Download Programming Massively Parallel Processors: A Hands-on by Wen-mei W. Hwu, David B. Kirk PDF

By Wen-mei W. Hwu, David B. Kirk

Multi-core processors are not any longer the way forward for computing-they are the current day fact. a standard heavily produced CPU gains a number of processor cores, whereas a GPU (Graphics Processing Unit) could have 1000's or maybe hundreds of thousands of cores. With the increase of multi-core architectures has come the necessity to educate complex programmers a brand new and crucial ability: the best way to software vastly parallel processors.

Programming vastly Parallel Processors: A Hands-on Approach exhibits either scholar alike the fundamental thoughts of parallel programming and GPU structure. quite a few options for developing parallel courses are explored intimately. Case reviews show the improvement approach, which starts off with computational considering and ends with potent and effective parallel programs.
* Teaches computational pondering and problem-solving concepts that facilitate high-performance parallel computing.
* makes use of CUDA (Compute Unified equipment Architecture), NVIDIA's software program improvement software created in particular for vastly parallel environments.
* exhibits you the way to accomplish either high-performance and high-reliability utilizing the CUDA programming version in addition to OpenCL.

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Additional info for Programming Massively Parallel Processors: A Hands-on Approach (Applications of GPU Computing Series)

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For each application, we begin by identifying alternative ways of formulating the basic structure of the parallel execution and follow up with reasoning about the advantages and disadvantages of each alternative. We then go through the steps of code transformation necessary to achieve high performance. These two chapters help the readers put all the materials from the previous chapters together and prepare for their own application development projects. Chapter 10 generalizes the parallel programming techniques into problem decomposition principles, algorithm strategies, and computational thinking.

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Steele, G. L. (1986). Data parallel algorithms. 7903). IEEE 754R Working Group. (2006). Standard for floating-point arithmetic P754 (Draft). pdf). Industrial Light and Magic. (2003). OpenEXR. com). Intel. (2007). Intel 64 and IA-32 Architectures optimization reference manual. Order No. 248966-016. Santa Clara, CA: Intel Corp. pdf). , & Rost, R. (2006). 20. Madison, AL: 3Dlabs, Inc. org/ documentation/specs/). , & Voorhies, D. (1990). The rendering architecture of the DN10000VS. Computer Graphics (SIGGRAPH 1990), 24(4), 299–307.

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