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

Execution model


The two main execution units in OpenCL are the kernels and the host program. The kernels execute on the so called OpenCL device and the host program runs on the host computer. The main purpose of the host program is to create and query the platform and device attributes, define a context for the kernels, build the kernel, and manage the execution of these kernels.

On submission of the kernel by the host to the device, an N dimensional index space is created. N is at least 1 and not greater than 3. Each kernel instance is created at each of the coordinates of this index space. This instance is called as the "work item" and the index space is called as the NDRange. In the following screenshot we have shown the three scenarios for 1, 2 and 3 dimensional NDRange:

OpenCL NDRange

In the saxpy example which we discussed in the previous chapter, we have taken a global size of 1024 and a local size of 64. Each work item computes the corresponding:

C[local id] = alpha* A[local id] + B...