Designing Scientific Applications on GPUs (Hardcover)
暫譯: 在GPU上設計科學應用程序 (精裝版)
Raphael Couturier
- 出版商: CRC
- 出版日期: 2013-11-21
- 售價: $3,150
- 貴賓價: 9.5 折 $2,993
- 語言: 英文
- 頁數: 498
- 裝訂: Hardcover
- ISBN: 1466571624
- ISBN-13: 9781466571624
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相關分類:
GPU、Computer Graphics
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相關主題
商品描述
Many of today’s complex scientific applications now require a vast amount of computational power. General purpose graphics processing units (GPGPUs) enable researchers in a variety of fields to benefit from the computational power of all the cores available inside graphics cards.
Understand the Benefits of Using GPUs for Many Scientific Applications
Designing Scientific Applications on GPUs shows you how to use GPUs for applications in diverse scientific fields, from physics and mathematics to computer science. The book explains the methods necessary for designing or porting your scientific application on GPUs. It will improve your knowledge about image processing, numerical applications, methodology to design efficient applications, optimization methods, and much more.
Everything You Need to Design/Port Your Scientific Application on GPUs
The first part of the book introduces the GPUs and Nvidia’s CUDA programming model, currently the most widespread environment for designing GPU applications. The second part focuses on significant image processing applications on GPUs. The third part presents general methodologies for software development on GPUs and the fourth part describes the use of GPUs for addressing several optimization problems. The fifth part covers many numerical applications, including obstacle problems, fluid simulation, and atomic physics models. The last part illustrates agent-based simulations, pseudorandom number generation, and the solution of large sparse linear systems for integer factorization. Some of the codes presented in the book are available online.
商品描述(中文翻譯)
許多當今複雜的科學應用現在需要大量的計算能力。通用圖形處理單元(GPGPU)使各個領域的研究人員能夠利用顯示卡內所有核心的計算能力。
了解使用 GPU 進行許多科學應用的好處
《在 GPU 上設計科學應用》展示了如何在物理學、數學到計算機科學等多個科學領域中使用 GPU 進行應用。這本書解釋了在 GPU 上設計或移植科學應用所需的方法。它將增進您對影像處理、數值應用、設計高效應用的方法論、優化方法等的知識。
設計/移植您的科學應用到 GPU 所需的一切
本書的第一部分介紹了 GPU 及 Nvidia 的 CUDA 編程模型,這是目前設計 GPU 應用的最廣泛環境。第二部分專注於 GPU 上的重要影像處理應用。第三部分介紹了在 GPU 上進行軟體開發的一般方法論,第四部分描述了使用 GPU 解決幾個優化問題。第五部分涵蓋了許多數值應用,包括障礙問題、流體模擬和原子物理模型。最後一部分說明了基於代理的模擬、偽隨機數生成以及解決大型稀疏線性系統以進行整數因式分解的方案。本書中呈現的一些代碼可在線獲得。