CUDA Fortran for Scientists and Engineers: Best Practices for Efficient CUDA Fortran Programming (Paperback)
Gregory Ruetsch, Massimiliano Fatica
- 出版商: Morgan Kaufmann
- 出版日期: 2013-09-17
- 定價: $2,450
- 售價: 8.0 折 $1,960
- 語言: 英文
- 頁數: 338
- 裝訂: Paperback
- ISBN: 0124169708
- ISBN-13: 9780124169708
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相關分類:
CUDA、程式語言
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其他版本:
CUDA Fortran for Scientists and Engineers: Best Practices for Efficient CUDA Fortran Programming
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商品描述
CUDA Fortran for Scientists and Engineers shows how high-performance application developers can leverage the power of GPUs using Fortran, the familiar language of scientific computing and supercomputer performance benchmarking. The authors presume no prior parallel computing experience, and cover the basics along with best practices for efficient GPU computing using CUDA Fortran.
To help you add CUDA Fortran to existing Fortran codes, the book explains how to understand the target GPU architecture, identify computationally intensive parts of the code, and modify the code to manage the data and parallelism and optimize performance. All of this is done in Fortran, without having to rewrite in another language. Each concept is illustrated with actual examples so you can immediately evaluate the performance of your code in comparison.
- Leverage the power of GPU computing with PGI's CUDA Fortran compiler
- Gain insights from members of the CUDA Fortran language development team
- Includes multi-GPU programming in CUDA Fortran, covering both peer-to-peer and message passing interface (MPI) approaches
- Includes full source code for all the examples and several case studies
- Download source code and slides from the book's companion website
商品描述(中文翻譯)
《CUDA Fortran for Scientists and Engineers》展示了高性能應用開發人員如何利用Fortran這一熟悉的科學計算和超級計算性能基準語言,發揮GPU的強大能力。作者假設讀者沒有並行計算的經驗,並介紹了CUDA Fortran的基礎知識和高效GPU計算的最佳實踐。
為了幫助讀者將CUDA Fortran添加到現有的Fortran代碼中,本書解釋了如何理解目標GPU架構,識別代碼中的計算密集部分,並修改代碼以管理數據和並行性並優化性能。所有這些都是使用Fortran完成的,無需重寫成其他語言。每個概念都通過實際示例進行了說明,因此您可以立即比較代碼的性能。
本書還包括以下內容:
- 利用PGI的CUDA Fortran編譯器發揮GPU計算的能力
- 從CUDA Fortran語言開發團隊成員那裡獲得見解
- 包括CUDA Fortran中的多GPU編程,涵蓋點對點和消息傳遞接口(MPI)方法
- 提供所有示例和幾個案例研究的完整源代碼
- 從本書的附屬網站下載源代碼和投影片