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Introduction to High Performance Computing for Scientists and Engineers (Computational Science)
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Introduction to High Performance Computing for Scientists and Engineers provides a solid introduction to current mainstream computer architecture, dominant parallel programming models, and useful optimization strategies for scientific HPC.
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- Written by high performance computing (HPC) experts, Introduction to High Performance Computing for Scientists and Engineers provides a solid introduction to current mainstream computer architecture, dominant parallel programming models, and useful optimization strategies for scientific HPC. From working in a scientific computing center, the authors gained a unique perspective on the requirements and attitudes of users as well as manufacturers of parallel computers.The text first introduces the architecture of modern cache-based microprocessors and discusses their inherent performance limitations, before describing general optimization strategies for serial code on cache-based architectures. It next covers shared- and distributed-memory parallel computer architectures and the most relevant network topologies. After discussing parallel computing on a theoretical level, the authors show how to avoid or ameliorate typical performance problems connected with OpenMP. They then present cache-coherent nonuniform memory access (ccNUMA) optimization techniques, examine distributed-memory parallel programming with message passing interface (MPI), and explain how to write efficient MPI code. The final chapter focuses on hybrid programming with MPI and OpenMP.Users of high performance computers often have no idea what factors limit time to solution and whether it makes sense to think about optimization at all. This book facilitates an intuitive understanding of performance limitations without relying on heavy computer science knowledge. It also prepares readers for studying more advanced literature.Read about the authors recent honor: Informatics Europe Curriculum Best Practices Award for Parallelism and Concurrency
| Publisher | CRC Press |
| Publication date | August 17, 2010 |
| Edition | 1st |
| Language | English |
| Print length | 330 pages |
| ISBN-10 | 143981192X |
| ISBN-13 | 978-1439811924 |
| Item Weight | 1.15 pounds (520 grams) |
| Dimensions | 6.14 x 0.82 x 9.21 inches (15.6 x 2.1 x 23.4 cm) |
| Part of series | Chapman & Hall/CRC Computational Science |
Who Should Buy?
-
Aspiring Researchers
Ideal for early-career researchers needing foundational knowledge in high-performance computing for scientific research applications.
-
University Students
Beneficial for undergraduate and graduate students studying computational science or related fields seeking practical HPC insights.
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Industry Professionals
Useful for engineers and scientists in industry looking to enhance their skills in high-performance computing applications.
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Complete Beginners
Not suitable for individuals with no prior experience in computing or programming, as it assumes some knowledge.
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Performance Optimization Editorial Review
The book 'Introduction to High Performance Computing for Scientists and Engineers' is an informative introduction book for those who want to understand the fundamentals of High-Performance Computing (HPC). The book covers several relevant aspects of HPC, including hardware, algorithm design, and parallel processing. The authors emphasize the importance of maximizing performance of serial programs before applying parallelization strategies, and each chapter has a set of questions that extend the concepts covered therein. The book provides a good overview of optimizing code for memory management and discusses the importance of a compiler in executing programs on the CPU. However, some reviewers found the book to be written in a dense style that uses a lot of jargon, making it difficult to follow. Others felt that the organization of the book could be improved, with some topics being spread across several chapters. The book primarily uses FORTRAN for most of the code examples, which some readers found unfortunate. However, it contains C++ code scattered here and there, which contains more problems than the FORTRAN code. In summary, 'Introduction to High Performance Computing for Scientists and Engineers' is a worthwhile read for anyone interested in the fundamentals of HPC. It is suitable for self-study and provides an overall understanding of HPC hardware, algorithms, and parallel processing. However, the writing style and organization, as well as the choice of language for code examples, may make it difficult for some readers to follow. **
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Pros
- Good overview of HPC fundamentals
- Emphasis on maximizing performance before applying parallelization
- Set of questions at the end of each chapter
- Covers relevant aspects of HPC
Cons
- Written in a dense style with a lot of jargon
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Features & Benefits
- Solid introduction to mainstream computer architecture
- Covers optimization strategies and parallel programming models
- Examines typical performance problems and how to avoid them
- Prepares readers for studying advanced literature
- Facilitates an intuitive understanding of performance limitations
- Written by experts in the field
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