In this talk, LLVMProject will present our OpenCL SDK and its core technology — the vectorizer compiler. Available for free download, the Intel OpenCL SDK 1.5 makes it easy for OpenCL developers to design, build, debug, and profile OpenCL applications running on the CPU device.
This paper presents a comprehensive performance comparison between CUDA and OpenCL. We have selected 16 benchmarks ranging from synthetic applications to real-world ones. We make an extensive analysis of the performance gaps taking into account programming models, optimization strategies, architectural details, and underlying compilers.
If you are not already familiar with OpenCL and why it matters, this AMD Whitepaper is a great introduction. This non-technical article explains what is OpenCL, why it is important, why an open approach is better than proprietary compute solutions, and then gives some examples of how and where OpenCL is being used.
In this paper, we have highlighted some of the benefits and limitations of early adoption of GPGPU for astronomy. While there are risks and significant effort may be required to prepare codes, in many cases the benefits will outweigh the limitations.
Here we describe a source-to-source translation tool, “Swan” for facilitating the conversion of an existing CUDA code to use the OpenCL model, as a means to aid programmers experienced with CUDA in evaluating OpenCL and alternative hardware.
This is “programmer’s introduction” where we cover the ideas behind OpenCL but also show how these ideas are translated into source code. We will do this through a series of progressively more challenging examples
The MulticoreWare tools framework drastically reduces the number of code versions and the time spent in Performance Optimization efforts, by providing key performance tracking and analysis tools coupled with micro-architecture optimized compile-time libraries.
A short presentation of GPU Systems and introduction to Libra Compute API – Technology Platform and Ecosystem with a technical hands-on “Hello World” tutorial from Libra SDK is presented.
ArrayFire, a freely-available GPU software library supporting CUDA and OpenCL devices. It supports C, C++, Fortran, and Python languages on AMD, Intel, and NVIDIA hardware