Operating System Algorithm Code


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Design and Implementation of Operating System


Design and Implementation of Operating System

Author: Er. Vivek Sharma

language: en

Publisher: Laxmi Publications, Ltd.

Release Date: 2010-08


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Design and Implementation of the MTX Operating System


Design and Implementation of the MTX Operating System

Author: K. C. Wang

language: en

Publisher: Springer

Release Date: 2015-06-29


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This course-tested textbook describes the design and implementation of operating systems, and applies it to the MTX operating system, a Unix-like system designed for Intel x86 based PCs. Written in an evolutional style, theoretical and practical aspects of operating systems are presented as the design and implementation of a complete operating system is demonstrated. Throughout the text, complete source code and working sample systems are used to exhibit the techniques discussed. The book contains many new materials on the design and use of parallel algorithms in SMP. Complete coverage on booting an operating system is included, as well as, extending the process model to implement threads support in the MTX kernel, an init program for system startup and a sh program for executing user commands. Intended for technically oriented operating systems courses that emphasize both theory and practice, the book is also suitable for self-study.

Algorithms with JULIA


Algorithms with JULIA

Author: Clemens Heitzinger

language: en

Publisher: Springer Nature

Release Date: 2022-12-12


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This book provides an introduction to modern topics in scientific computing and machine learning, using JULIA to illustrate the efficient implementation of algorithms. In addition to covering fundamental topics, such as optimization and solving systems of equations, it adds to the usual canon of computational science by including more advanced topics of practical importance. In particular, there is a focus on partial differential equations and systems thereof, which form the basis of many engineering applications. Several chapters also include material on machine learning (artificial neural networks and Bayesian estimation). JULIA is a relatively new programming language which has been developed with scientific and technical computing in mind. Its syntax is similar to other languages in this area, but it has been designed to embrace modern programming concepts. It is open source, and it comes with a compiler and an easy-to-use package system. Aimed at students of applied mathematics, computer science, engineering and bioinformatics, the book assumes only a basic knowledge of linear algebra and programming.