The book was written in , when OpenCL was in transition from its infancy to maturity as a practical programming tool for solving real-life problems in science and engineering.
Earlier, the Khronos Group successfully defined OpenCL specifications, and several companies developed stable OpenCL implementations ready for learning and testing. At this time fall , one can install OpenCL on a heterogeneous computer and perform meaningful computing experiments. Since OpenCL is relatively new, there are not many experienced users or sources of practical information. One can find on the Web some helpful publications about OpenCL, but there is still a shortage of complete descriptions of the system suitable for students and potential users from the scientific and engineering application communities.
Chapter 1 provides short but realistic examples of codes using MPI and OpenMP in order for readers to compare these two mature and very successful systems with the fledgling OpenCL.
MPI used for programming clusters and OpenMP for shared memory computers, have achieved remarkable worldwide success for several reasons. Both have been designed by groups of parallel computing specialists that perfectly understood scientific and engineering applications and software development tools. Our experience indicates that it is possible to teach scientists or students whose disciplines are other than computer science how to use MPI and OpenMP in a several hours time. We hope that OpenCL will benefit from this experience and achieve, in the near future, a similar success.
Paraphrasing the wisdom of Albert Einstein, we need to simplify OpenCL as much as possible but not more. The reader should keep in mind that OpenCL will be evolving and that pioneer users always have to pay an additional price in terms of initially longer program development time and suboptimal performance before they gain experience.
The goal of achieving simplicity for OpenCL programming requires an additional comment. OpenCL supporting heterogeneous computing offers us opportunities to select diverse parallel processing devices manufactured by different vendors in order to achieve near-optimal or optimal performance.
This flexibility is welcomed by many users of HPC technology, but it has a price. Programming heterogeneous computers is somewhat more complicated than writing programs in conventional MPI and OpenMP.
We hope this gap will disappear as OpenCL matures and is universally used for solving large scientific and engineering problems.
Guest Access. Register Log in. As a guest user you are not logged in or recognized by your IP address. Ebook: Using OpenCL loading Chapter 1 describes briefly two older de facto standard and highly successful parallel programming systems: MPI and OpenMP. Collectively, the MPI, OpenMP, and OpenCL systems cover programming of all major parallel architectures: clusters, shared-memory computers, and the newest heterogeneous computers.
Chapter 2, the technical core of the book, deals with OpenCL fundamentals: programming, hardware, and the interaction between them. Chapter 3 adds important information about such advanced issues as double-versus-single arithmetic precision, efficiency, memory use, and debugging.
Chapters 2 and 3 contain several examples of code and one case study on genetic algorithms. These examples are related to linear algebra operations, which are very common in scientific, industrial, and business applications. This supplementary material will assist the reader in getting a quick start on OpenCL projects. Rate this item: 1. Please wait Recent source codes. See all packages.
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