OpenCL Training Course in Calgary, AB – May 26, 2015

April 13th, 2015

Acceleware’s next OpenCL course takes place in Calgary. This professional four day course is designed for programmers who are looking to develop comprehensive skills in writing and optimizing applications that fully leverage data parallel processing capabilities of GPUs. Register before May 12 if you would like to reserve a spot. To find out what the course includes visit:
Learn OpenCL in Calgary      www.acceleware.com

PARALUTION Release 1.0

April 13th, 2015

PARALUTION is a library for sparse iterative methods which can be performed on various parallel devices, including multi-core CPU, GPU (CUDA and OpenCL) and Intel Xeon Phi.

The 1.0 version of the PARALUTION Library supports multi-node and multi-GPU configuration via MPI. All iterative solvers support global operations (i.e. distributed matrices and vectors) and all preconditioners can be used in a block-Jacobi fashion locally on each node/GPU. In addition, the software provides a global (fully distributed) Pair-Wise AMG solver. Read the rest of this entry »

C Framework for OpenCL v2.0.0 Now Available

February 11th, 2015

After four pre-releases, the stable 2.0.0 version of cf4ocl, the C Framework for OpenCL, is now available.

Since the last beta release, a number of tests were added, and a few bug fixes have been fixed. Support for device fission and native kernels has also been implemented. A complete list of features and fixes is available at https://github.com/FakenMC/cf4ocl/releases.

Cf4ocl has been tested on Linux, OS X and Windows, and offers a pure C object-oriented framework for developing and benchmarking OpenCL projects in C. It aims to:

1. Promote the rapid development of OpenCL host programs in C (with support for C++) and avoid the tedious and error-prone boilerplate code usually required. Read the rest of this entry »

Boost.Compute v0.4 Released

December 27th, 2014

Boost.Compute is an open-source, header-only C++ library for GPGPU and parallel-computing based on OpenCL. It provides a low-level C++ wrapper over OpenCL and high-level STL-like API with containers and algorithms for the GPU. Boost.Compute is available on GitHub and its documentation can be found here. See the full announcement here: http://kylelutz.blogspot.com/2014/12/boost-compute-0.4-released.html

PARALUTION v0.8.0 released

November 14th, 2014

PARALUTION is a library for sparse iterative methods which can be performed on various parallel devices, including multi-core CPU, GPU (CUDA and OpenCL) and Intel Xeon Phi. The new 0.8.0 release provides the following extra features:

  • Complex support
  • TNS, Variable preconditioner
  • BiCGStab(l), QMRCGStab, FCG solvers
  • RS and PairWise AMG
  • SIRA eigenvalue solver
  • Replace/Extract column/row functions
  • Stencil computation

For details, visit http://www.paralution.com.

Cf4ocl Brings Object-Oriented API to OpenCL C API

October 22nd, 2014

The Cf4ocl project is a GPLv3/LGPLv3 initiative to provide an object-oriented interface to the OpenCL C API with integrated profiling, promoting the rapid development of OpenCL host programs and avoiding boilerplate code. Its main goal is to allow developers to focus on OpenCL device code. After two alpha releases, the first beta is out, and can be tested on Linux, Windows and OS X. The framework is independent of the OpenCL platform version and vendor, and includes utilities to simplify the analysis of the OpenCL environment and of kernel requirements. While the project is making progress, it doesn’t yet offer OpenGL/DirectX interoperability, support for sub-devices, and doesn’t support pipes and SVM.

Cf4ocl can be downloaded from http://fakenmc.github.io/cf4ocl/.

Release of OpenCLIPP 2.0: an OpenCL library for computer vision and image processing

October 16th, 2014

Version 2.0 of OpenCLIPP, an Open Source OpenCL library for computer vision and image processing primitives, bas been released. For more information about the library, for programming contributions and for download, please refer to the OpenCLIPP Website.

Webinar Sep. 17: An Introduction to OpenCL using AMD GPUs

September 12th, 2014

This tutorial will begin with a brief overview of OpenCL and data-parallelism before focusing on the GPU programming model. We will explore the fundamentals of GPU kernels, host and device responsibilities, OpenCL syntax and work-item hierarchy. For more information and to register visit: http://acceleware.com/event/introduction-opencl-using-amd-gpus

New book: Numerical Computations with GPUs

July 22nd, 2014

A new book titled “Numerical Computations with GPUs” has been published:

This book brings together research on numerical methods adapted for Graphics Processing Units (GPUs). It explains recent efforts to adapt classic numerical methods, including solution of linear equations and FFT, for massively parallel GPU architectures. This volume consolidates recent research and adaptations, covering widely used methods that are at the core of many scientific and engineering computations. Each chapter is written by authors working on a specific group of methods; these leading experts provide mathematical background, parallel algorithms and implementation details leading to reusable, adaptable and scalable code fragments. This book also serves as a GPU implementation manual for many numerical algorithms, sharing tips on GPUs that can increase application efficiency. The valuable insights into parallelization strategies for GPUs are supplemented by ready-to-use code fragments. Numerical Computations with GPUs targets professionals and researchers working in high performance computing and GPU programming. Advanced-level students focused on computer science and mathematics will also find this book useful as secondary text book or reference.

From the table of contents: Read the rest of this entry »

Boost.Compute v0.3 Released

July 21st, 2014

Boost.Compute is a header-only C++ library for GPGPU and parallel-computing based on OpenCL. It provides a low-level C++ wrapper over OpenCL and high-level STL-like API with containers and algorithms for the GPU. It is available on GitHub and instructions for getting started can be found in the documentation. See the full announcement here: http://kylelutz.blogspot.com/2014/07/boost-compute-v0.3-released.html

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