An effective latency-hiding mechanism is presented in the parallelization of agent-based model simulations (ABMS) with millions of agents. The mechanism is designed to accommodate the hierarchical organization as well as heterogeneity of current state-of-the-art parallel computing platforms. We use it to explore the computation vs. communication trade-off continuum available with the deep computational and memory hierarchies of extant platforms and present a novel analytical model of the tradeoff. We describe our implementation and report preliminary performance results on two distinct parallel platforms suitable for ABMS: CUDA threads on multiple, networked graphical processing units (GPUs), and pthreads on multi-core processors. Message Passing Interface (MPI) is used for inter-GPU as well as inter-socket communication on a cluster of multiple GPUs and multi-core processors. Results indicate the benefits of our latency-hiding scheme, delivering as much as over 100-fold improvement in runtime for certain benchmark ABMS application scenarios with several million agents. This speed improvement is obtained on our system that is already two to three orders of magnitude faster on one GPU than an equivalent CPU-based execution in a popular simulator in Java. Thus, the overall execution of our current work is over four orders of magnitude faster when executed on multiple GPUs.

The dynamics of RE (runaway electrons) in fusion plasmas span a wide range of temporal scales, from the fast gyro-motion, ∼10−11 s, to the observational time scales, ∼10−2→1 s. To cope with this scale separation, RE are usually studied within the bounce-average or the guiding center approximations. Although these approximations have yielded valuable insights, a study with predictive capabilities of RE in fusion plasmas calls for the incorporation of full orbit effects in configuration space in the presence of three-dimensional magnetic fields. We present numerical results on this problem using the Kinetic Orbit Runaway electrons Code that follows relativistic electrons in general electric and magnetic fields under the full Lorentz force, collisions, and radiation losses. At relativistic energies, the main energy loss is due to radiation damping, which we incorporate using the Landau-Lifshitz formulation of the Abraham-Lorentz-Dirac force. The main focus is on full orbit effects on synchrotron radiation. It is shown that even in the absence of magnetic field stochasticty, neglecting orbit dynamics can introduce significant errors in the computation of the total radiated power and the synchrotron spectra. The statistics of collisionless (i.e., full orbit induced) pitch angle dispersion, and its key role played on synchrotron radiation, are studied in detail. Numerical results are also presented on the pitch angle dependence of the spatial confinement of RE and on full orbit effects on the competition of electric field acceleration and radiation damping. Finally, full orbit calculations are used to explore the limitations of gyro-averaging in the relativistic regime. To explore the practical impact of the results, DIII-D and ITER-like parameters are used in the simulations.

We present results from a study of light meson spectra and structure obtained within the framework of light-front QCD formulated on a transverse lattice.We discuss how imposing Lorentz covariance conditions on meson dispersion relations allows determination of parameters in the transverse lattice Hamiltonian. The pion distribution amplitude obtained in this framework is rather close to its asymptotic shape.

Calculations of the plasma response to applied non-axisymmetric fields in several DIII-D discharges show that predicted displacements depend strongly on the edge current density. This result is found using both a linear two-fluid-MHD model (M3D-C1) and a nonlinear ideal-MHD model (VMEC). Furthermore, it is observed that the probability of a discharge being edge localized mode (ELM)-suppressed is most closely related to the edge current density, as opposed to the pressure gradient. It is found that discharges with a stronger kink response are closer to the peeling-ballooning stability limit in ELITE simulations and eventually cross into the unstable region, causing ELMs to reappear. Thus for effective ELM suppression, the RMP has to prevent the plasma from generating a large kink response, associated with ELM instability. Experimental observations are in agreement with the finding; discharges which have a strong kink response in the MHD simulations show ELMs or ELM mitigation during the RMP phase of the experiment, while discharges with a small kink response in the MHD simulations are fully ELM suppressed in the experiment by the applied resonant magnetic perturbation. The results are cross-checked against modeled 3D ideal MHD equilibria using the VMEC code. The procedure of constructing optimal 3D equilibria for diverted H-mode discharges using VMEC is presented. Kink displacements in VMEC are found to scale with the edge current density, similar to M3D-C1, but the displacements are smaller. A direct correlation in the flux surface displacements to the bootstrap current is shown.

In complex phenomena such as epidemiological outbreaks, the intensity of inherent feedback effects and the significant role of transients in the dynamics make simulation the only effective method for proactive, reactive or post facto analysis. The spatial scale, runtime speed, and behavioral detail needed in detailed simulations of epidemic outbreaks cannot be supported by sequential or small-scale parallel execution, making it necessary to use large-scale parallel processing. Here, an optimistic parallel execution of a new discrete event formulation of a reaction–diffusion simulation model of epidemic propagation is presented to facilitate a dramatic increase in the fidelity and speed by which epidemiological simulations can be performed. Rollback support needed during optimistic parallel execution is achieved by combining reverse computation with a small amount of incremental state saving. Parallel speedup of over 5,500 and other runtime performance metrics of the system are observed with weak-scaling execution on a small (8,192-core) Blue Gene/P system, while scalability with a weak-scaling speedup of over 10,000 is demonstrated on 65,536 cores of a large Cray XT5 system. Scenarios representing large population sizes, with mobility and detailed state evolution modeled at the level of each individual, exceeding several hundreds of millions of individuals in the largest cases, are successfully exercised to verify model scalability.