ofgpu v0.2 released: GPU linear solvers for OpenFOAM

September 24th, 2011

The latest release of Symscape’s ofgpu (v0.2) for OpenFOAM® 2.0.x is now available. ofgpu is an open source experimental linear solver library that targets NVIDIA CUDA GPU devices on Windows, Linux, and (untested) Mac OS X. ofgpu now has support for the Cusp preconditioners:

  • smoothed_aggregation – equivalent to Algebraic Multi-Grid (AMG)
  • scaled_bridson_ainv
  • bridson_ainv
  • nonsym_bridson_ainv

Also supported is the option to select the GPU device. For more details see http://www.symscape.com/gpu-0-2-openfoam.

Aparapi – Parallel programming with Java and OpenCL

September 15th, 2011

AMD just released to open source a project called Aparapi that started in their JavaLabs team. Aparapi is an API for expressing data parallel workloads in Java and a runtime component capable of converting the Java bytecode of compatible workloads into OpenCL™ so that it can be executed on a variety of GPU devices.  More information can be found in this blog entry.

Thrust: A Productivity-Oriented Library for CUDA

September 12th, 2011

Abstract:

This chapter demonstrates how to leverage the Thrust parallel template library to implement high-performance applications with minimal programming effort. Based on the C++ Standard Template Library (STL), Thrust brings a familiar high-level interface to the realm of GPU Computing while remaining fully interoperable with the rest of the CUDA software ecosystem. Applications written with Thrust are concise, readable, and efficient.

(Nathan Bell and Jared Hoberock: “Thrust: A Productivity-Oriented Library for CUDA”, GPU Computing Gems, Jade Edition, edited by Wen-mei W. Hwu, October 2011)

libCL 1.0 released

September 8th, 2011

libCL is an open-source parallel algorithm library written in C++ and OpenCL. Rather than a specific domain, libCL intends to encompass a wide range of parallel algorithms and data structures. The goal is to provide a comprehensive repository for high performance visual-centric computing ranging from fundamental primitives such as sorting, searching and algebra to advanced systems of algorithms for computational research and visualization. The current distribution of libCL already contains entirely parallelized implementations of the following algorithms:

  • Bounding volume hierarchy construction
  • Smoothed particle hydrodynamics
  • Radix sort
  • Adaptive tone-mapping
  • Screen-space ambient occlusion culling
  • Bilateral and Recursive Gaussian

libCL emerged out of OpenCL Studio, and as such integrates well with the development environment and its visualization capabilities. libCL is Open Source and released under the Apache license.

CUDPP 2.0: parallel hash tables, tridiagonal solver, parallel reductions, and double precision

August 8th, 2011

CUDPP release 2.0 is a major new release of the CUDA Data-Parallel Primitives Library, with exciting new features. The public interface has undergone a minor redesign to provide thread safety. Parallel reductions (cudppReduce) and a tridiagonal system solver (cudppTridiagonal) have been added, and a new component library, cudpp_hash, provides fast data-parallel hash table functionality. In addition, support for 64-bit data types (double as well as long long and unsigned long long) has been added to all CUDPP algorithms, and a variety of bugs have been fixed.  For a complete list of changes, see the change log. CUDPP 2.0 is available for download now.

Solving ordinary differential equations with CUDA

August 8th, 2011

Odeint is a high level C++ library for solving ordinary differential equations. It is released under an open-source license and supports a variety of different methods for solving ODEs. As a special feature it supports different algebras which perform the basic mathematical operations. This allows the user to solve ordinary differential equations on modern graphic cards. A Thrust interface is implemented, so that the power of CUDA can easily be employed. Furthermore, arbitrary precision types can easily be supported.  Read the rest of this entry »

GPU.NET v2.0 released

July 29th, 2011

TidePowerd has released Version 2 of their GPU computing solution for the .NET framework, GPU.NET. Their platform allows developers to quickly and easily write GPU-accelerated applications completely in .NET-based languages. Some key benefits include:

  • Stay in C# and treat kernel methods like any regular method
  • “Boilerplate” GPU programming tasks such as memory transfer and GPU scheduling are abstracted from the developer
  • Cross-platform and cross-hardware with a single binary
  • Systems seamlessly adapt to new hardware without rewriting code
  • Speed on par with native code

New version 2 features:

  • Visual Studio Error list and IntelliSense integration
  • On-device random number generation
  • Double precision support

A free 30-days evaluation license is available, as well as in-depth examples and tutorials.

Jacket v1.8 and LibJacket v1.1 released

July 24th, 2011

Jacket 1.8 and LibJacket 1.1 have been released by Accelereyes, enabling GPU support for MATLAB and easier CUDA development with C/C++/Fortran and Python.  New features include:

  • Expanded support for the Signal Processing, Image Processing, and Statistics Libraries included with both Jacket and LibJacket
  • Faster linear algebra for special systems (e.g. symmetric, positive definite, triangular, etc.)
  • Enhanced visualizations
  • New and updated examples: FDTD, Mandelbrot fractals, maximum-likelihood neural segmentation, MDS for genomics
  • Built with CUDA 4.0 for peak performance

Visit http://www.accelereyes.com/ for details, downloads, whitepapers and tutorials.

CUVI 0.5 Released

July 24th, 2011

TunaCode is pleased to announce the release of CUVI (CUDA Vision and Imaging Library) version 0.5 which comes with a new API and new features. This release makes it even simpler to add acceleration to existing Imaging applications, without any prior technical knowledge of GPUs. CUVI v0.5 is built from bottom up with performance and ease-of-use in mind.

CUVI version 0.5 is available for download at http://cuvilib.com and is available for Windows (Win32, x64) with planned support for Linux and Mac.

Proven Algorithmic Techniques for Manycore Processors Summer School

July 20th, 2011

The Virtual School of Computational Science and Engineering (VSCSE) will offer a hands-on course for graduate students August 15-19:

Proven Algorithmic Techniques for Manycore Processors

This course will be delivered to a number of sites nationwide—including the National Center for Supercomputing Applications at the University of Illinois at Urbana-Champaign—using high-definition video conferencing technologies. Students at all sites will be able to work with a cohort of fellow computational scientists, have access to local teaching assistants, and interact virtually with course instructors.

Registration for the weeklong course is $100. Please visit www.vscse.org for more information or hub.vscse.org to register.

Read the rest of this entry »

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