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

Implementing image filters


An image filter is a mathematical operation on the original image that transforms it to the filtered image. The goal of the mathematical operation is to perform a mathematical computation for a pixel, based on the values of the neighboring pixels. A precisely defined image filter is a function that transforms each pixel of the original image to pixels of the filtered image. Consider a simple example—what would one do if he or she wants to decrease the brightness of an image?

In an image with gray scale representation, each pixel would contain one integer representing intensity. Deduct some positive integer say VALUE from all the pixels and if some integer becomes negative then truncate the result to zero. This is referred to as the mathematical operation which is applied to every pixel in the original image. This function would transform the image into one that is the same as the original image, but with lower brightness. Similarly adding a constant value to all...