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In this paper we present a workflow management system which permits the kinds of data-driven workflows required by urgent computing, namely where new data is integrated into the workflow as a disaster progresses in order refine the predictions as time goes on. This allows the workflow toadapt to new data at runtime, a capability that most workflow management systems do not possess. The workflow management system was developed for the EU-funded VESTEC project, which aims to fuse HPC with real-time data for supporting urgent decision making. We first describe an example workflow from the VESTEC project, and show why existing workflow technologies do not meet the needs of the project. We then go on to present the design of our Workflow Management System, describe how it is implemented into the VESTEC system, and provide an example of the workflow system in use for a test case.

The MPI intercommunication framework was used for coupling of two lattice-Boltzmann solvers with suspended particles, which model advection and diffusion respectively of these particles in a carrier fluid. Simulation domain was divided into two parts, one with advection and diffusion, and the other with diffusion only (no macroscopic flow). Particles were exchanged between these domains at their common boundary by a direct process to process communication. By analysing weak and strong scaling, it was shown that the linear scaling characteristics of the lattice-Boltzmann solvers were not compromised by their coupling.

The use of High Performance Computing (HPC) to compliment urgent decision making in the event of disasters is an important future potential use of supercomputers. However, the usage modes involved are rather different from how HPC has been used traditionally. As such, there are many obstacles that need to be overcome, not least the unbounded wait times in the batch system queues, to make the use of HPC in disaster response practical. In this paper, we present how the VESTEC project plans to overcome these issues and develop a working prototype of an urgent computing control system. We describe the requirements for such a system and analyse the different technologies available that can be leveraged to successfully build such a system. We finally explore the design of the VESTEC system and discuss ongoing challenges that need to be addressed to realise a production level system., Comment: Preprint of paper in 2019 IEEE/ACM HPC for Urgent Decision Making (UrgentHPC)

Technological advances are creating exciting new opportunities that have the potential to move HPC well beyond traditional computational workloads. In this paper we focus on the potential for HPC to be instrumental in responding to disasters such as wildfires, hurricanes, extreme flooding, earthquakes, tsunamis, winter weather conditions, and accidents. Driven by the VESTEC EU funded H2020 project, our research looks to prove HPC as a tool not only capable of simulating disasters once they have happened, but also one which is able to operate in a responsive mode, supporting disaster response teams making urgent decisions in real-time. Whilst this has the potential to revolutionise disaster response, it requires the ability to drive HPC interactively, both from the user's perspective and also based upon the arrival of data. As such interactivity is a critical component in enabling HPC to be exploited in the role of supporting disaster response teams so that urgent decision makers can make the correct decision first time, every time., Comment: Pre-print in International Conference on High Performance Computing (pp. 528-540). Springer, Cham

In this article, we present PolNet, an open-source software tool for the study of blood flow and cell-level biological activity during vessel morphogenesis. We provide an image acquisition, segmentation, and analysis protocol to quantify endothelial cell polarity in entire in vivo vascular networks. In combination, we use computational fluid dynamics to characterize the hemodynamics of the vascular networks under study. The tool enables, to our knowledge for the first time, a network-level analysis of polarity and flow for individual endothelial cells. To date, PolNet has proven invaluable for the study of endothelial cell polarization and migration during vascular patterning, as demonstrated by two recent publications. Additionally, the tool can be easily extended to correlate blood flow with other experimental observations at the cellular/molecular level. We release the source code of our tool under the Lesser General Public License.

In this paper, we present PolNet, an open source software tool for the study of blood flow and cell-level biological activity during vessel morphogenesis. We provide an image acquisition, segmentation, and analysis protocol to quantify endothelial cell polarity in entire in vivo vascular networks. In combination, we use computational fluid dynamics to characterise the haemodynamics of the vascular networks under study. The tool enables, for the first time, network-level analysis of polarity and flow for individual endothelial cells. To date, PolNet has proven invaluable for the study of endothelial cell polarisation and migration during vascular patterning, as demonstrated by our recent papers [1, 2]. Additionally, the tool can be easily extended to correlate blood flow with other experimental observations at the cellular/molecular level. We release the source code of our tool under the LGPL licence.

In this Letter, we study the collective behaviour of a large number of self-propelled microswimmers immersed in a fluid. Using unprecedently large-scale lattice Boltzmann simulations, we reproduce the transition to bacterial turbulence. We show that, even well below the transition, swimmers move in a correlated fashion that cannot be described by a mean-field approach. We develop a novel kinetic theory that captures these correlations and is non-perturbative in the swimmer density. To provide an experimentally accessible measure of correlations, we calculate the diffusivity of passive tracers and reveal its non-trivial density dependence. The theory is in quantitative agreement with the lattice Boltzmann simulations and captures the asymmetry between pusher and puller swimmers below the transition to turbulence., Accepted for publication in Phys. Rev. Lett

Obtaining a good load balance is a significant challenge in scaling up lattice-Boltzmann simulations of realistic sparse problems to the exascale. Here we analyze the effect of weighted decomposition on the performance of the HemeLB lattice-Boltzmann simulation environment, when applied to sparse domains. Prior to domain decomposition, we assign wall and in/outlet sites with increased weights which reflect their increased computational cost. We combine our weighted decomposition with a second optimization, which is to sort the lattice sites according to a space filling curve. We tested these strategies on a sparse bifurcation and very sparse aneurysm geometry, and find that using weights reduces calculation load imbalance by up to 85%, although the overall communication overhead is higher than some of our runs., 11 pages, 8 figures, 1 table, accepted for the EASC2014 conference

The Discrete Simulation of Fluid Dynamics (DSFD) series of conferences originated with the 1986 Los Alamos conference organised by Gary D. Doolen. Since that time, the DSFD conferences have emerged as the premier forum for researchers in the field, and many exciting new discoveries in lattice models of fluid dynamics have been announced at DSFD conferences. Topics emphasised at these meetings include lattice Boltzmann schemes, dissipative particle dynamics, smoothed-particle hydrodynamics, direct simulation Monte Carlo, molecular dynamics, quantum Monte Carlo methods, multiparticle collision dynamics and hybrid methods. At the 23rd edition of DSFD in Paris 2014, we were given the privilege of organising the 24th running of the meeting series in Edinburgh, from 13th to 17th July 2015 at the Royal Society of Edinburgh, which names Adam Smith, Joseph Black and Benjamin Franklin among its founding fellows. Edinburgh is Scotland’s truly cosmopolitan capital. Apart from its amazing castle and Arthur’s Seat (an ancient volcanic plug), parts of the city centre are UNESCO World Heritage Sites. Numerous famous scientists have been born or worked in Edinburgh, for example Alexander Graham Bell, Max Born, Charles Darwin, Peter Higgs or James Clerk Maxwell. We were delighted to host a total of 164 attendees, 60 of whom were students, from 21 countries. We enjoyed twelve invited talks and 100 contributed talks. There were 29 posters and 16 flash presentations. We had, of course, a great deal of help in preparing the meeting, particularly from The University of Edinburgh, our colleagues on the Scientific Committee, the conference venue the Royal Society of Edinburgh, and this Journal for the publication of this Special Issue. We are also grateful to the following for their financial support, without which arranging the meeting would have been impossible: Porous Media, Processes and Mathematics; SoftComp; the British Heart Foundation; Sphere Fluidics; Electric Ant Lab; The American Physical Society; UK- COMES, the UK Consortium on Mesoscale Engineering Sciences; SUPA, the Scottish 1 Universities Physics Alliance; our colleagues from the Institute for Condensed Matter and Complex Systems at the School of Physics and Astronomy through their EPSRC Programme Grant; Cray, the Supercomputer Company, and NVIDIA. We are very pleased that with this Special Issue the Journal of Computational Science has given us the opportunity to present the latest developments in theory and application of discrete simulation methods for fluid dynamics. Topics discussed at the conference include the theory of lattice Boltzmann, e.g. the mathematical lattice structure [14], mixed quadratures for finite Knudsen number flows [1], optimisation of pseudopotential models [6], phase-field models for multiphase flows [18] and axisymmetric multiphase models [13]. Other presenters focussed on various lattice Boltzmann applications, such as the simulation of harbour seal vibrissae [10], diffusivity and reactivity of nanoporous catalyst media [9], rare cell capture in obstacle arrays [3] and the PowerFLOW solver for multi-component engineering applications [12]. A specific emphasis was put on droplet dynamics through various simulation methods, including droplet dynamics in confinement [4], bounce regime of droplet collisions [19], contact angle hysteresis of microdroplets on structured surfaces [2] and phase-field simulations of partially wetted and textured surfaces [16]. One of the conference topics was multiscale problems in fluid dynamics, for instance the coupling for lattice Boltzmann and conventional Navier-Stokes solvers [11], a hybrid molecular-dynamics/fluctuating-hydrodynamics model [5] and direct-simulation-Monte- Carlo/lattice-Boltzmann mapping for gas flows [15]. Finally, the conference featured a number of multi-physics applications, including inertial dilute particle flow with an Euler- Euler lattice Boltzmann method [17], lattice Boltzmann for light simulation and radiative transport through absorbing and scattering media [8] and jet electro-hydrodynamics [7]. We hope these contributions will be of interest and value to readers from a wide range of subject areas and form a reference for future development of discrete simulation methods of fluid dynamics.

There is currently limited understanding of the role played by haemodynamic forces on the processes governing vascular development. One of many obstacles to be overcome is being able to measure those forces, at the required resolution level, on vessels only a few micrometres thick. In this paper, we present an in silico method for the computation of the haemodynamic forces experienced by murine retinal vasculature (a widely used vascular development animal model) beyond what is measurable experimentally. Our results show that it is possible to reconstruct high-resolution three-dimensional geometrical models directly from samples of retinal vasculature and that the lattice-Boltzmann algorithm can be used to obtain accurate estimates of the haemodynamics in these domains. We generate flow models from samples obtained at postnatal days (P) 5 and 6. Our simulations show important differences between the flow patterns recovered in both cases, including observations of regression occurring in areas where wall shear stress (WSS) gradients exist. We propose two possible mechanisms to account for the observed increase in velocity and WSS between P5 and P6: (i) the measured reduction in typical vessel diameter between both time points and (ii) the reduction in network density triggered by the pruning process. The methodology developed herein is applicable to other biomedical domains where microvasculature can be imaged but experimental flow measurements are unavailable or difficult to obtain.

Perturbations to the homeostatic distribution of mechanical forces exerted by blood on the endothelial layer have been correlated with vascular pathologies including intracranial aneurysms and atherosclerosis. Recent computational work suggests that in order to correctly characterise such forces, the shear-thinning properties of blood must be taken into account. To the best of our knowledge, these findings have never been compared against experimentally observed pathological thresholds. In the current work, we apply the three-band diagram (TBD) analysis due to Gizzi et al. to assess the impact of the choice of blood rheology model on a computational model of the right middle cerebral artery. Our results show that, in the model under study, the differences between the wall shear stress predicted by a Newtonian model and the well known Carreau-Yasuda generalized Newtonian model are only significant if the vascular pathology under study is associated with a pathological threshold in the range 0.94 Pa to 1.56 Pa, where the results of the TBD analysis of the rheology models considered differs. Otherwise, we observe no significant differences., 14 pages, 6 figures, published at Interface Focus

Modeling blood flow in larger vessels using lattice-Boltzmann methods comes with a challenging set of constraints: a complex geometry with walls and inlets and outlets at arbitrary orientations with respect to the lattice, intermediate Reynolds (Re) number, and unsteady flow. Simple bounce-back is one of the most commonly used, simplest, and most computationally efficient boundary conditions, but many others have been proposed. We implement three other methods applicable to complex geometries [Guo, Zheng, and Shi, Phys. Fluids 14, 2007 (2002); Bouzidi, Firdaouss, and Lallemand, Phys. Fluids 13, 3452 (2001); Junk and Yang, Phys. Rev. E 72, 066701 (2005)] in our open-source application hemelb. We use these to simulate Poiseuille and Womersley flows in a cylindrical pipe with an arbitrary orientation at physiologically relevant Re number (1-300) and Womersley (4-12) numbers and steady flow in a curved pipe at relevant Dean number (100-200) and compare the accuracy to analytical solutions. We find that both the Bouzidi-Firdaouss-Lallemand (BFL) and Guo-Zheng-Shi (GZS) methods give second-order convergence in space while simple bounce-back degrades to first order. The BFL method appears to perform better than GZS in unsteady flows and is significantly less computationally expensive. The Junk-Yang method shows poor stability at larger Re number and so cannot be recommended here. The choice of collision operator (lattice Bhatnagar-Gross-Krook vs multiple relaxation time) and velocity set (D3Q15 vs D3Q19 vs D3Q27) does not significantly affect the accuracy in the problems studied.

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., Accepted by the Journal of Computational Science. 33 pages, 16 figures, 7 tables

We simulate by lattice Boltzmann the nonequilibrium steady states of run-and-tumble particles (inspired by a minimal model of bacteria), interacting by far-field hydrodynamics, subject to confinement. Under gravity, hydrodynamic interactions barely perturb the steady state found without them, but for particles in a harmonic trap such a state is quite changed if the run length is larger than the confinement length: a self-assembled pump is formed. Particles likewise confined in a narrow channel show a generic upstream flux in Poiseuille flow: chiral swimming is not required.

We present a second-order accurate method to include arbitrary distributions of force densities in the lattice Boltzmann formulation of hydrodynamics. Our method may be used to represent singular force densities arising either from momentum-conserving internal forces or from external forces which do not conserve momentum. We validate our method with several examples involving point forces and find excellent agreement with analytical results. A minimal model for dilute sedimenting particles is presented using the method which promises a substantial gain in computational efficiency., Comment: 22 pages, 9 figures. Submitted to Phys. Rev. E

Multidimensional potential energy landscapes (PELs) have a Gaussian distribution for the energies of the minima, but at the same time the distribution of the hyperareas for the basins of attraction surrounding the minima follows a power-law. To explore how both these features can simultaneously be true, we introduce an ``egg-box'' model. In these model landscapes, the Gaussian energy distribution is used as a starting point and we examine whether a power-law basin area distribution can arise as a natural consequence through the swallowing up of higher-energy minima by larger low-energy basins when the variance of this Gaussian is increased sufficiently. Although the basin area distribution is substantially broadened by this process,it is insufficient to generate power-laws, highlighting the role played by the inhomogeneous distribution of basins in configuration space for actual PELs., 7 pages, 8 figures