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Give your students a state-of-the-art approach to algorithms available only in Miller/Boxer's ALGORITHMS SEQUENTIAL AND PARALLEL: A UNIFIED APPROACH, 3E. This unique and functional text provides an introduction to algorithms and paradigms for modern computing systems, integrating the study of parallel and sequential algorithms within a focused presentation targeted at a one-semester course. This book prepares students to design, analyze, and implement algorithms for modern computing systems. This edition includes definitions and algorithms for a variety of state-of-the-art computing systems, including clouds, GPGPUs, grids, clusters, and networks of workstations. A wide range of practical exercises and engaging examples drawn from fundamental application domains enable students to develop the analytical and problem solving skills they need to design and implement efficient algorithms for current and future computing systems. ALGORITHMS SEQUENTIAL AND PARALLEL: A UNIFIED APPROACH, 3E also offers instructor support material in order to provide students with a solid background in both sequential and parallel modes of computation.
- ADDITIONAL TIME-TESTED EXAMPLES PROMPT READER ENTHUSIASM. Abundant, memorable examples throughout this edition clearly illustrate difficult concepts and demonstrate the applications of parallel algorithms within an exciting, accurate representation of today's scientific and engineering environment. These class-tested examples are proven to further learning and enthusiasm in today's students.
- DEFINITIONS AND ALGORITHMS FOR MULTICORE- AND GPGPU-BASED SYSTEMS KEEP YOUR COURSE ON THE CUTTING EDGE. The book's coverage of multiple processor systems with interconnects (multicore) and GPGPU systems functioning as traditional SIMD systems specifically reflects the latest modern technology with terminology, pertinent examples, and corresponding end-of-chapter questions to ensure your course remains on the leading edge.
- INCREASED EMPHASIS ON MODELS OF MULTIPROCESSOR/MULTI-CORE COMPUTING MORE CLOSELY REFLECT TODAY'S ACTUAL WORKING ENVIRONMENT. This edition places additional emphasis on models of modern computing to balance theoretical abstractions with practical concepts students can apply in the real world.
- MATHEMATICAL PROOFS NOW APPEAR IN APPENDICES TO CLARIFY BOOK'S PRESENTATION. Based on input from users, the authors have relocated several optional mathematical proofs that require advanced mathematical skills to the appendices, ensuring a clear presentation throughout the book.
- ONE-OF-A-KIND, CONTEMPORARY APPROACH INTEGRATES TREATMENT OF SEQUENTIAL AND PARALLEL ALGORITHMS. To prepare students to develop efficient software for today's multiprocessor computers, this unique book provides an integrated approach to the presentation of sequential and parallel algorithms and paradigms.
- LENGTH IS IDEAL FOR SINGLE-SEMESTER UNDERGRADUATE OR GRADUATE STUDY OF ALGORITHMS. Rather than adopting an encyclopedic approach to sequential algorithms, this text concentrates on key sequential and parallel algorithms with a focused brevity that is ideal for a thorough, yet manageable, one-semester course.
- EMPHASIS ON PRACTICAL APPLICATIONS PREPARES READERS TO UTILIZE SKILLS. This book thoroughly explores practical applications of algorithms as the authors present efficient methods for solving critical problems in computational geometry, image processing, graph theory, and scientific computing.
- EARLY EMPHASIS ON KEY MATHEMATICAL SKILLS AND TOOLS PREPARES READERS FOR SUCCESS THROUGHOUT THE COURSE. The authors intentionally develop and focus on mathematical tools throughout early chapters to ensure the solid foundation undergraduate and graduate students need for future endeavors.
1. Asymptotic Analysis.
2. Induction and Recursion.
3. The Master Method.
4. Models of Computation.
5. Combinational Circuits.
6. Matrix Operations.
7. Parallel Prefix.
8. Pointer Jumping.
10. Computational Geometry.
11. Image Processing.
12. Graph Algorithms.
13. Numerical Problems.
Appendix 1: Proof of Mathematical Induction.
Appendix 2: Proof of Master Theorem.
Appendix 3: Proof of Expected Running Time of Quicksort.
Appendix 4: Expected-Case Running Time of Quicksort.
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