Aaftab Munshi，OpenCL核心設計小組的靈魂人物之一，同時他也是OpenCL、OpenGL ES 1.1、OpenGL ES 2.0規範的編輯，與Dan Ginsburg和Dave Shreiner閤著瞭《OpenGL ES 2.0 Programming Guide》。目前他任職於Apple公司。

Benedict R. Gaster，資深軟件架構師，他的主要工作是為下一代異構處理器開發編程模型，具體工作是在包含CPU和加速器的新興處理器（如GPU）上探索並行編程的高層抽象。他為OpenCL的設計做齣瞭巨大貢獻，在Khronos Group開放標準協會中他是AMD的代錶。由於他在可擴展記錄和變量的類型係統方麵成績卓著，因而獲得瞭計算機科學的博士學位。

Timothy G. Mattson，資深並行編程專傢，從20世紀80年代中期開始從事相關工作，一直持續到現在。在此期間，他使用過各種類型的並行計算機（矢量超級計算機、SMP、VLIW、NUMA、MPP、集群和多核處理器）。1993年加入Intel公司，專注於OpenCL相關技術的研究。他還是一位資深的技術作傢，參與撰寫瞭《Patterns for Parallel Programming》、《An Introduction to Concurrency in Programming Languages》等經典著作。他因自己在分子分散理論方麵的工作獲得化學博士學位。

James Fung，NVIDIA資深技術工程師，專注於圖形硬件上的計算機視覺和圖像處理的研究，已經從圖形發展到通用計算，經驗十分豐富。擁有多倫多大學的電子與計算機工程博士學位，在並行GPU計算機視覺和介導現實領域發錶過多篇IEEE和ACM論文。

Dan Ginsburg，資深OpenGL和OpenCL專傢，曾經在AMD工作8年，是AMD技術部的高級成員，承擔過多種工作，包括開發OpenGL驅動程序、創建桌麵和手持3D演示應用，以及領導手持GPU開發工具的開發。他還曾在Still River Systems工作，為Monarch 250質子束放射綫治療係統開發GPU加速圖像注冊軟件。目前在Boston兒童醫院的新生兒神經影像和開發科學中心擔任首席軟件架構師，緻力於使用OpenCL來提高神經影像算法的速度。他擁有Worcester Polytechnic學院的計算機科學學士學位和Bentley大學的MBA學位。

Using the new OpenCL (Open Computing Language) standard, you can write applications that access all available programming resources: CPUs, GPUs, and other processors such as DSPs and the Cell/B.E. processor. Already implemented by Apple, AMD, Intel, IBM, NVIDIA, and other leaders, OpenCL has outstanding potential for PCs, servers, handheld/embedded devices, high performance computing, and even cloud systems. This is the first comprehensive, authoritative, and practical guide to OpenCL 1.1 specifically for working developers and software architects. Written by five leading OpenCL authorities, OpenCL Programming Guide covers the entire specification. It reviews key use cases, shows how OpenCL can express a wide range of parallel algorithms, and offers complete reference material on both the API and OpenCL C programming language. Through complete case studies and downloadable code examples, the authors show how to write complex parallel programs that decompose workloads across many different devices. They also present all the essentials of OpenCL software performance optimization, including probing and adapting to hardware. Coverage includes * Understanding OpenCL's architecture, concepts, terminology, goals, and rationale * Programming with OpenCL C and the runtime API * Using buffers, sub-buffers, images, samplers, and events * Sharing and synchronizing data with OpenGL and Microsoft's Direct3D * Simplifying development with the C++ Wrapper API * Using OpenCL Embedded Profiles to support devices ranging from cellphones to supercomputer nodes * Case studies dealing with physics simulation; image and signal processing, such as image histograms, edge detection filters, Fast Fourier Transforms, and optical flow; math libraries, such as matrix multiplication and high-performance sparse matrix multiplication; and more