Numerical Relativity As A Tool For Computational Astrophysics

The astrophysics of compact objects, which requires Einstein's theory of general relativity for understanding phenomena such as black holes and neutron stars, is attracting increasing attention. In general relativity, gravity is governed by an extremely complex set of coupled, nonlinear, hyperbolic-elliptic partial differential equations. The largest parallel supercomputers are finally approaching the speed and memory required to solve the complete set of Einstein's equations for the first time since they were written over 80 years ago, allowing one to attempt full 3D simulations of such exciting events as colliding black holes and neutron stars. In this paper we review the computational effort in this direction, and discuss a new 3D multi-purpose parallel code called ``Cactus'' for general relativistic astrophysics. Directions for further work are indicated where appropriate.Comment: Review for JCA

Parallel algorithms for real-time peptide-spectrum matching

Tandem mass spectrometry is a powerful experimental tool used in molecular biology to determine the composition of protein mixtures. It has become a standard technique for protein identification. Due to the rapid development of mass spectrometry technology, the instrument can now produce a large number of mass spectra which are used for peptide identification. The increasing data size demands efficient software tools to perform peptide identification. In a tandem mass experiment, peptide ion selection algorithms generally select only the most abundant peptide ions for further fragmentation. Because of this, the low-abundance proteins in a sample rarely get identified. To address this problem, researchers develop the notion of a `dynamic exclusion list', which maintains a list of newly selected peptide ions, and it ensures these peptide ions do not get selected again for a certain time. In this way, other peptide ions will get more opportunity to be selected and identified, allowing for identification of peptides of lower abundance. However, a better method is to also include the identification results into the `dynamic exclusion list' approach. In order to do this, a real-time peptide identification algorithm is required. In this thesis, we introduce methods to improve the speed of peptide identification so that the `dynamic exclusion list' approach can use the peptide identification results without affecting the throughput of the instrument. Our work is based on RT-PSM, a real-time program for peptide-spectrum matching with statistical significance. We profile the speed of RT-PSM and find out that the peptide-spectrum scoring module is the most time consuming portion. Given by the profiling results, we introduce methods to parallelize the peptide-spectrum scoring algorithm. In this thesis, we propose two parallel algorithms using different technologies. We introduce parallel peptide-spectrum matching using SIMD instructions. We implemented and tested the parallel algorithm on Intel SSE architecture. The test results show that a 18-fold speedup on the entire process is obtained. The second parallel algorithm is developed using NVIDIA CUDA technology. We describe two CUDA kernels based on different algorithms and compare the performance of the two kernels. The more efficient algorithm is integrated into RT-PSM. The time measurement results show that a 190-fold speedup on the scoring module is achieved and 26-fold speedup on the entire process is obtained. We perform profiling on the CUDA version again to show that the scoring module has been optimized sufficiently to the point where it is no longer the most time-consuming module in the CUDA version of RT-PSM. In addition, we evaluate the feasibility of creating a metric index to reduce the number of candidate peptides. We describe evaluation methods, and show that general indexing methods are not likely feasible for RT-PSM

Turbulent transport in rotating tokamak plasmas

Small scale turbulence in a magnetically confined fusion plasma drives energy and particle transport which determine the confinement. The plasma in a tokamak experiment has a toroidal rotation which may be driven externally, but can also arise spontaneously from turbulent momentum transport. This thesis investigates the interaction between turbulence and rotation via nonlinear numerical simulations, which use the gyrokinetic description in the frame that corotates with the plasma. A local gyrokinetic code is extended to include both the centrifugal force, and the stabilising effect of sheared equilibrium flow. Sheared flow perpendicular to the magnetic field suppresses the turbulence, and also breaks a symmetry of the local model. The resulting asymmetry creates a turbulent residual stress which can counteract diffusive momentum transport and contribute to spontaneous rotation. The competition between symmetry breaking and turbulence suppression results in a maximum in the nondiffusive momentum flux at intermediate shearing rates. Whilst this component of the momentum transport is driven by the sheared flow, it is also found to be suppressed by the shearing more strongly than the thermal transport. The direction of the residual stress reverses for negative magnetic shear, but also persists at zero magnetic shear. The parallel component of the centrifugal force traps particles on the outboard side of the plasma, which destabilises trapped particle driven modes. The perpendicular component of the centrifugal force appears as a centrifugal drift which modifies the phase relation between density and electric field perturbations, and is stabilising for both electron and ion driven instabilities. For ion temperature gradient dominated turbulence, an increased fraction of slow trapped electrons enhances the convective particle pinch, suggesting increased density peaking for strongly rotating plasmas. Heavy impurities feel the centrifugal force more strongly, therefore the effects of rotation are significant for impurities even when the bulk ion Mach number is low. For ion driven modes, rotation results in a strong impurity convection inward, whilst a more moderate convection outward is found for electron driven modes.EThOS - Electronic Theses Online ServiceEngineering and Physical Sciences Research Council (EPSRC)Culham Centre for Fusion Energy (CCFE)GBUnited Kingdo

Simulating Radiating and Magnetized Flows in Multi-Dimensions with ZEUS-MP

This paper describes ZEUS-MP, a multi-physics, massively parallel, message- passing implementation of the ZEUS code. ZEUS-MP differs significantly from the ZEUS-2D code, the ZEUS-3D code, and an early "version 1" of ZEUS-MP distributed publicly in 1999. ZEUS-MP offers an MHD algorithm better suited for multidimensional flows than the ZEUS-2D module by virtue of modifications to the Method of Characteristics scheme first suggested by Hawley and Stone (1995), and is shown to compare quite favorably to the TVD scheme described by Ryu et. al (1998). ZEUS-MP is the first publicly-available ZEUS code to allow the advection of multiple chemical (or nuclear) species. Radiation hydrodynamic simulations are enabled via an implicit flux-limited radiation diffusion (FLD) module. The hydrodynamic, MHD, and FLD modules may be used in one, two, or three space dimensions. Self gravity may be included either through the assumption of a GM/r potential or a solution of Poisson's equation using one of three linear solver packages (conjugate-gradient, multigrid, and FFT) provided for that purpose. Point-mass potentials are also supported. Because ZEUS-MP is designed for simulations on parallel computing platforms, considerable attention is paid to the parallel performance characteristics of each module. Strong-scaling tests involving pure hydrodynamics (with and without self-gravity), MHD, and RHD are performed in which large problems (256^3 zones) are distributed among as many as 1024 processors of an IBM SP3. Parallel efficiency is a strong function of the amount of communication required between processors in a given algorithm, but all modules are shown to scale well on up to 1024 processors for the chosen fixed problem size.Comment: Accepted for publication in the ApJ Supplement. 42 pages with 29 inlined figures; uses emulateapj.sty. Discussions in sections 2 - 4 improved per referee comments; several figures modified to illustrate grid resolution. ZEUS-MP source code and documentation available from the Laboratory for Computational Astrophysics at http://lca.ucsd.edu/codes/currentcodes/zeusmp2

HARDWARE-ACCELERATED AUTOMATIC 3D NONRIGID IMAGE REGISTRATION

Software implementations of 3D nonrigid image registration, an essential tool in medical applications like radiotherapies and image-guided surgeries, run excessively slow on traditional computers. These algorithms can be accelerated using hardware methods by exploiting parallelism at different levels in the algorithm. We present here, an implementation of a free-form deformation-based algorithm on a field programmable gate array (FPGA) with a customized, parallel and pipelined architecture. We overcome the performance bottlenecks and gain speedups of up to 40x over traditional computers while achieving accuracies comparable to software implementations. In this work, we also present a method to optimize the deformation field using a gradient descent-based optimization scheme and solve the problem of mesh folding, commonly encountered during registration using free-form deformations, using a set of linear constraints. Finally, we present the use of novel dataflow modeling tools to automatically map registration algorithms to hardware like FPGAs while allowing for dynamic reconfiguration

Interface Tracking and Solid-Fluid Coupling Techniques with Coastal Engineering Applications

Multi-material physics arise in an innumerable amount of engineering problems. A broadly scoped numerical model is developed and described in this thesis to simulate the dynamic interaction of multi-fluid and solid systems. It is particularly aimed at modelling the interaction of two immiscible fluids with solid structures in a coastal engineering context; however it can be extended to other similar areas of research. The Navier Stokes equations governing the fluids are solved using a combination of finite element (FEM) and control volume finite element (CVFE) discretisations. The sharp interface between the fluids is obtained through the compressive transport of material properties (e.g. material concentration). This behaviour is achieved through the CVFE method and a conveniently limited flux calculation scheme based on the Hyper-C method by Leonard (1991). Analytical and validation test cases are provided, consisting of steady and unsteady flows. To further enhance the method, improve accuracy, and exploit Lagrangian benefits, a novel moving mesh method is also introduced and tested. It is essentially an Arbitrary Lagrangian Eulerian method in which the grid velocity is defined by semi-explicitly solving an iterative functional minimisation problem. A multi-phase approach is used to introduce solid structure modelling. In this approach, solution of the velocity field for the fluid phase is obtained using Model B as explained by Gidaspow (1994, page 151). Interaction between the fluid phase and the solids is achieved through the means of a source term included in the fluid momentum equations. The interacting force is calculated through integration of this source term and adding a buoyancy contribution. The resulting force is passed to an external solid-dynamics model such as the Discrete Element Method (DEM), or the combined Finite Discrete Element Method (FEMDEM). The versatility and novelty of this combined modelling approach stems from its ability to capture the fluid interaction with particles of random size and shape. Each of the three main components of this thesis: the advection scheme, the moving mesh method, and the solid interaction are individually validated, and examples of randomly shaped and sized particles are shown. To conclude the work, the methods are combined together in the context of coastal engineering applications, where the complex coupled problem of waves impacting on breakwater amour units is chosen to demonstrate the simulation possibilities. The three components developed in this thesis significantly extend the application range of already powerful tools, such as Fluidity, for fluids-modelling and finite discrete element solids-modelling tools by bringing them together for the first time