Domänen parallele Maschinen

A computational model is introduced, which abstracts and idealizes computers with access to fragment shaders. While the set of functions computable by this model remains the same, the running times can be drastically reduced through parallelization compared to conventional models. Some of the algorithms designed for the model can be approximated using fragment shaders. With an automatic transcompilation scheme, fragment shader programs can be generated automatically from a description in a high-level language.In dieser Arbeit wird ein Rechenmodell, das Computer mit Zugriff zu Fragment Shader abstrahiert und idealisiert, eingeführt. Zwar bleibt der Umfang der durch dieses Modell berechenbarer Funktionen gleich, jedoch können die Laufzeiten durch Parallelisierung im Vergleich zu herkömmlichen Modellen drastisch verkürzt werden. Einige der für das Modell entworfenen Algorithmen lassen sich mithilfe von Fragment Shadern approximieren. In einer Hochsprache beschriebene Algorithmen werden automatisiert in Fragment Shader Programme übersetzt

Bibliography of Lewis Research Center technical publications announced in 1989

This compilation of abstracts describes and indexes the technical reporting that resulted from the scientific and engineering work performed and managed by the Lewis Research Center in 1989. All the publications were announced in the 1989 issues of STAR (Scientific and Technical Aerospace Reports) and/or IAA (International Aerospace Abstracts). Included are research reports, journal articles, conference presentations, patents and patent applications, and theses

Aeronautical engineering: A continuing bibliography with indexes (supplement 212)

This bibliography lists 493 reports, articles and other documents introduced into the NASA scientific and technical information system in March, 1987

Architecture of Advanced Numerical Analysis Systems

This unique open access book applies the functional OCaml programming language to numerical or computational weighted data science, engineering, and scientific applications. This book is based on the authors' first-hand experience building and maintaining Owl, an OCaml-based numerical computing library. You'll first learn the various components in a modern numerical computation library. Then, you will learn how these components are designed and built up and how to optimize their performance. After reading and using this book, you'll have the knowledge required to design and build real-world complex systems that effectively leverage the advantages of the OCaml functional programming language. What You Will Learn Optimize core operations based on N-dimensional arrays Design and implement an industry-level algorithmic differentiation module Implement mathematical optimization, regression, and deep neural network functionalities based on algorithmic differentiation Design and optimize a computation graph module, and understand the benefits it brings to the numerical computing library Accommodate the growing number of hardware accelerators (e.g. GPU, TPU) and execution backends (e.g. web browser, unikernel) of numerical computation Use the Zoo system for efficient scripting, code sharing, service deployment, and composition Design and implement a distributed computing engine to work with a numerical computing library, providing convenient APIs and high performance Who This Book Is For Those with prior programming experience, especially with the OCaml programming language, or with scientific computing experience who may be new to OCaml. Most importantly, it is for those who are eager to understand not only how to use something, but also how it is built up

High-Fidelity Simulation of Small-Body Lander/Rover Spacecraft

The scientific return of spacecraft missions that explore solar system small bodies can be increased through the inclusion of surface exploration with deployed probes. In this dissertation, a methodology is presented that allows for fast, parallel simulation of bouncing trajectories of arbitrary-shaped ballistic probes in the small-body environment. This enables planning of probe deployment and operation, and supports their inclusion on future missions.The coarse small-body shape is modeled using an implicit signed distance field (SDF) that allows for fast collision detection. Statistical features are included onto the SDF using procedural generation techniques. The small-body gravity field is captured using a voxelization of the classical constant-density polyhedron. Surface interactions between a probe and the surface are accounted for using a hard contact model that takes into account restitution and friction. These models are implemented in a GPU environment to allow for the parallel execution of multiple trajectories.The developed simulation framework is applied to perform parametric investigations of probe deployment, which quantify the effects of relevant properties of a probe and its target small body. The probe shape and internal mass distribution are found to strongly affect its deployment dynamics, with near-spherical probes dispersing over greater regions than more distorted shapes. The effect of the surface interactions coefficients on the different shapes variants is quantified. The presence of statistical surface features is also shown to further influence probe dynamics.Finally, the framework is applied to perform a pre-arrival deployment analysis of the MINERVA-II rovers onboard the Hayabusa-2 spacecraft. This analysis identified challenges in the rover deployment and was used to redesign aspects of the nominal rover release sequence. These models will be used to inform the target site selection and follow-on analysis for the Hayabusa-2 mission rover deployments

Optimizing Constrainted Concurrent Applications at Run-time

Computer systems are resource constrained. Application adaptation is a useful way to optimize system resource usage while satisfying an application’s performance requirements. Current multicore computer systems supporting these applications, however, are not designed to reliably meet these requirements. Meanwhile, these computer systems are resource-limited, e.g., have power-induced energy and thermal constraints. Compounding the application’s performance requirements are increasingly-stringent microprocessor thermal constraints. Previous application adaptation efforts, however, were ad-hoc, time-consuming, and highly application-specific, with limited portability between computer systems. This thesis presents OCCAM, a software platform for developing multicore adaptable applications. OCCAM’s design-time platform consists of design patterns, APIs, and data structures that allow application developers to specify the performance constraints and application-specific optimization techniques. OCCAM generates a run-time controller offline, using profiling data. It then uses this profiling data to generate an internal model that it subsequently employs to generate a robust Markov Decision Process-based Model Predictive Controller. Using a set of Recognition, Mining, and Synthesis benchmarks, the experimental study demonstrates that OCCAM can successfully optimize the system while meeting the systems performance requirements across a wide range of computer platforms, ranging from an energy-constrained single-core system to a high-performance 16-core system. Finally, OCCAM presents a simulation-based, stochastic model checking-based framework for quantifying the robustness of the controller