, and physical/empirical scaling laws.

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“…A real-time vertical growth rate calculation system aiming at improving vertical instability control is implemented on EAST. Adopting the TokSys vertical growth rate algorithms, P-EFIT is extended to include modules which are also based on GPU parallel computation to accelerate the calculation and provides real-time vertical growth rate per 2 ms during the discharge [15]. As shown in figure 4, the real-time vertical growth rate agrees well with off-line calculation by Tok-Sys and EFIT, the maximum relative deviation is less than 11.5%, and the average relative deviation is about 1.78%.…”

Section: Real-time Vertical Growth Rate Calculation For Vde Controlmentioning

confidence: 99%

GPU-optimized fast plasma equilibrium reconstruction in fine grids for real-time control and data analysis

et al. 2020

Self Cite

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P-EFIT, a GPU parallel equilibrium reconstruction code, is based on the EFIT framework, but built with the CUDA™ (Compute Unified Device Architecture) to take advantage of massively parallel Graphical Processing Unit (GPU) cores to significantly accelerate the computation. With the parallelized Grad-Shafranov solver and middle-scale matrix calculation modules, P-EFIT can accurately reproduce the EFIT reconstruction algorithms at a fraction of the EFIT computational time. Integrated into EAST plasma control system, P-EFIT not only provides control signal results but also enhances EAST plasma control capacity with unique designed function modules. Using the synthetic magnetic diagnostic signals from ITER plasma equilibria obtained by the CREATE-L and CREATE-NL codes in standalone and streaming mode, P-EFIT has good enough accuracy and time latency performance in most of the considered cases. P-EFIT achieves full kinetic equilibrium reconstruction algorithms and repeats the EFIT results with the DIII-D internal plasma current and kinetic profile measurements in one-percent cost time of EFIT. All these works suggest that P-EFIT can provide quality magnetic equilibrium reconstruction in real-time, offer full kinetic equilibrium reconstruction with high spatial resolution and high speed, support more detailed, better plasma control and data analysis for tokamak devices.

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A Real-Time Disruption Prediction Tool for VDE on EAST

Cited by 16 publications

References 22 publications

WITHDRAWN: RPUGuard: a Building Block for Next-Generation MPSoCs Hypervisors toward Mixed-Criticality Systems

WITHDRAWN: RPUGuard: a Building Block for Next-Generation MPSoCs Hypervisors toward Mixed-Criticality Systems

A hybrid physics/data-driven logic to detect, classify, and predict anomalies and disruptions in tokamak plasmas

GPU-optimized fast plasma equilibrium reconstruction in fine grids for real-time control and data analysis

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