Towards Optimal Application Mapping for Energy-Efficient Many-Core Platforms

Siirretty Doriast

Evolutionary Algorithms and Computational Methods for Derivatives Pricing

This work aims to provide novel computational solutions to the problem of derivative pricing. To achieve this, a novel hybrid evolutionary algorithm (EA) based on particle swarm optimisation (PSO) and differential evolution (DE) is introduced and applied, along with various other state-of-the-art variants of PSO and DE, to the problem of calibrating the Heston stochastic volatility model. It is found that state-of-the-art DEs provide excellent calibration performance, and that previous use of rudimentary DEs in the literature undervalued the use of these methods. The use of neural networks with EAs for approximating the solution to derivatives pricing models is next investigated. A set of neural networks are trained from Monte Carlo (MC) simulation data to approximate the closed form solution for European, Asian and American style options. The results are comparable to MC pricing, but with offline evaluation of the price using the neural networks being orders of magnitudes faster and computationally more efficient. Finally, the use of custom hardware for numerical pricing of derivatives is introduced. The solver presented here provides an energy efficient data-flow implementation for pricing derivatives, which has the potential to be incorporated into larger high-speed/low energy trading systems

Small satellite earth-to-moon direct transfer trajectories using the CR3BP

The CubeSat/small satellite field is one of the fastest growing means of space exploration, with applications continuing to expand for component development, communication, and scientific research. This thesis study focuses on establishing suitable small satellite Earth-to-Moon direct-transfer trajectories, providing a baseline understanding of their propulsive demands, determining currently available off-the-shelf propulsive technology capable of meeting these demands, as well as demonstrating the effectiveness of the Circular Restricted Three Body Problem (CR3BP) for preliminary mission design. Using the CR3BP and derived requirements from NASA\u27s Cube Quest Challenge, five different trajectory scenarios were analyzed for their propulsive requirements. Results indicate that the CR3BP is an effective means for preliminary mission design; however, limitations were noted in its ability to account for the lunar orbit eccentricity with respect to the Earth. Additionally, two available options of off-the-shelf propulsion systems are identified that can achieve the ΔV necessary for lunar capture, but have not yet been demonstrated in-flight --Abstract, page iii

Optimizing Image Reconstruction in Electrical Impedance Tomography

Tato disertační práce pojednává o optimalizaci algoritmů pro rekonstrukci obrazu neznámé měrné vodivosti z měřených dat pořízených elektrickou impedanční tomografií. Danou problematiku zde věcně vymezuje několik různých prvků, zejména pak stručný matematický popis dopředné a inverzní úlohy řešené různými přístupy, metodika měření a pořizování dat pro rekonstrukci a přehled dostupných numerických nástrojů. Uvedenou charakteristiku rozšiřuje rozbor optimalizací parametrů modelu ovlivňujících přesnost rekonstrukce, způsoby paralelního zpracování algoritmů a souhrn dostupných zařízení pro měření tomografických dat. Na základě získaných poznatků byla navržena optimalizace parametrů matematického modelu, která umožňuje jeho velmi přesný návrh dle měřených dat. V této souvislosti dochází ke snížení nejistoty rekonstrukce rozložení konduktivity. Pro zefektivnění procesu získávání dat bylo navrženo zařízení k automatizaci tomografie s důrazem na cenovou dostupnost a snížení nejistoty měření. V oblasti tvorby numerického modelu byly dále zkoumány možnosti užití otevřených a uzavřených domén pro různé metody regularizace a hrubost sítě, a to s ohledem na velikost chyby rekonstruované konduktivity a výpočetní náročnost. Součástí práce je také paralelizace subalgoritmů rekonstrukce s využitím vícejádrové grafické karty. Předložené výsledky mají přímý vliv na snížení nejistoty rekonstrukce (optimalizací počáteční hodnoty konduktivity, rozmístění elektrod a tvarové deformace domény, regularizačních metod a typu domén) a urychlení výpočtů paralelizací algoritmů, přičemž výzkum byl podpořen vlastním návrhem jednotky pro automatizaci tomografie.The thesis presents, analyzes, and discusses the optimization of algorithms that reconstruct images of unknown specific conductivity from data acquired via electrical impedance tomography. In this context, the author provides a brief mathematical description of the forward and inverse tasks solved by using diverse approaches, characterizes relevant measurement techniques and data acquisition procedures, and discusses available numerical tools. Procedurally, the initial working stages involved analyzing the methods for optimizing those parameters of the model that influence the reconstruction accuracy; demonstrating approaches to the parallel processing of the algorithms; and outlining a survey of available instruments to acquire the tomographic data. The obtained knowledge then yielded a process for optimizing the parameters of the mathematical model, thus allowing the model to be designed precisely, based on the measured data; such a precondition eventually reduced the uncertainty in reconstructing the specific conductivity distribution. When forming the numerical model, the author investigated the possibilities and overall impact of combining the open and closed domains with various regularization methods and mesh element scales, considering both the character of the conductivity reconstruction error and the computational intensity. A complementary task resolved within the broader scheme outlined above lay in parallelizing the reconstruction subalgorithms by using a multi-core graphics card. The results of the thesis are directly reflected in a reduced reconstruction uncertainty (through an optimization of the initial conductivity value, placement of the electrodes, and shape deformation of the domains) and accelerated computation via parallelized algorithms. The actual research benefited from an in-house designed automated tomography unit.

NASA Tech Briefs, November 2009

Topics covered include: Cryogenic Chamber for Servo-Hydraulic Materials Testing; Apparatus Measures Thermal Conductance Through a Thin Sample from Cryogenic to Room Temperature; Rover Attitude and Pointing System Simulation Testbed; Desktop Application Program to Simulate Cargo-Air-Drop Tests; Multimodal Friction Ignition Tester; Small-Bolt Torque-Tension Tester; Integrated Spacesuit Audio System Enhances Speech Quality and Reduces Noise; Hardware Implementation of a Bilateral Subtraction Filter; Simple Optoelectronic Feedback in Microwave Oscillators; Small X-Band Oscillator Antennas; Free-Space Optical Interconnect Employing VCSEL Diodes; Discrete Fourier Transform Analysis in a Complex Vector Space; Miniature Scroll Pumps Fabricated by LIGA; Self-Assembling, Flexible, Pre-Ceramic Composite Preforms; Flight-speed Integral Image Analysis Toolkit; Work Coordination Engine; Multi-Mission Automated Task Invocation Subsystem; Autonomously Calibrating a Quadrupole Mass Spectrometer; Determining Spacecraft Reaction Wheel Friction Parameters; Composite Silica Aerogels Opacified with Titania; Multiplexed Colorimetric Solid-Phase Extraction; Detecting Airborne Mercury by Use of Polymer/Carbon Films; Lattice-Matched Semiconductor Layers on Single Crystalline Sapphire Substrate; Pressure-Energized Seal Rings to Better Withstand Flows; Rollerjaw Rock Crusher; Microwave Sterilization and Depyrogenation System; Quantifying Therapeutic and Diagnostic Efficacy in 2D Microvascular Images; NiF2/NaF:CaF2/Ca Solid-State High-Temperature Battery Cells; Critical Coupling Between Optical Fibers and WGM Resonators; Microwave Temperature Profiler Mounted in a Standard Airborne Research Canister; Alternative Determination of Density of the Titan Atmosphere; Solar Rejection Filter for Large Telescopes; Automated CFD for Generation of Airfoil Performance Tables; Progressive Classification Using Support Vector Machines; Active Learning with Irrelevant Examples; A Data Matrix Method for Improving the Quantification of Element Percentages of SEM/EDX Analysis; Deployable Shroud for the International X-Ray Observatory; Improved Model of a Mercury Ring Damper; Optoelectronic pH Meter: Further Details; X-38 Advanced Sublimator; and Solar Simulator Represents the Mars Surface Solar Environment

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

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

A Comprehensive Survey on Particle Swarm Optimization Algorithm and Its Applications

Particle swarm optimization (PSO) is a heuristic global optimization method, proposed originally by Kennedy and Eberhart in 1995. It is now one of the most commonly used optimization techniques. This survey presented a comprehensive investigation of PSO. On one hand, we provided advances with PSO, including its modifications (including quantum-behaved PSO, bare-bones PSO, chaotic PSO, and fuzzy PSO), population topology (as fully connected, von Neumann, ring, star, random, etc.), hybridization (with genetic algorithm, simulated annealing, Tabu search, artificial immune system, ant colony algorithm, artificial bee colony, differential evolution, harmonic search, and biogeography-based optimization), extensions (to multiobjective, constrained, discrete, and binary optimization), theoretical analysis (parameter selection and tuning, and convergence analysis), and parallel implementation (in multicore, multiprocessor, GPU, and cloud computing forms). On the other hand, we offered a survey on applications of PSO to the following eight fields: electrical and electronic engineering, automation control systems, communication theory, operations research, mechanical engineering, fuel and energy, medicine, chemistry, and biology. It is hoped that this survey would be beneficial for the researchers studying PSO algorithms