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"Virtually every computing system today is part of a distributed system. Programmers, developers, and engineers need to understand the underlying principles and paradigms as well as the real-world application of those principles. Now, internationally renowned expert Andrew S. Tanenbaum ? with colleague Martin van Steen ? presents a complete introduction that identifies the seven key principles of distributed systems, with extensive examples of each. Adds a completely new chapter on architecture to address the principle of organizing distributed systems. Provides extensive new material on peer-to-peer systems, grid computing and Web services, virtualization, and application-level multicasting. Updates material on clock synchronization, data-centric consistency, object-based distributed systems, and file systems and Web systems coordination. For all developers, software engineers, and architects who need an in-depth understanding of distributed systems."

"This best-selling guide to CUDA and GPU parallel programming has been revised with more parallel programming examples, commonly-used libraries, and explanations of the latest tools. With these improvements, the book retains its concise, intuitive, practical approach based on years of road-testing in the authors' own parallel computing courses. "Programming Massively Parallel Processors: A Hands-on Approach" shows both student and professional alike the basic concepts of parallel programming and GPU architecture. Various techniques for constructing parallel programs are explored in detail. Case studies demonstrate the development process, which begins with computational thinking and ends with effective and efficient parallel programs. Updates in this edition include: new coverage of CUDA 4.0, improved performance, enhanced development tools, increased hardware support, and more; increased coverage of related technology OpenCL and new material on algorithm patterns, GPU clusters, host programming, and data parallelism; and two new case studies explore the latest applications of CUDA and GPUs for scientific research and high-performance computing."

"Plagiarisme merupakan tindakan mengakui hasil karya orang lain sebagai hasil karya pribadi tanpa izin pemilik asli karya tersebut. Tindakan plagiarisme dalam bentuk dokumen sudah sangat banyak terjadi saat era digital seperti ini. Pada skripsi ini dibuat sistem pendeteksi plagiarisme otomatis pada karya tulis digital dwibahasa (Indonesia - Inggris) dengan bahasa Indonesia digunakan sebagai karya tulis yang akan diuji dan bahasa Inggris sebagai karya tulis referensinya. Sistem pendeteksi plagiarisme terdapat dua bagian penting, yaitu akurasi dan kecepatan yang dihasilkan oleh sistem. Pada skripsi ini dilakukan pengembangan terhadap sistem pendeteksi plagiarisme dengan menambahkan penerjemah Microsoft Translator API dan menerapkan similar word. Penerapan penerjemah Microsoft Translator API dapat meningkatkan akurasi yang cukup signifikan yaitu sebesar 14,93 % dibandingkan penerjemah Googletrans API dan penerapan similar word dapat meningkatkan akurasi sistem dari 0,24% hingga 15,37%. Parallel processing diterapkan untuk mengatasi permasalahan waktu eksekusi yang lama ketika jumlah dokumen referensi yang digunakan banyak. Hasil pengujian dengan menerapkan parallel processing dapat meningkatkan kecepatan 1,06 hingga 6,71 kali lebih cepat dari program yang berjalan secara serial.

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Plagiarism is the act of acknowledging the work of others personal work without their permissions. The prevalence of plagiarism is high in this digital era. In this thesis, an automatic plagiarism detection system on bilingual digital paper (Indonesian-English) is created with Indonesian paper as the tested paper and English paper as the reference paper. The plagiarism detection system has two important parts, namely the accuracy and speed produced by the system.

In this thesis, a plagiarism detection system is developed by adding a Microsoft Translator API translator and applying a similar word. The application of the Microsoft Translator API translator can increase the accuracy of the significant amount of 14.93% compared to the Googletrans API translator and the application of similar word can increase system accuracy from 0.24% to 15.37%. Parallel processing will be applied to overcome the problems of a long execution time when the number of reference documents that are used a lot. The test results by applying parallel processing can increase the speed of 1.06 to 6.71 times faster than programs running in serial."

"1. Introduction 2. History 3. Language Design Principles 4. Syntax 5. Basic Semantics 6. Data Types 7. Control I - Expressions and Statements 8. Control II- Procedures and Environments 9. Modules and Abstract Data 10. Object-Oriented Programming 11. Functional Programming 12. Logic Programming 13. Formal Semantics of Programming Languages 14. Parallel Programming "