Towards Real-Time Detection and Tracking of Spatio-Temporal Features: Blob-Filaments in Fusion Plasma

A novel algorithm and implementation of real-time identification and tracking of blob-filaments in fusion reactor data is presented. Similar spatio-temporal features are important in many other applications, for example, ignition kernels in combustion and tumor cells in a medical image. This work presents an approach for extracting these features by dividing the overall task into three steps: local identification of feature cells, grouping feature cells into extended feature, and tracking movement of feature through overlapping in space. Through our extensive work in parallelization, we demonstrate that this approach can effectively make use of a large number of compute nodes to detect and track blob-filaments in real time in fusion plasma. On a set of 30GB fusion simulation data, we observed linear speedup on 1024 processes and completed blob detection in less than three milliseconds using Edison, a Cray XC30 system at NERSC.Comment: 14 pages, 40 figure

Algorithms for Large Scale Problems in Eigenvalue and Svd Computations and in Big Data Applications

As ”big data” has increasing influence on our daily life and research activities, it poses significant challenges on various research areas. Some applications often demand a fast solution of large, sparse eigenvalue and singular value problems; In other applications, extracting knowledge from large-scale data requires many techniques such as statistical calculations, data mining, and high performance computing. In this dissertation, we develop efficient and robust iterative methods and software for the computation of eigenvalue and singular values. We also develop practical numerical and data mining techniques to estimate the trace of a function of a large, sparse matrix and to detect in real-time blob-filaments in fusion plasma on extremely large parallel computers. In the first work, we propose a hybrid two stage SVD method for efficiently and accurately computing a few extreme singular triplets, especially the ones corresponding to the smallest singular values. The first stage achieves fast convergence while the second achieves the final accuracy. Furthermore, we develop a high-performance preconditioned SVD software based on the proposed method on top of the state-of-the-art eigensolver PRIMME. The method can be used with or without preconditioning, on parallel computers, and is superior to other state-of-the-art SVD methods in both efficiency and robustness. In the second study, we provide insights and develop practical algorithms to accomplish efficient and accurate computation of interior eigenpairs using refined projection techniques in non-Krylov iterative methods. By analyzing different implementations of the refined projection, we propose a new hybrid method to efficiently find interior eigenpairs without compromising accuracy. Our numerical experiments illustrate the efficiency and robustness of the proposed method. In the third work, we present a novel method to estimate the trace of matrix inverse that exploits the pattern correlation between the diagonal of the inverse of the matrix and that of some approximate inverse. We leverage various sampling and fitting techniques to fit the diagonal of the approximation to that of the inverse. Our method may serve as a standalone kernel for providing a fast trace estimate or as a variance reduction method for Monte Carlo in some cases. An extensive set of experiments demonstrate the potential of our method. In the fourth study, we provide first results on applying outlier detection techniques to effectively tackle the fusion blob detection problem on extremely large parallel machines. We present a real-time region outlier detection algorithm to efficiently find and track blobs in fusion experiments and simulations. Our experiments demonstrated we can achieve linear time speedup up to 1024 MPI processes and complete blob detection in two or three milliseconds

Challenges of Video Monitoring for Phenomenological Diagnostics in Present and Future Tokamaks

With the development of heterogeneous camera networks working at different wavelengths and frame rates and covering a large surface of vacuum vessel, the visual observation of a large variety of plasma and thermal phenomena (e.g., hot spots, ELMs, MARFE, arcs, dusts, etc.) becomes possible. In the domain of machine protection, a phenomenological diagnostic is a key-element towards plasma/thermal event dangerousness assessment during real time operation. It is also of primary importance to automate the extraction and the storage of phenomena information for further off-line event retrieval and analysis, thus leading to a better use of massive image data bases for plasma physics studies. To this end, efforts have been devoted to the development of image processing algorithms dedicated to the recognition of specific events. But a need arises now for the integration of techniques developed so far in both hardware and software directions. We present in this paper our latests results in the field of real time phenomena recognition and management through our image understanding software platform. This platform has been validated on Tore Supra during operation and is under evaluation for the foreseen imaging diagnostic of ITER

Analysis of Plasma Filaments with Fast Visible Imaging in the Mega Ampère Spherical Tokamak

The cross-field transport of particles in the scrape-off layer (SOL) of magnetic fusion devices is dominated by the convection of coherent filamentary plasma structures. In this thesis, we present a new technique for the analysis of filaments in fast visible camera data. The new technique operates by inverting the background subtracted emission in the camera images onto a basis set of uniformly emitting field line images, constructed using information from magnetic equilibrium reconstructions. The output of the inversion is a 2D mapping of emission parametrising the average intensity of field lines in the SOL by the coordinates of their intersection with the mid-plane. Filaments manifest in the inverted emission profile as blobs of raised emission. A filament detection technique has been developed to identify these regions of increased emission and fit them with 2D Gaussians. This yields the positions, widths and amplitudes of the filaments. A tracking algorithm is then applied to calculate the filaments velocities and lifetimes. Data from a synthetic camera diagnostic is used to assess the capabilities and limitations of the new technique and quantify its errors. This exercise shows it can detect ~36% of all filaments in the analysis region, corresponding to ~74% of filaments above the targeted amplitude threshold. This sensitivity is achieved with a true positive detection rate of 98.8%. Standard errors in the radial and toroidal positions of the filaments are estimated to be ~2 mm, while errors in the toroidal and radial widths are around ~3 mm and ~7 mm respectively. The shapes of the probability density functions (PDFs) of the filament parameters are also qualitatively recovered and the effect of filament overlap on filament amplitude measurements is investigated. Valuable insight is gained into effects from the non-orthogonality of the field line basis functions and the resulting spatial dependence of the measurement errors. Finally, the technique is applied to MAST data and compared to Langmuir probe measurements. Good agreement is found between the two diagnostics, including exponential waiting times and symmetrical conditionally averaged waveforms. Measurements of the PDFs of filament properties provide valuable inputs for analytic models of SOL transport and show filament lifetimes to be exponentially distributed. The depth of field of the technique enables measurement of the toroidal filament spacing, with results supporting the assertion that filaments are generated uniformly and independently, and are thus described by Poisson statistics underpinning several analytic models

Investigating Dynamics of HIV-1 Protease Activity during the Viral Assembly Process

Human immunodeficiency virus (HIV-1) particles assemble and bud at the host cell plasma membrane and are released as immature, noninfectious particles. Concomitant with release, the viral protease (PR) cleaves Gag and GagProPol polyproteins into single proteins, leading to a major structural rearrangement of the virion. Temporal control of proteolytic cleavage with respect to particle assembly appears crucial for the maturation of infectious particles. The order of Gag processing is tightly regulated by utilization of different proteolytic cleavage sites with specific binding affinities to HIV-1 PR. However, the precise mechanism and kinetics of PR activation, as well as the time course of proteolytic maturation are currently unclear. Since many virus particles are formed in an infected cell and the time course of formation is asynchronous – not only between individual cells but also on the surface of a single cell - bulk biochemical analyses are not suitable for analysis of PR activation. Therefore, the aim of my thesis was to monitor and quantitate the HIV-1 PR activity during virus particle assembly by live-cell microscopy. Live-cell analysis of HIV-1 assembly site formation using fluorescence microscopy was already established in the lab. Previous studies from our and other groups, imaging fluorescently labeled virus assembly by total internal fluorescence microscopy (TIRF), showed that formation of viral assembly sites proceeds over 1-2 h, and Gag assembly for an individual bud is completed within 10-20 min. Here, I designed and explored various approaches for single virus tracking of PR activity in parallel to Gag assembly. For this purpose, I developed and tested different sensors to detect (i) PR enzymatic activity at the nascent assembly site, (ii) Gag polyprotein processing mediated by PR, or (iii) the generation of mature HIV-1 PR by autoprocessing from the GagProPol precursor. To measure PR activity at the assembly site, I designed Förster resonance energy transfer (FRET) reporter molecules which were targeted to nascent assemblies. For this, a FRET pair of autofluorescent proteins was linked via a Gag-derived PR cleavage site and fused to the viral protein r (Vpr) to mediate incorporation into particles. We could show the incorporation, and proteolytic processing of the FRET-based sensor was observed. While sensor co-expression with wild-type HIV-1 PR caused a decrease of the FRET values by two-fold upon proteolytic processing, during time-lapse measurements of the assembly process we could not detect a change in FRET signal over time. In order to detect Gag cleavage as readout for HIV-1 PR activity, I attempted different approaches. Initially, I applied a previously established system for distinguishing immature and mature particles by STED nanoscopy to the analysis of particles formed at the cell surface in live-cell experiments. I then tested two approaches for live-cell measurements of Gag processing. A first attempt to utilize a split fluorescent protein-based method was not successful, since fluorescence was found to be independent of the Gag processing state. In an alternative approach, I explored the use of changes in eCFP fluorescence lifetime depending on fluorophore concentration via homo FRET. Proteolytic processing should release the fluorophore for free diffusion within the virus particle and thereby cause an increase in fluorescence lifetime. Indeed, Gag.eCFP cleavage by HIV-1 PR resulted in changes in fluorescence lifetime measured in purified VLPs and at the plasma membrane of HeLa Kyoto cells. Time-lapse experiments visualized differences in fluorescent lifetime during viral assembly. So far, only few events that may correspond to proteolytic processing were detected. Further adaptation of the system to live cell measurements is under way. Finally, I studied the formation of active HIV-1 PR during assembly with a sensor to fluoresce upon binding to the PR active site, were provided by our collaboration partners who coupled the fluorogenic dye silicone-rhodamine (SiR) to the PR inhibitor Ritonavir (RTV). Specific signal increase upon binding to active PR was shown in vitro and on assembly sites at the plasma membrane of HeLa Kyoto cells. Using this compound, I successful established conditions for time-resolved detection of mature PR at nascent assembly sites. Different SiR recruitment patterns with respect to progression of Gag assembly were observed. Further improvement of signal-to-noise ratio would be beneficial and is currently under way