Book Image

OpenCL Programming by Example

Book Image

OpenCL Programming by Example

Overview of this book

Research in parallel programming has been a mainstream topic for a decade, and will continue to be so for many decades to come. Many parallel programming standards and frameworks exist, but only take into account one type of hardware architecture. Today computing platforms come with many heterogeneous devices. OpenCL provides royalty free standard to program heterogeneous hardware. This guide offers you a compact coverage of all the major topics of OpenCL programming. It explains optimization techniques and strategies in-depth, using illustrative examples and also provides case studies from diverse fields. Beginners and advanced application developers will find this book very useful. Beginning with the discussion of the OpenCL models, this book explores their architectural view, programming interfaces and primitives. It slowly demystifies the process of identifying the data and task parallelism in diverse algorithms. It presents examples from different domains to show how the problems within different domains can be solved more efficiently using OpenCL. You will learn about parallel sorting, histogram generation, JPEG compression, linear and parabolic regression and k-nearest neighborhood, a clustering algorithm in pattern recognition. Following on from this, optimization strategies are explained with matrix multiplication examples. You will also learn how to do an interoperation of OpenGL and OpenCL. "OpenCL Programming by Example" explains OpenCL in the simplest possible language, which beginners will find it easy to understand. Developers and programmers from different domains who want to achieve acceleration for their applications will find this book very useful.
Table of Contents (18 chapters)
OpenCL Programming by Example
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface
Index

Image histogram computation


In the previous chapter, we computed the RGB histogram of an input image on an OpenCL buffer object. In this chapter, we will discuss the same with input as an OpenCL image object. The input image is read into a contiguous buffer and an image object is created using the clCreateImage function. At the kernel side the pixel values can be sampled using read_image OpenCL built-in. The next diagram illustrates how an image is read and processed in the example code. The input image from the file system is read into a contiguous buffer, row wise as shown by step 1 in the diagram. The input image can be of any format BMP, PNG, or JPEG. The raw image pixel buffer is then used to create an OpenCL image object using the clCreateImage function. The CL_MEM_USE_HOST_PTR flag is passed. This is shown as step 2 in the diagram. Finally each kernel instance executes on the image buffer as shown by step 3.

Take a look at the following histogram_image_kernel OpenCL kernel. This kernel...