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In the history of modern computation, large mechanical calculators preceded computers. A person would sit there punching keys according to a procedure and a number would eventually appear. Once calculators became fast enough, it became obvious that the critical path was the punching rather than the calculation itself. That is what made the stored program concept vital to further progress. Once the instructions were stored in the machine, the entire computation could run at the speed of the machine. This book shows how to do the same thing for DNA computing. Rather than asking a robot or a person to pour in specific strands at different times in order to cause a DNA computation to occur (by analogy to a person punching numbers and operations into a mechanical calculator), the DNA instructions are stored within the solution and guide the entire computation. We show how to store straight line programs, conditionals, loops, and a rudimentary form of subroutines. To achieve this goal, the book proposes a complete language for describing the intrinsic topology of DNA complexes and nanomachines, along with the dynamics of such a system. We then describe dynamic behavior using a set of basic transitions, which operate on a small neighborhood within a complex in a well-defined way. These transitions can be formalized as purely syntactical functions of the string representations. Building on that foundation, the book proposes a novel machine motif which constitutes an instruction stack, allowing for the clocked release of an arbitrary sequence of DNA instruction or data strands. The clock mechanism is built of special strands of DNA called ""tick"" and ""tock."" Each time a ""tick"" and ""tock"" enter a DNA solution, a strand is released from an instruction stack (by analogy to the way in which as a clock cycle in an electronic computer causes a new instruction to enter a processing unit). As long as there remain strands on the stack, the next cycle will release a new instruction strand. Regardless of the actual strand or component to be released at any particular clock step, the ""tick"" and ""tock"" fuel strands remain the same, thus shifting the burden of work away from the end user of a machine and easing operation. Pre-loaded stacks enable the concept of a stored program to be realized as a physical DNA mechanism. A conceptual example is given of such a stack operating a walker device. The stack allows for a user to operate such a clocked walker by means of simple repetition of adding two fuel types, in contrast to the previous mechanism of adding a unique fuel -- at least 12 different types of strands -- for each step of the mechanism. We demonstrate by a series of experiments conducted in Ned Seeman's lab that it is possible to ""initialize"" a clocked stored program DNA machine. We end the book with a discussion of the design features of a programming language for clocked DNA programming. There is a lot left to do. Table of Contents: Introduction / Notation / A Topological Description of DNA Computing / Machines and Motifs / Experiment: Storing Clocked Programs in DNA / A Clocked DNA Programming Language
This book introduces all the technical features that make up blockchain technology today. It starts with a thorough explanation of all technological concepts necessary to understand any discussions related to distributed ledgers and a short history of earlier implementations. It then discusses in detail how the Bitcoin network looks and what changes are coming in the near future, together with a range of altcoins that were created on the same base code. To get an even better idea, the book shortly explores how Bitcoin might be forked before going into detail on the Ethereum network and cryptocurrencies running on top of the network, smart contracts, and more. The book introduces the Hyperledger foundation and the tools offered to create private blockchain solutions. For those willing, it investigates directed acyclic graphs (DAGs) and several of its implementations, which could solve several of the problems other blockchain networks are still dealing with to this day. In Chapter 4, readers can find an overview of blockchain networks that can be used to build solutions of their own and the tools that can help them in the process.
This book is a gentle but rigorous introduction to Formal Logic. It is intended primarily for use at the college level. However, it can also be used for advanced secondary school students, and it can be used at the start of graduate school for those who have not yet seen the material. The approach to teaching logic used here emerged from more than 20 years of teaching logic to students at Stanford University and from teaching logic to tens of thousands of others via online courses on the World Wide Web. The approach differs from that taken by other books in logic in two essential ways, one having to do with content, the other with form. Like many other books on logic, this one covers logical syntax and semantics and proof theory plus induction. However, unlike other books, this book begins with Herbrand semantics rather than the more traditional Tarskian semantics. This approach makes the material considerably easier for students to understand and leaves them with a deeper understanding of what logic is all about. In addition to this text, there are online exercises (with automated grading), online logic tools and applications, online videos of lectures, and an online forum for discussion. They are available at http://intrologic.stanford.edu/
This book is the first to present the state of the art and provide technical focus on the latest advances in the foundations of blockchain systems. It is a collaborative work between specialists in cryptography, distributed systems, formal languages, and economics, and addresses hot topics in blockchains from a theoretical perspective: cryptographic primitives, consensus, formalization of blockchain properties, game theory applied to blockchains, and economical issues. This book reflects the expertise of the various authors, and is intended to benefit researchers, students, and engineers who seek an understanding of the theoretical foundations of blockchains.
This book is one of the first technical overviews of autonomous vehicles written for a general computing and engineering audience. The authors share their practical experiences designing autonomous vehicle systems. These systems are complex, consisting of three major subsystems: (1) algorithms for localization, perception, and planning and control; (2) client systems, such as the robotics operating system and hardware platform; and (3) the cloud platform, which includes data storage, simulation, high-definition (HD) mapping, and deep learning model training. The algorithm subsystem extracts meaningful information from sensor raw data to understand its environment and make decisions as to its future actions. The client subsystem integrates these algorithms to meet real-time and reliability requirements. The cloud platform provides offline computing and storage capabilities for autonomous vehicles. Using the cloud platform, new algorithms can be tested so as to update the HD map—in addition to training better recognition, tracking, and decision models. Since the first edition of this book was released, many universities have adopted it in their autonomous driving classes, and the authors received many helpful comments and feedback from readers. Based on this, the second edition was improved by extending and rewriting multiple chapters and adding two commercial test case studies. In addition, a new section entitled “Teaching and Learning from this Book” was added to help instructors better utilize this book in their classes. The second edition captures the latest advances in autonomous driving and that it also presents usable real-world case studies to help readers better understand how to utilize their lessons in commercial autonomous driving projects. This book should be useful to students, researchers, and practitioners alike. Whether you are an undergraduate or a graduate student interested in autonomous driving, you will find herein a comprehensive overview of the whole autonomous vehicle technology stack. If you are an autonomous driving practitioner, the many practical techniques introduced in this book will be of interest to you. Researchers will also find extensive references for an effective, deeper exploration of the various technologies.
Search structures support the fundamental data storage primitives on key-value pairs: insert a pair, delete by key, search by key, and update the value associated with a key. Concurrent search structures are parallel algorithms to speed access to search structures on multicore and distributed servers. These sophisticated algorithms perform fine-grained synchronization between threads, making them notoriously difficult to design correctly. Indeed, bugs have been found both in actual implementations and in the designs proposed by experts in peer-reviewed publications. The rapid development and deployment of these concurrent algorithms has resulted in a rift between the algorithms that can be verified by the state-of-the-art techniques and those being developed and used today. The goal of this book is to show how to bridge this gap in order to bring the certified safety of formal verification to high-performance concurrent search structures. Similar techniques and frameworks can be applied to concurrent graph and network algorithms beyond search structures.
This book is an introduction to analytical performance modeling for computer systems, i.e., writing equations to describe their performance behavior. It is accessible to readers who have taken college-level courses in calculus and probability, networking, and operating systems. This is not a training manual for becoming an expert performance analyst. Rather, the objective is to help the reader construct simple models for analyzing and understanding the systems that they are interested in. Describing a complicated system abstractly with mathematical equations requires a careful choice of assumptions and approximations. They make the model tractable, but they must not remove essential characteristics of the system, nor introduce spurious properties. To help the reader understand the choices and their implications, this book discusses the analytical models for 40 research papers. These papers cover a broad range of topics: GPUs and disks, routers and crawling, databases and multimedia, worms and wireless, multicore and cloud, security and energy, etc. An appendix provides many questions for readers to exercise their understanding of the models in these papers.
This book is a gentle but rigorous introduction to formal logic. It is intended primarily for use at the college level. However, it can also be used for advanced secondary school students, and it can be used at the start of graduate school for those who have not yet seen the material. The approach to teaching logic used here emerged from more than 20 years of teaching logic to students at Stanford University and from teaching logic to tens of thousands of others via online courses on the World Wide Web. The approach differs from that taken by other books in logic in two essential ways, one having to do with content, the other with form. Like many other books on logic, this one covers logical syntax and semantics and proof theory plus induction. However, unlike other books, this book begins with Herbrand semantics rather than the more traditional Tarskian semantics. This approach makes the material considerably easier for students to understand and leaves them with a deeper understanding of what logic is all about. The primary content difference concerns the semantics of the logic that is taught. In addition to this text, there are online exercises (with automated grading), online logic tools and applications, online videos of lectures, and an online forum for discussion. They are available at logic.stanford.edu/intrologic/. Table of Contents: Introduction / Propositional Logic / Propositional Proofs / Propositional Resolution / Satisfiability / Herbrand Logic / Herbrand Logic Proofs / Resolution / Induction / First Order Logic
This book is an introduction to analytical performance modeling for computer systems, i.e., writing equations to describe their performance behavior. It is accessible to readers who have taken college-level courses in calculus and probability, networking and operating systems. This is not a training manual for becoming an expert performance analyst. Rather, the objective is to help the reader construct simple models for analyzing and understanding the systems that they are interested in.
This book constitutes the refereed proceedings of the 20th International Conference on DNA Computing and Molecular Programming, DNA 20, held in Kyoto, Japan, in September 2014. The 10 full papers presented were carefully selected from 55 submissions. The papers are organized in many disciplines (including mathematics, computer science, physics, chemistry, material science and biology) to address the analysis, design, and synthesis of information-based molecular systems.