This scientific work focuses on computer-aided computational models in architecture. The author initially investigates established computational models and then expands these with newer approaches to modeling. In his research the author integrates approaches to analytical philosophy, probability theory, formal logic, quantum physics, abstract algebra, computer-aided design, computer graphics, glossematics, machine learning, architecture, and others. For researchers in the fields of information technology and architecture.
In this introduction to computational modelling the authors provide a concise description of computational methods, including dynamic simulation, knowledge-based models and machine learning, as a single broad class of research tools.
In this book we give an overview of modeling techniques used to describe computer systems to mathematical optimization tools. We give a brief introduction to various classes of mathematical optimization frameworks with special focus on mixed integer linear programming which provides a good balance between solver time and expressiveness. We present four detailed case studies -- instruction set customization, data center resource management, spatial architecture scheduling, and resource allocation in tiled architectures -- showing how MILP can be used and quantifying by how much it outperforms traditional design exploration techniques. This book should help a skilled systems designer to learn techniques for using MILP in their problems, and the skilled optimization expert to understand the types of computer systems problems that MILP can be applied to.
Codify: Parametric and Computational Design in Landscape Architecture provides a series of essays that explore what it means to use, modify and create computational tools in a contemporary design environment. Landscape architecture has a long history of innovation in the areas of computation and media, particularly in how the discipline represents, analyses, and constructs complex systems. This curated volume spans academic and professional projects to form a snapshot of digital practices that aim to show how computation is a tool that goes beyond methods of representation and media. The book is organized in four sections; syntax, perception, employ, and prospective. The essays are written by leading academics and professionals and the sections examine the role of computational tools in landscape architecture through case studies, historical accounts, theoretical arguments, and nascent propositions.
An investigation of different uses for the architectural model through history—as sign, souvenir, funerary object, didactic tool, medium for design, and architect's muse. For more than five hundred years, architects have employed three-dimensional models as tools to test, refine, and illustrate their ideas. But, as Matthew Mindrup shows, the uses of physical architectural models extend beyond mere representation. An architectural model can also simulate, instruct, inspire, and generate architectural designs. It can be, among other things, sign, souvenir, toy, funerary object, didactic tool, medium, or muse. In this book, Mindrup surveys the history of architectural models by investigating their uses, both theoretical and practical. Tracing the architectural model's development from antiquity to the present, Mindrup also offers an interpretive framework for understanding each of its applications in the context of time and place. He first examines models meant to portray extant, fantastic, or proposed structures, describing their use in ancient funerary or dedicatory practices, in which models are endowed with magical power; as a medium for architectural reverie and inspiration; and as prototypes for twentieth-century experimental designs. Mindrup then considers models that exemplify certain architectural uses, exploring the influence of Leon Battista Alberti's dictum that models be simple, lest they distract from the architect's ideas; analyzing the model as a generative tool; and investigating allegorical, analogical, and anagogical interpretations of models. Mindrup's histories show how the model can be a surrogate for the architectural structure itself, or for the experience of its formal, tactile, and sensory complexity; and beyond that, that the manipulation, play, experimentation, and dreaming enabled by models allow us to imagine architecture in new ways.
This book is an introduction to the High Level Architecture for modeling and simulation. The HLA is a software architecture for creating computer models and simulation out of component models or simulations. HLA was adopted by the US Defense Dept. The book is an introduction to HLA for application developers.
A variety of programming models relevant to scientists explained, with an emphasis on how programming constructs map to parts of the computer. What makes computer programs fast or slow? To answer this question, we have to get behind the abstractions of programming languages and look at how a computer really works. This book examines and explains a variety of scientific programming models (programming models relevant to scientists) with an emphasis on how programming constructs map to different parts of the computer's architecture. Two themes emerge: program speed and program modularity. Throughout this book, the premise is to "get under the hood," and the discussion is tied to specific programs. The book digs into linkers, compilers, operating systems, and computer architecture to understand how the different parts of the computer interact with programs. It begins with a review of C/C++ and explanations of how libraries, linkers, and Makefiles work. Programming models covered include Pthreads, OpenMP, MPI, TCP/IP, and CUDA.The emphasis on how computers work leads the reader into computer architecture and occasionally into the operating system kernel. The operating system studied is Linux, the preferred platform for scientific computing. Linux is also open source, which allows users to peer into its inner workings. A brief appendix provides a useful table of machines used to time programs. The book's website (https://github.com/divakarvi/bk-spca) has all the programs described in the book as well as a link to the html text.
Introduction to Computational Models with Python explains how to implement computational models using the flexible and easy-to-use Python programming language. The book uses the Python programming language interpreter and several packages from the huge Python Library that improve the performance of numerical computing, such as the Numpy and Scipy m
