Regarding the Mains of Others.

The platformed logics of social media favor unique and spectacular content and thus encourage the production and display of unique and spectacular bodies. In the realm of social media, attractive and unattainable bodies have emerged as the norm rather than the exception. This article, however, sets out to investigate how a specific type of spectacular body comes into being by turning to the phenomenon of mukbangs. We explore how excessive food consumption, audiovisual aesthetics, media technologies, and platform logics all become constituents of the spectacular body’s performance. Our analysis will focus on two tendencies: First, the platformed body is distributed and comes into being through its entanglement with nonhuman agents, such as the microphone enhancing eating sounds, the camera and image composition displaying the food’s excessive quantity, and the food’s entanglement with the body through a spectacle of excess. Second, mukbang videos cater to a spectating body ready to be affected by the exceptional body capable of extreme eating and how this bodily performance transcends the medium, and the videos produce disgust or cravings.

Over and Over, and Over Again: Tension, Repetition, and Catharsis in the Films of Wes Anderson

This article argues that Wes Anderson’s films repeat formal and thematic strategies in such a way that resists traditional auteurist analysis. By looking at Anderson’s recognizable style of image composition, his expansive paratext, and recurring thematic motifs, we can see a productive system of repetition operative both within and across his films. The value Anderson places on repetition opposes Peter Wollen’s structural auteurist framework, which values variation over repetition. Such opposition allows Anderson’s films to be taken up as a critique of this valuation, demonstrated through an analysis of the productive role of repetition in his work.

In situ visualization of large-scale turbulence simulations in Nek5000 with ParaView Catalyst

In situ visualization on high-performance computing systems allows us to analyze simulation results that would otherwise be impossible, given the size of the simulation data sets and offline post-processing execution time. We develop an in situ adaptor for Paraview Catalyst and Nek5000, a massively parallel Fortran and C code for computational fluid dynamics. We perform a strong scalability test up to 2048 cores on KTH’s Beskow Cray XC40 supercomputer and assess in situ visualization’s impact on the Nek5000 performance. In our study case, a high-fidelity simulation of turbulent flow, we observe that in situ operations significantly limit the strong scalability of the code, reducing the relative parallel efficiency to only $$\approx 21\%$$ ≈ 21 % on 2048 cores (the relative efficiency of Nek5000 without in situ operations is $$\approx 99\%$$ ≈ 99 % ). Through profiling with Arm MAP, we identified a bottleneck in the image composition step (that uses the Radix-kr algorithm) where a majority of the time is spent on MPI communication. We also identified an imbalance of in situ processing time between rank 0 and all other ranks. In our case, better scaling and load-balancing in the parallel image composition would considerably improve the performance of Nek5000 with in situ capabilities. In general, the result of this study highlights the technical challenges posed by the integration of high-performance simulation codes and data-analysis libraries and their practical use in complex cases, even when efficient algorithms already exist for a certain application scenario.

Modified iterative method with red-black ordering for image composition using poisson equation

Image composition involves the process of embedding a selected region of the source image to the target image to produce a new desirable image seamlessly. This paper presents an image composition procedure based on numerical differentiation using the laplacian operator to obtain the solution of the poisson equation. The proposed method employs the red-black strategy to speed up the computation by using two acceleration parameters. The method is known as modified two-parameter over-relaxation (MTOR) and is an extension of the existing relaxation methods. The MTOR was extensively studied in solving various linear equations, but its usefulness in image processing was never explored. Several examples were tested to examine the effectiveness of the proposed method in solving the poisson equation for image composition. The results showed that the proposed MTOR performed faster than the existing methods.