Computer Systems: A Programmer's Perspective (3rd Edition)

这本书最打动人的，是它真的把'程序'和'系统'焊在了一起。它不满足于告诉你C语言的语法，而是逼你盯着指针去看寄存器、看内存布局、看汇编如何把`A[i]`翻译成`movl`——那种'原来如此'的通透感，是读完很多底层教材得不到的。作者用'掀开引擎盖'的方式，让应用程序员理解计算机各部件如何协同工作，从而写出更快的程序：从循环展开的CPE优化，到Web服务器用动态链接取代fork，每一步都贴着真实的性能取舍。它的广度也引发争议：前六章偏组原，后几章讲链接、OS、网络、并行却篇幅仓促，有人因此觉得'挺一般'。但正是这种'一览无余'的全局观，让它在众多只讲单点的书里独树一帜——适合愿意为debug到'智商被碾压'而付出、渴望真正看懂机器如何运转的读者。

Randal E. Bryant received his bachelor’s degree from the University of Michigan in 1973 and then attended graduate school at the Massachusetts Institute of Technology, receiving his PhD degree in computer science in 1981. He spent three years as an assistant professor at the California Institute of Technology, and has been on the faculty at Carnegie Mellon since 1984. For five of those years he served as head of the Computer Science Department, and for ten of them he served as Dean of the School of Computer Science. He is currently a university professor of computer science. He also holds a courtesy appointment with the Department of Electrical and Computer Engineering. Professor Bryant has taught courses in computer systems at both the undergraduate and graduate level for around 40 years. Over many years of teaching computer architecture courses, he began shifting the focus from how computers are designed to how programmers can write more efficient and reliable programs if they understand the system better. Together with Professor O’Hallaron, he developed the course 15-213, Introduction to Computer Systems, at Carnegie Mellon that is the basis for this book. He has also taught courses in algorithms, programming, computer networking, distributed systems, and VLSI design. Most of Professor Bryant’s research concerns the design of software tools to help software and hardware designers verify the correctness of their systems. These include several types of simulators, as well as formal verification tools that prove the correctness of a design using mathematical methods. He has published over 150 technical papers. His research results are used by major computer manufacturers, including Intel, IBM, Fujitsu, and Microsoft. He has won several major awards for his research. These include two inventor recognition awards and a technical achievement award from the Semiconductor Research Corporation, the Kanellakis Theory and Practice Award from the Association for Computer Machinery (ACM), and the W. R. G. Baker Award, the Emmanuel Piore Award, the Phil Kaufman Award, and the A. Richard Newton Award from the Institute of Electrical and Electronics Engineers (IEEE). He is a fellow of both the ACM and the IEEE and a member of both the US National Academy of Engineering and the American Academy of Arts and Sciences. David R. O’Hallaron is a professor of computer science and electrical and computer engineering at Carnegie Mellon University. He received his PhD from the University of Virginia. He served as the director of Intel Labs, Pittsburgh, from 2007 to 2010. He has taught computer systems courses at the undergraduate and graduate levels for 20 years on such topics as computer architecture, introductory computer systems, parallel processor design, and Internet services. Together with Professor Bryant, he developed the course at Carnegie Mellon that led to this book. In 2004, he was awarded the Herbert Simon Award for Teaching Excellence by the CMU School of Computer Science, an award for which the winner is chosen based on a poll of the students. Professor O’Hallaron works in the area of computer systems, with specific interests in software systems for scientific computing, data-intensive computing, and virtualization. The best-known example of his work is the Quake project, an endeavor involving a group of computer scientists, civil engineers, and seismologists who have developed the ability to predict the motion of the ground during strong earthquakes. In 2003, Professor O’Hallaron and the other members of the Quake team won the Gordon Bell Prize, the top international prize in high-performance computing. His current work focuses on the notion of autograding, that is, programs that evaluate the quality of other programs.