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2014剑桥大学出版新书：加速MATLAB计算的1001个小技巧
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Accelerating MATLAB Performance: 1001 Tips to Speed Up MATLAB Programs The MATLAB® programming environment is often perceived as a platform suitable for prototyping and modeling but not for actual real-life applications. One of the reasons that I constantly hear when consulting with clients is that “MATLAB is slow”. This book aims to help reduce this perception and shows that MATLAB programs can in fact be made to run extremely fast, in a wide variety of different ways. MathWorks, who develop MATLAB, invests a significant amount of R&D effort in constantly improving MATLAB’s performance and advocating best practices for improved performance.1 Postings for performance-related R&D jobs are periodically posted2 and the engine’s performance improves with almost every semi-annual MATLAB release. In fact, the same MATLAB programs that might have been slow 10 or more years ago may now be blazingly fast when run using the latest MATLAB release, on the very same platform. Using programming techniques presented in this book, MATLAB applications can be made even faster, fast enough for most uses. This enables significant reduction of the development time and cost, since we can use MATLAB from end to end, from prototyping to deployment, without having to maintain a mirror code–base using a different programming language and environment. So, the perception of MATLAB as a slow environment may at least partly be due to a combination of factors, ranging from negative experience from past releases, to application code that does not follow good programming practices. Contents at a Glance Preface............................................................................................................................................xix Author...........................................................................................................................................xxv 1. Introduction to Performance Tuning...................................................................................1 2. Profiling MATLAB® Performance.....................................................................................25 3. Standard Performance-Tuning Techniques.....................................................................59 4. MATLAB®-Specific Techniques.......................................................................................135 6. Explicit Parallelization Using MathWorks Toolboxes.................................................285 7. Explicit Parallelization by Other Means........................................................................353 8. Using Compiled Code.........................................................................................................389 9. Memory-Related Techniques............................................................................................459 10. Graphics and GUI................................................................................................................525 11. I/O Techniques.....................................................................................................................593 Appendix A: Additional Resources........................................................................................631 Appendix B: Performance Tuning Checklist........................................................................643 References and Notes.................................................................................................................645 |
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2014-12-21 10:45:50, 144.77 M
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