56 research outputs found
A Generalized Grid-Based Fast Multipole Method for Integrating Helmholtz Kernels
A grid-based fast multipole method (GB-FMM) for optimizing three-dimensional (3D) numerical molecular orbitals in the bubbles and cube double basis has been developed and implemented. The present GB-FMM method is a generalization of our recently published GB-FMM approach for numerically calculating electrostatic potentials and two-electron interaction energies. The orbital optimization is performed by integrating the Helmholtz kernel in the double basis. The steep part of the functions in the vicinity of the nuclei is represented by one-center bubbles functions, whereas the remaining cube part is expanded on an equidistant 3D grid The integration of the bubbles part is treated by using one-center expansions of the Helmholtz kernel in spherical harmonics multiplied with modified spherical Bessel functions of the first and second kind, analogously to the numerical inward and outward integration approach for calculating two-electron interaction potentials in atomic structure calculations. The expressions and algorithms for massively parallel calculations on general purpose graphics processing units (GPGPU) are described. The accuracy and the correctness of the implementation has been checked by performing Hartree-Fock self-consistent-field calculations (HF-SCF) on H-2, H2O, and CO. Our calculations show that an accuracy of 10(-4) to 10(-7) E-h can be reached in HF-SCF calculations on general molecules.Peer reviewe
FARGO3D: A new GPU-oriented MHD code
We present the FARGO3D code, recently publicly released. It is a magnetohydrodynamics code developed with special emphasis on the physics of protoplanetary disks and planet-disk interactions, and parallelized with MPI. The hydrodynamics algorithms are based on finite-difference upwind, dimensionally split methods. The magnetohydrodynamics algorithms consist of the constrained transport method to preserve the divergence-free property of the magnetic field to machine accuracy, coupled to a method of characteristics for the evaluation of electromotive forces and Lorentz forces. Orbital advection is implemented, and an N-body solver is included to simulate planets or stars interacting with the gas. We present our implementation in detail and present a number of widely known tests for comparison purposes. One strength of FARGO3D is that it can run on either graphical processing units (GPUs) or central processing units (CPUs), achieving large speed-up with respect to CPU cores. We describe our implementation choices, which allow a user with no prior knowledge of GPU programming to develop new routines for CPUs, and have them translated automatically for GPUs.Fil: Benítez Llambay, Pablo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Astronomía Teórica y Experimental. Universidad Nacional de Córdoba. Observatorio Astronómico de Córdoba. Instituto de Astronomía Teórica y Experimental; ArgentinaFil: Masset, Frédéric S.. Universidad Nacional Autónoma de México; Méxic
Massively parallel split-step Fourier techniques for simulating quantum systems on graphics processing units
The split-step Fourier method is a powerful technique for solving partial differential equations and simulating ultracold atomic systems of various forms. In this body of work, we focus on several variations of this method to allow for simulations of one, two, and three-dimensional quantum systems, along with several notable methods for controlling these systems. In particular, we use quantum optimal control and shortcuts to adiabaticity to study the non-adiabatic generation of superposition states in strongly correlated one-dimensional systems, analyze chaotic vortex trajectories in two dimensions by using rotation and phase imprinting methods, and create stable, threedimensional vortex structures in Bose–Einstein condensates through artificial magnetic fields generated by the evanescent field of an optical nanofiber. We also discuss algorithmic optimizations for implementing the split-step Fourier method on graphics processing units. All computational methods present in this work are demonstrated on physical systems and have been incorporated into a state-of-the-art and open-source software suite known as GPUE, which is currently the fastest quantum simulator of its kind.Okinawa Institute of Science and Technology Graduate Universit
Fast algorithm for real-time rings reconstruction
The GAP project is dedicated to study the application of GPU in several contexts in which
real-time response is important to take decisions. The definition of real-time depends on
the application under study, ranging from answer time of μs up to several hours in case
of very computing intensive task. During this conference we presented our work in low
level triggers [1] [2] and high level triggers [3] in high energy physics experiments, and
specific application for nuclear magnetic resonance (NMR) [4] [5] and cone-beam CT [6].
Apart from the study of dedicated solution to decrease the latency due to data transport
and preparation, the computing algorithms play an essential role in any GPU application.
In this contribution, we show an original algorithm developed for triggers application, to
accelerate the ring reconstruction in RICH detector when it is not possible to have seeds
for reconstruction from external trackers
Recommended from our members
Particle Dynamics Simulation toward High-Shear Mixing Process in Many Particle Systems
Granular materials appear in a broad range of industrial processes, including mineral processing, plastics manufacturing, ceramic component, pharmaceutical tablets and food products. Engineers and scientists are always seeking efficient tools that can characterize, predict, or simulate the effective material properties in a timely manner and with acceptable accuracy, such that the cost for design and develop novel composite granular materials could be reduced.
The major scope of this dissertation covers the development, verification and validation of particle system simulations, including solid-liquid two-phase particle mixing process and foaming asphalt process. High shear mixing process is investigated in detail with different types of mixers. Besides particle mixing study, one liquid-gas two phase foaming asphalt simulation is studied to show the broad capacity of our particulate dynamics simulation scheme. Methodologies and numerical studies for different scenarios are presented, and acceleration plans to speed up the simulations are discussed in detail.
The dissertation starts with the problem statement, which briefly demonstrates the background of the problem and introduces the numerical models built from the physical world. In this work, liquid-solid two-phase particle mixing process is mainly studied. These mixing processes are conducted in a sealed mixer and different types of particles are mixed with the rotation of the mixer blades, to obtain a homogeneous particle mixture. In addition to the solid-liquid particle mixing problem, foaming asphalt problem, which is a liquid-gas two phase flow problem is also investigated. Foaming asphalt is generated by injecting a small amount of liquid additive (usually water) to asphalt at a high temperature. The volume change during this asphalt foaming process is studied.
Given the problem statement, detailed methodologies of particle dynamics simulation are illustrated. For solid-liquid particle mixing, Smoothed Particle Hydrodynamics (SPH) and Discrete Element Method (DEM) are introduced and implemented to simulate the dynamics of solid and liquid particles, respectively. Solid-liquid particle interactions are computed according to Darcy`s Law. Then the proposed SPH coupling DEM model is verified by three classical case studies.
For foaming asphalt problems, a SPH numerical model for foaming asphalt simulation is proposed, and simulations with different water contents, pressures and temperatures are conducted and the results agree with the experiments well. The coupled SPH-DEM method is applied to the particle mixing process, and several particle mixing numerical studies are conducted and these simulations are analyzed in multiple aspects. For the solid-liquid particle mixing problem, liquid plays an important role in the mixing performance. The effects of liquid content and liquid viscosity on mixing performance are studied. The mixing indexes of the mixture are applied to analyze the mixing quality, and the differences between three kinds of mixing indexes are discussed. Then mixers commonly used in industry such as Double Planetary Mixer (DPM) are modeled in mixing simulation and their results are compared with the experiments.
Similar to other numerical simulation problems, the scale of the model and the accuracy of the simulation results are constrained by the computational capacity. Our in-house software package Particle Dynamics Parallel Simulator(PDPS) has been used as a platform to implement the algorithms above and conduct the simulations. Two parallel computing methods of Message Passing Interface (MPI) parallel computing and Graphics Processing Unit (GPU) acceleration have been used to accelerate the simulations. Speedup results for both MPI parallel computing and GPU methods are illustrated in the case studies.
In summary, a comprehensive approach for particle simulation is proposed and applied to particle mixing process and asphalt foaming simulation. The simulation results are analyzed in various aspects to provide valuable insights to the problems studied in this work. Given the improvement of computational capacity, particle dynamics in higher resolution and simulations in more complex configurations can be obtained. This particle simulation platform is general and it can be straightforwardly extended to many-particle systems with more particle phases and solid-liquid-gas dynamics problems
Cellular Automata
Modelling and simulation are disciplines of major importance for science and engineering. There is no science without models, and simulation has nowadays become a very useful tool, sometimes unavoidable, for development of both science and engineering. The main attractive feature of cellular automata is that, in spite of their conceptual simplicity which allows an easiness of implementation for computer simulation, as a detailed and complete mathematical analysis in principle, they are able to exhibit a wide variety of amazingly complex behaviour. This feature of cellular automata has attracted the researchers' attention from a wide variety of divergent fields of the exact disciplines of science and engineering, but also of the social sciences, and sometimes beyond. The collective complex behaviour of numerous systems, which emerge from the interaction of a multitude of simple individuals, is being conveniently modelled and simulated with cellular automata for very different purposes. In this book, a number of innovative applications of cellular automata models in the fields of Quantum Computing, Materials Science, Cryptography and Coding, and Robotics and Image Processing are presented
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