Analyzing and Modeling the Performance of the HemeLB Lattice-Boltzmann Simulation Environment

We investigate the performance of the HemeLB lattice-Boltzmann simulator for cerebrovascular blood flow, aimed at providing timely and clinically relevant assistance to neurosurgeons. HemeLB is optimised for sparse geometries, supports interactive use, and scales well to 32,768 cores for problems with ~81 million lattice sites. We obtain a maximum performance of 29.5 billion site updates per second, with only an 11% slowdown for highly sparse problems (5% fluid fraction). We present steering and visualisation performance measurements and provide a model which allows users to predict the performance, thereby determining how to run simulations with maximum accuracy within time constraints.Comment: Accepted by the Journal of Computational Science. 33 pages, 16 figures, 7 table

The Living Application: a Self-Organising System for Complex Grid Tasks

We present the living application, a method to autonomously manage applications on the grid. During its execution on the grid, the living application makes choices on the resources to use in order to complete its tasks. These choices can be based on the internal state, or on autonomously acquired knowledge from external sensors. By giving limited user capabilities to a living application, the living application is able to port itself from one resource topology to another. The application performs these actions at run-time without depending on users or external workflow tools. We demonstrate this new concept in a special case of a living application: the living simulation. Today, many simulations require a wide range of numerical solvers and run most efficiently if specialized nodes are matched to the solvers. The idea of the living simulation is that it decides itself which grid machines to use based on the numerical solver currently in use. In this paper we apply the living simulation to modelling the collision between two galaxies in a test setup with two specialized computers. This simulation switces at run-time between a GPU-enabled computer in the Netherlands and a GRAPE-enabled machine that resides in the United States, using an oct-tree N-body code whenever it runs in the Netherlands and a direct N-body solver in the United States.Comment: 26 pages, 3 figures, accepted by IJHPC

Multiscale modelling and simulation, 13th international workshop

Multiscale Modelling and Simulation (MMS) is a cornerstone in the today's research in computational science. Simulations containing multiple models, with each model operating at a different temporal or spatial scale, are a challenging setting that frequently require innovative approaches in areas such as scale bridging, code deployment, error quantification, and scientific analysis. The aim of the MMS workshop is to encourage and consolidate the progress in this multidisciplinary research field, both in the areas of the scientific applications and the underlying infrastructures that enable these applications. Here we briefly introduce the scope of the workshop and highlight some of the key aspects of this year's submissions

Probing dynamics of an electron-spin ensemble via a superconducting resonator

We study spin relaxation and diffusion in an electron-spin ensemble of nitrogen impurities in diamond at low temperature (0.25-1.2 K) and polarizing magnetic field (80-300 mT). Measurements exploit mode- and temperature-dependent coupling of hyperfine-split sub-ensembles to the resonator. Temperature-independent spin linewidth and relaxation time suggest that spin diffusion limits spin relaxation. Depolarization of one sub-ensemble by resonant pumping of another indicates fast cross-relaxation compared to spin diffusion, with implications on use of sub-ensembles as independent quantum memories.Comment: 5 pages, 5 figures, and Supplementary Information (2 figures

Two-dimensional superconductivity at the (111)LaAlO3_3/SrTiO3_3 interface

We report on the discovery and transport study of the superconducting ground state present at the (111)LaAlO$_3$/SrTiO$_3$ interface. The superconducting transition is consistent with a Berezinskii-Kosterlitz-Thouless transition and its 2D nature is further corroborated by the anisotropy of the critical magnetic field, as calculated by Tinkham. The estimated superconducting layer thickness and coherence length are 10 nm and 60 nm, respectively. The results of this work provide a new platform to clarify the microscopic details of superconductivity at LaAlO$_3$/SrTiO$_3$ interfaces, in particular in what concerns the link with orbital symmetry.Comment: 4 pages, 4 figure

Using Galvanic Vestibular Stimulation to Induce Post-Roll Illusion in a Fixed-Base Flight Simulator

INTRODUCTION: The illusions of head motion induced by galvanic vestibular stimulation (GVS) can be used to compromise flight performance of pilots in fixed-base simulators. However, the stimuli used in the majority of studies fail to mimic disorientation in realistic flight because they are independent from the simulated aircraft motion. This study investigated the potential of bilateral-bipolar GVS coupled to aircraft roll in a fixed-base simulator to mimic vestibular spatial disorientation illusions, specifically the “post-roll illusion” observed during flight.METHODS: There were 14 nonpilot subjects exposed to roll stimuli in a flight simulator operating in a fixed-base mode. GVS was delivered via carbon rubber electrodes on the mastoid processes. The electrical stimulus was driven by the high-pass filtered aircraft roll rate to mimic the semicircular canals’ physiological response. The post-roll test scenarios excluded outside visual cues or instruments and required subjects to actively maintain a constant bank angle after an abrupt stop following a passive prolonged roll maneuver. The anticipated outcome was an overshot in roll elicited by the GVS signal. RESULTS: The responses across subjects showed large variability, with less than a third aligning with the post-roll illusion. Subjective ratings suggest that the high-pass filtered GVS stimuli were mild and did not induce a clear sense of roll direction. However, uncontrolled head movements during stimulation might have obscured the intended effects of GVS-evoked illusory head movements. CONCLUSION: The mild and transient GVS stimuli used in this study, together with the uncontrolled head movements, did not convincingly mimic the post-roll illusion.</p

Scene complexity modulates degree of feedback activity during object detection in natural scenes

Selective brain responses to objects arise within a few hundreds of milliseconds of neural processing, suggesting that visual object recognition is mediated by rapid feed-forward activations. Yet disruption of neural responses in early visual cortex beyond feed-forward processing stages affects object recognition performance. Here, we unite these discrepant findings by reporting that object recognition involves enhanced feedback activity (recurrent processing within early visual cortex) when target objects are embedded in natural scenes that are characterized by high complexity. Human participants performed an animal target detection task on natural scenes with low, medium or high complexity as determined by a computational model of low-level contrast statistics. Three converging lines of evidence indicate that feedback was selectively enhanced for high complexity scenes. First, functional magnetic resonance imaging (fMRI) activity in early visual cortex (V1) was enhanced for target objects in scenes with high, but not low or medium complexity. Second, event-related potentials (ERPs) evoked by target objects were selectively enhanced at feedback stages of visual processing (from ~220 ms onwards) for high complexity scenes only. Third, behavioral performance for high complexity scenes deteriorated when participants were pressed for time and thus less able to incorporate the feedback activity. Modeling of the reaction time distributions using drift diffusion revealed that object information accumulated more slowly for high complexity scenes, with evidence accumulation being coupled to trial-to-trial variation in the EEG feedback response. Together, these results suggest that while feed-forward activity may suffice to recognize isolated objects, the brain employs recurrent processing more adaptively in naturalistic settings, using minimal feedback for simple scenes and increasing feedback for complex scenes