The International Conference for High Performance Computing, Networking, Storage and Analysis
Real-Time Outlier Detection Algorithm for Finding Blob-Filaments in Plasma.
Student: Lingfei Wu (College of William & Mary)
Supervisor: Andreas stathopoulos (College of William & Mary)
Abstract: Magnetic fusion could be an inexhaustible, clean, and safe solution to the global energy needs. The success of magnetically confined fusion reactors demand steady-state plasma confinement which is challenged by the edge turbulence such as the blob-filaments. Real time analysis can be used to monitor the progress of fusion experiments and prevent catastrophic events. We present a real-time outlier detection algorithm to efficiently find blobs in the fusion experiments and numerical simulations. We have implemented this algorithm with hybrid MPI/OpenMP and demonstrated the accuracy and efficiency with a set of data from the XGC1 fusion simulations. Our tests show that we can complete blob detection in a few milliseconds using a cluster at NERSC and achieve linear time scalability. We plan to apply the detection algorithm to experimental measurement data from operating fusion devices. We also plan to develop a blob tracking algorithm based on the proposed method.