Computer Architecture,
Edition 7 A Quantitative ApproachEditors: By John L. Hennessy, David A. Patterson and Christos Kozyrakis
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Computer Architecture: A Quantitative Approach, has been considered essential reading by instructors, students and practitioners of computer design for nearly 30 years. The seventh edition of this classic textbook from John Hennessy and David Patterson, winners of the 2017 ACM A.M. Turing Award recognizing contributions of lasting and major technical importance to the computing field, along with new author Christos Kozyrakis, is fully revised with the latest developments in processor and system architecture.
True to its original mission of demystifying computer architecture, this edition continues the longstanding tradition of focusing on areas where the most exciting computing innovation is happening, while always keeping an emphasis on good engineering design.
Key Features
- Winner of a 2019 Textbook Excellence Award (Texty) from the Textbook and Academic Authors Association
- Each chapter follows a consistent framework: explanation of the ideas in each chapter; a "crosscutting issues" section, which presents how the concepts covered in one chapter connect with those given in other chapters; a "putting it all together" section that links these concepts by discussing how they are applied in real machine; and detailed examples of misunderstandings and architectural traps commonly encountered by developers and architects
- Includes "Putting It All Together" sections near the end of every chapter, providing real-world technology examples that demonstrate the principles covered in each chapter
- Covers new developments in GPU and CPU architectures, as well as domain specific architectures
- Features more comprehensive coverage of systems on chip and heterogeneity
About the author
By John L. Hennessy, Departments of Electrical Engineering and Computer Science, Stanford University, USA; David A. Patterson, Pardee Professor of Computer Science, Emeritus, University of California at Berkeley, USA and Christos Kozyrakis, Departments of Electrical Engineering and Computer Science, Stanford University, Stanford, CA
1. Fundamentals of Quantitative Design and Analysis
2. Memory Hierarchy Design
3. Instruction-Level Parallelism and Its Exploitation
4. Data-Level Parallelism in Vector, SIMD, and GPU Architectures
5. Thread-Level Parallelism
6. Warehouse-Scale Systems for Utility Computing
7. Domain-Specific Architectures
A. Instruction Set Principles
B. Review of Memory Hierarchy
C. Pipelining: Basic and Intermediate Concepts
Online
D. Storage Systems
E. Embedded Systems
F. Interconnection Networks
G. Vector Processors
H. Hardware and Software for VLIW and EPIC
I. Large-Scale Multiprocessors and Scientific Applications
J. Computer Arithmetic
K. Survey of Instruction Set Architectures
L. Advanced Concepts on Address Translation
M. Historical Perspectives and References