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X-ray crystallography provides a unique opportunity to study the arrangement of atoms in a molecule. This book's modern computer-graphics centered approach facilitates the extrapolation of these valuable observations. A unified treatment of crystal systems, the book explains how atoms are arranged in crystals using the metric matrix. Featuring t
Explore GPU-enabled programmable environment for machine learning, scientific applications, and gaming using PuCUDA, PyOpenGL, and Anaconda Accelerate Key FeaturesUnderstand effective synchronization strategies for faster processing using GPUsWrite parallel processing scripts with PyCuda and PyOpenCLLearn to use the CUDA libraries like CuDNN for deep learning on GPUsBook Description GPUs are proving to be excellent general purpose-parallel computing solutions for high performance tasks such as deep learning and scientific computing. This book will be your guide to getting started with GPU computing. It will start with introducing GPU computing and explain the architecture and programming models for GPUs. You will learn, by example, how to perform GPU programming with Python, and you’ll look at using integrations such as PyCUDA, PyOpenCL, CuPy and Numba with Anaconda for various tasks such as machine learning and data mining. Going further, you will get to grips with GPU work flows, management, and deployment using modern containerization solutions. Toward the end of the book, you will get familiar with the principles of distributed computing for training machine learning models and enhancing efficiency and performance. By the end of this book, you will be able to set up a GPU ecosystem for running complex applications and data models that demand great processing capabilities, and be able to efficiently manage memory to compute your application effectively and quickly. What you will learnUtilize Python libraries and frameworks for GPU accelerationSet up a GPU-enabled programmable machine learning environment on your system with AnacondaDeploy your machine learning system on cloud containers with illustrated examplesExplore PyCUDA and PyOpenCL and compare them with platforms such as CUDA, OpenCL and ROCm.Perform data mining tasks with machine learning models on GPUsExtend your knowledge of GPU computing in scientific applicationsWho this book is for Data Scientist, Machine Learning enthusiasts and professionals who wants to get started with GPU computation and perform the complex tasks with low-latency. Intermediate knowledge of Python programming is assumed.
Computing Methods in Crystallography is a collection of lectures delivered at a Summer School, held in Oxford in August 1962. The book presents the underlying mathematics and computing methods in crystallography. The text covers topics on the algebra required for the fundamental operations of transformation of coordinates, interpolation, approximation of trigonometric and exponential functions, solution of linear equations and derivation of latent roots and vectors; methods for calculation of structure factors, least-squares adjustment, and Fourier series evaluation; the theory and practice of intensity scaling and symmetry determination; and methods of direct phase determination. Crystallographers, physicists, and students in allied fields will find the book very useful.
International Tables for Crystallography Volume G, Definition and exchange of crystallographic data, describes the standard data exchange and archival file format (the Crystallographic Information File, or CIF) used throughout crystallography. It provides in-depth information vital for small-molecule, inorganic and macromolecular crystallographers, mineralogists, chemists, materials scientists, solid-state physicists and others who wish to record or use the results of a single-crystal or powder diffraction experiment. The volume also provides the detailed data ontology necessary for programmers and database managers to design interoperable computer applications. The accompanying CD-ROM contains the CIF dictionaries in machine-readable form and a collection of libraries and utility programs. This volume is an essential guide and reference for programmers of crystallographic software, data managers handling crystal-structure information and practising crystallographers who need to use CIF.
This book provides a clear introduction to topics which are essential to students in a wide range of scientific disciplines but which are otherwise only covered in specialised and mathematically detailed texts. It shows how crystal structures may be built up from simple ideas of atomic packing and co-ordination, it develops the concepts of crystal symmetry, point and space groups by way of two dimensional examples of patterns and tilings, it explains the concept of the reciprocal lattice in simple terms and shows its importance in an understanding of light, X-ray and electron diffraction. Practical examples of the applications of these techniques are described and also the importance of diffraction in the performance of optical instruments. The book is also of value to the general reader since it shows, by biographical and historical references, how the subject has developed and thereby indicates some of the excitement of scientific discovery.
Crystallography Made Crystal Clear is designed to meet the need for an X-ray analysis that is between brief textbook sections and complete treatments. The book provides non-crystallographers with an intellectually satisfying explanation of the principles of how protein models are gleaned from X-ray analysis. The understanding of these concepts will foster wise use of the models, including the recognition of the strengths and weaknesses of pictures or computer graphics. Since proteins comprise the majority of the mass of macromolecules in cells and carry out biologically important tasks, the book will be of interest to biologists.Provides accessible descriptions of principles of x-ray crystallography, built on simple foundations for anyone with a basic science backgroundLeads the reader through clear, thorough, unintimidating explanations of the mathematics behind crystallographyExplains how to read crystallography papers in research journalsIf you use computer-generated models of proteins or nucleic acids for:Studying molecular interactionsDesigning ligands, inhibitors, or drugsEngineering new protein functionsInterpreting chemical, kinetic, thermodynamic, or spectroscopic dataStudying protein foldingTeaching macromolecule structure,and if you want to read new structure papers intelligently; become a wiser user of macromolecular models; and want to introduce undergraduates to the important subject of x-ray crystallography, then this book is for you.
A valuable learning tool as well as a reference, this book provides students and researchers in surface science and nanoscience with the theoretical crystallographic foundations, which are necessary to understand local structure and symmetry of bulk crystals, including ideal and real single crystal surfaces. The author deals with the subject at an introductory level, providing numerous graphic examples to illustrate the mathematical formalism. The book brings together and logically connects many seemingly disparate structural issues and notations used frequently by surface scientists and nanoscientists. Numerous exercises of varying difficulty, ranging from simple questions to small research projects, are included to stimulate discussions about the different subjects. From the contents: Bulk Crystals, Three-Dimensional Lattices - Crystal Layers, Two-Dimensional Lattices, Symmetry - Ideal Single Crystal Surfaces - Real Crystal Surfaces - Adsorbate layers - Interference Lattices - Chiral Surfaces - Experimental Analysis of Real Crystal Surfaces - Nanoparticles and Crystallites - Quasicrystals - Nanotubes
The book presents the basic information needed to understand and to organize the huge amount of known structures of crystalline solids. Its basis is crystallographic group theory (space group theory), with special emphasis on the relations between the symmetry properties of crystals.