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Introduction to High Performance Scientific Computing, by Victor Eijkhout
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This is a textbook that teaches the bridging topics between numerical analysis, parallel computing, code performance, large scale applications.
- Sales Rank: #611148 in Books
- Published on: 2015-12-28
- Released on: 2015-12-28
- Original language: English
- Number of items: 1
- Dimensions: 11.00" h x 1.21" w x 8.50" l,
- Binding: Paperback
- 534 pages
Most helpful customer reviews
6 of 6 people found the following review helpful.
Amazing Volume, Don't let the Creative Commons Attribution or On Demand Print Fool You...
By Let's Compare Options Preptorial
This is not a text to be read, but to be studied, referenced, cherished. Eijkhout is truly the rarest of creatures-- a present day polymath. There is simply NO way a single text or author can cover the entire field of scientific supercomputing in a single text, and yet this is the closest I've found in reviewing and teaching from dozens of texts.
To begin your journey of astonishment, when first seeing that this is a creative commons book (and freely available as a pdf online), you might mistake it for, heaven forbid, one of those hack commons books that are a copy of Wiki articles. DO NOT MAKE THAT MISTAKE! This text is perhaps the finest single collection of HPC/Supercomputing information on the planet, when you consider the online additions, code and amazing amount of references, both books and articles.
Also don't be fooled by the word "Introduction." This is clearly a graduate level supercomputing text, unless you're a top Senior undergrad specializing in HPC at MIT. Because there is simply no way to cover all the modern applications of HPC, from defense and cryptography to weather, fusion, molecular modeling and astrophysics, there also is no way to completely cover all the computational underpinnings of those applications, from numerical modeling to parallel computing, architecture, software, chips, compilers, numerical linear algebra and a career long school of hard knocks practical summary of performance optimization tricks and traps. So, the author gives brief "snippet" summaries of each topic, assuming you know the notation of advanced matrix algebra, eigenvalues, Frobenius norms, difference stencils and other advanced topics in HPC and computational mathematics. The text "teaches" these topics by giving fast, practical examples, online code, and then a wealth of references and bibs, so do not expect deep coverage of each topic, and do not expect it to be "introductory" if you're rusty in partial differential equations, complexity theory (both arithmetic and memory), or advanced linear algebra.
This is clearly a practice/skill oriented text that both strikes a balance between theory and research and provides a wonderful cookbook of ideas for practical problem solving when NP hard problems need to be reduced to polynomial time, not just with code or software, but with deep knowledge of processor and circuit architecture also. I teach an online class in supercomputing, mostly to graduate Engineers, and this text resonates most with those who have either worked in a top HPC environment, or built their own GPU based platforms. Although the author has to sacrifice depth for breadth in 500 pages, you get enough of each topic to explore it in depth with other references. For example, the couple pages on vector processors give enough of a "taste" to find the three books and 14 most current (as of 2016) articles on the topic, but won't "teach" you vector processing as I'm sure you would guess.
I'm a budget oriented teacher, but I also highly recommend you buy this text, not just get the online PDF, both to reward the publisher and author (the book is self published, on-demand, and kept up to date as is the pdf), and have a tool at hand that is much easier to use in print than as a pdf. DO get the pdf and online code and examples of course, but this is one where the print copy is a MUST due to density, and complemented by the online code, which you can copy and paste into your system for experimentation and practice. I'm rarely this enthusiastic about a single (incomparable) text, so need to say that I have nothing to do with the author or publisher, and my students pay full price for this text when they use it in my classes, nor have I solicited or received samples, although I do use the free online materials and version extensively. Highly recommended.
0 of 4 people found the following review helpful.
Manufacture quality is awful, content great
By Amazon Customer
I haven't deeply read the book, and it looks that content is great, actually it's the first book for HPC that I see that takes this approach (scientific applications, how to manage precision, etc) and that for me it's amazing.
But I give to it just two starts because the manufacture quality of the book is awful, nasty, a clone book would look better!
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