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Computational Mathematics: Models, Methods, and Analysis with MATLAB® and MPI, Second Edition (Textbooks in Mathematics), by Robert E.
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Computational Mathematics: Models, Methods, and Analysis with MATLAB® and MPI is a unique book covering the concepts and techniques at the core of computational science. The author delivers a hands-on introduction to nonlinear, 2D, and 3D models; nonrectangular domains; systems of partial differential equations; and large algebraic problems requiring high-performance computing. The book shows how to apply a model, select a numerical method, implement computer simulations, and assess the ensuing results.
Providing a wealth of MATLAB, Fortran, and C++ code online for download, the Second Edition of this very popular text:
- Includes a new chapter with two sections on the finite element method, two sections on shallow water waves, and two sections on the driven cavity problem
- Introduces multiprocessor/multicore computers, parallel MATLAB, and message passing interface (MPI) in the chapter on high-performance computing
- Updates and adds code and documentation
Computational Mathematics: Models, Methods, and Analysis with MATLAB® and MPI, Second Edition is an ideal textbook for an undergraduate course taught to mathematics, computer science, and engineering students. By using code in practical ways, students take their first steps toward more sophisticated numerical modeling.
- Sales Rank: #149249 in Books
- Published on: 2015-11-17
- Original language: English
- Number of items: 1
- Dimensions: 9.30" h x 1.20" w x 6.20" l, .0 pounds
- Binding: Hardcover
- 500 pages
Most helpful customer reviews
2 of 2 people found the following review helpful.
Comparing First and Second Editions
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I've used the first edition of this volume for numerous discrete math and computational computing online classes, and have now gotten feedback from thousands of students. The first edition came in at 4 to 5 stars for my applications, and this review compares this new edition to the previous. There are several unique elements to this comparison that differ from others: 1. The first edition is still a wonderful and valuable asset, and is selling as such on Amazon, with prices HIGHER for used than this new edition in some cases! So the frequent publisher rip off of creating "new" with minimal changes just to make students pay more does not apply at all in this case at this writing. 2. "New" also applies to fields with rapid changes that require extensive updates for research. In this case, the field goes back to the 1980's in computation (and 1950 in math) with $15 Dover editions that cover the basics very well, especially general numerical methods. The main "fast moving" aspect of the field is software, parallel processing and specific application examples, and both editions' true value have been, since 2003, in the very specific code examples in extremely detailed example applications, both research and applied.
Other reviews of the previous edition knocked the format as too specific and difficult for a first undergrad numerical methods class. The reason for this IMHO after using it for more specialized classes is that if you are covering parallel processing carefully, you NEED PDE systems (my handle on wiki is pdecalculus to show my bias) or you'll be TOO general and not able to give as many applied examples as these fine texts do, especially in the key, hot field of parallel.To quote Gehring and Ramme, "Hundreds of papers have been written about scheduling models in parallel systems, however, there is a huge discrepancy in what is studied and what can be applied." Job Scheduling Strategies for Parallel Processing: 18th International Workshop, JSSPP 2014, Phoenix, AZ, USA, May 23, 2014. Revised Selected Papers (Lecture Notes in Computer Science) p. 72 in Hawaii conference, et al in Phoenix.
Given that discrepancy, this is NOT a good text in either edition as a vast and general overview of numerical methods, but both are IDEAL texts if your objective is total immersion in a LOT of code (Matlab, GNU Octave, Domain specific parallel problems, etc.) with UNIQUE and FUN practical examples throughout the 500 pages, albeit focused on PDE systems and parallel.
The first edition was outstanding for online resources, and this second is even better. With a C++ compiler, if you are an autodidact, you don't need an expensive Matlab license to take advantage of the plethora of "wash on wash off" coding exercises and examples, and the resulting graphics and solutions are stunning. Some examples obviously are intended for supercomputing environments, and Coursera has been kind enough to allow hundreds of my students access even after finishing a course. Even without it, a good solid PC can handle 90% of the examples, as the authors did not assume that all students would be in supercomputing environments, and the online resources are generous with hints and solutions. All in all, given current pricing and the many new developments in parallel architectures, I strongly recommend this edition over the first, which is unusual since I like saving students money. In this case the new edition does both.
Final point: this is intended for undergrads, but the emphasis on PDEs puts it more as a specialized course for Seniors or grad students. You don't HAVE to be a math major, but if you're getting into computational computing, or especially careers in the hottest area of computing (parallel embedded), this information is a MUST today. It is NOT easy material, and autodidacts, if not strong in PDEs, will need a tutor to help them along.
Highly Recommended. Note: I get quantity discounts from publishers for students, but paid full price for both editions of my own copies here on Amazon, and did not solicit or accept review copies, for the sake of objectivity.
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