Designing Scientific Applications on GPUs (Hardcover)

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.

現今許多複雜的科學應用程式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受益於圖形卡內所有核心的計算能力。

了解在許多科學應用中使用GPU的好處

《在GPU上設計科學應用程式》向您展示如何在不同科學領域中使用GPU進行應用，從物理學和數學到計算機科學。本書解釋了在GPU上設計或移植科學應用程式所需的方法。它將提升您對圖像處理、數值應用、設計高效應用程式的方法、優化方法等方面的知識。

擁有設計/移植科學應用程式所需的一切

本書的第一部分介紹了GPU和Nvidia的CUDA編程模型，目前是最廣泛使用的GPU應用程式設計環境。第二部分重點介紹了在GPU上進行重要的圖像處理應用。第三部分介紹了在GPU上進行軟體開發的一般方法。第四部分描述了使用GPU解決多個優化問題的方法。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。最後一部分介紹了基於代理的模擬、偽隨機數生成以及解決大型稀疏線性系統進行整數因數分解的方法。本書中提供的一些程式碼可在線上獲得。