Accelerating MATLAB with GPU Computing : A Primer with Examples (Paperback)

Jung W. Suh, Youngmin Kim

  • 出版商: Morgan Kaufmann
  • 出版日期: 2013-12-02
  • 售價: $2,380
  • 貴賓價: 9.5$2,261
  • 語言: 英文
  • 頁數: 258
  • 裝訂: Paperback
  • ISBN: 0124080804
  • ISBN-13: 9780124080805
  • 相關分類: GPUMatlab
  • 立即出貨 (庫存=1)

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商品描述

Beyond simulation and algorithm development, many developers increasingly use MATLAB even for product deployment in computationally heavy fields. This often demands that MATLAB codes run faster by leveraging the distributed parallelism of Graphics Processing Units (GPUs). While MATLAB successfully provides high-level functions as a simulation tool for rapid prototyping, the underlying details and knowledge needed for utilizing GPUs make MATLAB users hesitate to step into it. Accelerating MATLAB with GPUs offers a primer on bridging this gap.

Starting with the basics, setting up MATLAB for CUDA (in Windows, Linux and Mac OS X) and profiling, it then guides users through advanced topics such as CUDA libraries. The authors share their experience developing algorithms using MATLAB, C++ and GPUs for huge datasets, modifying MATLAB codes to better utilize the computational power of GPUs, and integrating them into commercial software products.  Throughout the book, they demonstrate many example codes that can be used as templates of C-MEX and CUDA codes for readers' projects.  Download example codes from the publisher's website: http://booksite.elsevier.com/9780124080805/

  • Shows how to accelerate MATLAB codes through the GPU for parallel processing, with minimal hardware knowledge
  • Explains the related background on hardware, architecture and programming for ease of use
  • Provides simple worked examples of MATLAB and CUDA C codes as well as templates that can be reused in real-world projects

商品描述(中文翻譯)

除了模擬和算法開發之外,許多開發人員在計算密集型領域中,越來越多地使用MATLAB來部署產品。這通常要求MATLAB代碼通過利用圖形處理單元(GPU)的分佈式並行處理來運行更快。儘管MATLAB成功地提供了高級功能作為快速原型設計的仿真工具,但利用GPU的底層細節和知識使MATLAB用戶猶豫不前。《加速MATLAB與GPU》提供了一個橋樑,幫助用戶填補這一差距。

從基礎知識開始,設置MATLAB用於CUDA(在Windows、Linux和Mac OS X中)和性能分析,然後引導用戶進入高級主題,如CUDA庫。作者們分享了他們使用MATLAB、C++和GPU開發用於處理大型數據集的算法的經驗,修改MATLAB代碼以更好地利用GPU的計算能力,並將它們集成到商業軟件產品中。在整本書中,他們展示了許多示例代碼,可以作為讀者項目的C-MEX和CUDA代碼的模板。從出版商的網站上下載示例代碼:http://booksite.elsevier.com/9780124080805/

本書展示了如何通過GPU進行並行處理來加速MATLAB代碼,並且只需最少的硬件知識。它解釋了有關硬件、架構和編程的相關背景,以便使用起來更加容易。它提供了MATLAB和CUDA C代碼的簡單實例以及可以在實際項目中重複使用的模板。