--- product_id: 3723049 title: "Programming Massively Parallel Processors: A Hands-on Approach" brand: "david b. kirkwen-mei w. hwu" price: "₹ 16314" currency: INR in_stock: true reviews_count: 12 url: https://www.desertcart.in/products/3723049-programming-massively-parallel-processors-a-hands-on-approach store_origin: IN region: India --- # Programming Massively Parallel Processors: A Hands-on Approach **Brand:** david b. kirkwen-mei w. hwu **Price:** ₹ 16314 **Availability:** ✅ In Stock ## Quick Answers - **What is this?** Programming Massively Parallel Processors: A Hands-on Approach by david b. kirkwen-mei w. hwu - **How much does it cost?** ₹ 16314 with free shipping - **Is it available?** Yes, in stock and ready to ship - **Where can I buy it?** [www.desertcart.in](https://www.desertcart.in/products/3723049-programming-massively-parallel-processors-a-hands-on-approach) ## Best For - david b. kirkwen-mei w. hwu enthusiasts ## Why This Product - Trusted david b. kirkwen-mei w. hwu brand quality - Free international shipping included - Worldwide delivery with tracking - 15-day hassle-free returns ## Description Programming Massively Parallel Processors: A Hands-on Approach ## Images ![Programming Massively Parallel Processors: A Hands-on Approach - Image 1](https://m.media-amazon.com/images/I/81zQoajz6xL.jpg) ## Customer Reviews ### ⭐⭐⭐⭐⭐ 5.0 out of 5 stars Very useful *by R***T on Reviewed in the United States on December 24, 2019* Very good book ### ⭐⭐⭐⭐ 4.0 out of 5 stars Much to like, some minuses in the review *by G***E on Reviewed in the United States on June 17, 2013* Although not evident from the title, this book is mainly about CUDA, NVIDIA's method for programming their GPUs, but the title is perhaps justified by the existence of chapters on half a dozen or so other packages for programming GPUs, including an important one on using GPUs on MPI lusters. Most of the examples are in C, but with a chapter on FORTRAN. As other reviewers have already mentioned, the book is either excessively wordy or wonderfully detailed, depending on your mode of learning. For me, it was too wordy: there were sometimes two or three pages to explain an algorithm that was immediately clear from the figure. I would add that the authors have a curious view of what readers might know or not know: they give a long explanation of IEEE floating-point formats, which I believe are well known among application programmers, but mention only in passing with no explanation such less well known concepts as atomic operations and Amdahl's law. Various generations of NVIDIA chips are mentioned by code names that are probably not familiar to those of us who just buy a graphics card, although an appendix at the end gives some details. All in all, I found this a very useful introduction to CUDA, and especially to problems of memory access management on GPU boards, which I knew nothing about beforehand. Nonetheless, it was clear that one would need access to the detailed library manuals and spec sheets for the particular chip one was using before undertaking a real coding project, as there seem to be rather significant differences between chips in how one might try to maximize efficient use of the multiple execution units, memory blocks, and different cache sizes on the different chips. I expect that to have life beyond the current generation of chips, an application would need to query the system for these properties and optimize accordingly at run time. The book has some hints on how to do this. ### ⭐⭐⭐ 3.0 out of 5 stars Sloppy, sad, and salvageable *by M***L on Reviewed in the United States on September 20, 2014* So much effort went into writing this text, but better guidance was needed. True, there are typos as many have said, but not as many as I find in most textbooks and research papers.Before I get started, I have one strong compliment for the text: exercises at the ends of the chapters, where they appear, are very well thought out and get right to the point.The worst part of this book is its index, which gets an unnegotiable F grade from me. So much is missing. Try looking for the gridDim built-in variable; it's not there. blockDim is, but not gridDim. Or look up "constant memory"; that's not there under "memory", "constant", or otherwise. In fact although most of parallel programming is about overcoming memory bottlenecks, the index doesn't say much about memory in general. Indexing books is very hard and is usually left to professional indexers; there really is such a trade. But for this book the authors needed to pay more attention to the end product.The overall arrangement is illogical, starting from an enormous abstraction and then adding detail. Better to begin with something small and concrete which can be understood, and build up.At several points a non-programmer was permitted to do the typing, which is like allowing a pilot to fly while waking out of general anesthesia. See Figure 10.4 at lines 1 and 5.Many concepts are never brought together in some kind of summary that one would ever turn to as a reference, such as special variables. One can also find seeming conflicts that need clarification, such as Table 5.1's "local" memory for automatic array variables that are "stored into the global memory" on the next page. Both turn out to be true, but the presentation is not ideal.References are sloppily missing in certain cases, such as ELLPACK on page 224.At several points the text completely derails with outrageous metaphors. For instance page 85, where the authors try to explain standard queries of an implementation's capabilities by informing us that "most American hotel rooms come with hair dryers". The illustration's purpose is to publish a thicker book that looks "more valuable", but the truth is that any programmer who read to page 85 knows that most libraries have functions for querying their parameters and limits. There's no need to digress into toothpaste in Asia.If you must take a course that is based on this text, things get worse for you: the authors made presentation slides, and you bear the risk that your instructor may use them in the classroom. These are not well thought out from either a clarity or instructional standpoint, and they are very cluttered with confusing details. One example is how tiled matrix multiplication is explained; one slide actually draws three 4x4 matrices with row, column, and matrix name (!!!) labels in every single cell, giving the poor class 3 x (4 x 4) x 3 = 144 extra trivialities to distract them on that slide alone.Another pedagogical problem with their slide example, which the book also mishandles, is that they've chosen to illustrate the use of submatrices by dividing a 4 x 4 problem into a 2 x 2 problem. Although this is the smallest case they could select, the difficulty is that the human brain comprehends these 2 x 2 divisions in terms of "corners" (top left, etc.) instead of columns and rows. The examples should have been 9 x 9 divided into 3 x 3.In fairness, Kirk and Hwu did not have the best of resources available to assemble this book from. nVIDIA's "CUDA C Programming Guide" has no index whatsoever, and the table of contents doesn't seem to have much to do with what one is trying to find a second time. There's a reason nVIDIA doesn't sell print copies of that text on Amazon; people would review it. --- ## Why Shop on Desertcart? - 🛒 **Trusted by 1.3+ Million Shoppers** — Serving international shoppers since 2016 - 🌍 **Shop Globally** — Access 737+ million products across 21 categories - 💰 **No Hidden Fees** — All customs, duties, and taxes included in the price - 🔄 **15-Day Free Returns** — Hassle-free returns (30 days for PRO members) - 🔒 **Secure Payments** — Trusted payment options with buyer protection - ⭐ **TrustPilot Rated 4.5/5** — Based on 8,000+ happy customer reviews **Shop now:** [https://www.desertcart.in/products/3723049-programming-massively-parallel-processors-a-hands-on-approach](https://www.desertcart.in/products/3723049-programming-massively-parallel-processors-a-hands-on-approach) --- *Product available on Desertcart India* *Store origin: IN* *Last updated: 2026-05-18*