GPGPU » Tag: Libraries :: GPGPU.org

ViennaCL 1.2.0 released

dom — Mon, 02 Jan 2012 09:51:24 +0000

Version 1.2.0 of the OpenCL-based C++ linear algebra library ViennaCL is now available for download! It features a high-level interface compatible with Boost.ublas, which allows for compact code and high productivity. Highlights of the new release are the following features (all experimental):

Several algebraic multigrid preconditioners
Sparse approximate inverse preconditioners
Fast Fourier transform
Structured dense matrices (circulant, Hankel, Toeplitz, Vandermonde)
Reordering algorithms (Cuthill-McKee, Gibbs-Poole-Stockmeyer)
Proxies for manipulating subvectors and submatrices

The features are expected to reach maturity in the 1.2.x branch. More information about the library including download links is available at http://viennacl.sourceforge.net.

FortranCL: An OpenCL interface for Fortran 90

dom — Fri, 30 Dec 2011 08:55:20 +0000

FortranCL is an interface to OpenCL from Fortran90 programs, and it is distributed under the LGPL free software license. It allows Fortran programmer to directly execute code on GPUs or other massively parallel processors. The interface is designed to be as close to the C OpenCL interface as possible, and it is written in native Fortran 90 with type checking. FortranCL is not complete yet, but it includes enough subroutines to write GPU accelerated code in Fortran. More information: http://code.google.com/p/fortrancl/

GPU Virtualization for Dynamic GPU Provisioning

dom — Fri, 18 Nov 2011 08:23:53 +0000

From a recent press release:

Taipei, November 18, 2011: Zillians, a leading cloud solution provider specializing in high performance computing, GPU virtualization middleware and massive multi-player online game (MMOG) platforms today announced the availability of vGPU – the world’s first commercial virtualization solution for decoupling GPU hardware from software. Traditionally, physical GPUs must reside on the same machine running GPU code. This severely hampers GPU cloud deployment due to the difficulty of dynamic GPU provisioning. With vGPU technology, bulky hardware is no longer a limiting factor. vGPU introduces a thin, transparent RPC layer between local application and remote GPU, enabling existing GPU software to run without any modification on a remote GPU resource.

Utilizing Mellanox Technologies InfiniBand RDMA I/O solutions and NVDIA GPUDirect technology, Zillians vGPU achieved peak data transfer rates between application and GPU hardware. This opens the door to a broader range of GPU applications that can take advantage of virtualized GPU resources, and also a boon for service providers or cloud operators looking to deploy next generation cloud services based on scalable GPU and Infiniband technologies. As interest in GPU-based HPC clusters continues to grow, vGPU represents a critical enabler for systems to realize resource sharing and improve system utilization across a variety of application domains.

“We are excited to collaborate with Zillians to provide new capabilities for high-performance and massive multi-player online gaming cloud platforms,” said Gilad Shainer, Senior Director, Market Development at Mellanox Technologies. “Mellanox InfiniBand I/O solutions with native RDMA support and GPU acceleration provide the essential technology for Zillians’ innovative vGPU solution.”

Availability

Zillians vGPU is now available for early evaluation request. Version 1.0 featuring support for NVIDIA CUDA 4.0 runtime and driver APIs will be released by the end of 2011. Version 2.0 featuring further support for OpenCL 1.1 is scheduled for release in 2012 Q1. To learn more, please visit www.zillians.com/vgpu.

CULA Sparse Now Available

dom — Thu, 10 Nov 2011 09:09:48 +0000

EM Photonics has released CULA Sparse, a ready-to-integrate package for solving sparse linear systems. Features include:

Interfaces: C, C++, Fortran, Matlab, Python
Platforms: all CUDA platforms. including Linux, Windows, and OS X
Solvers and preconditioners: BiCG, BiCGStab, CG, GMRES, MINRES and Jacobi, ILU(0)
Data formats: COO, CSR, CSC in double precision real and complex floating point
No CUDA programming experience required.

More information is available at http://www.culatools.com/sparse.

rCUDA 3.1 Released

dom — Thu, 20 Oct 2011 10:49:26 +0000

The new version 3.1 of rCUDA (Remote CUDA), the Open Source package that allows performing CUDA calls to remote GPUs, is now available. Release highlights:

Fully updated API to CUDA 4.0 (added support for modules “Peer Device Memory Access” and “Unified Addressing”).
Fixed low level Surface Reference management functions.

For further information, please visit the rCUDA webpage at http://www.gap.upv.es/rCUDA.

Thrust: A Productivity-Oriented Library for CUDA

dom — Mon, 12 Sep 2011 08:01:56 +0000

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)

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

Mark Harris — Tue, 09 Aug 2011 03:07:13 +0000

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.

Jacket v1.8 and LibJacket v1.1 released

dom — Sun, 24 Jul 2011 22:14:51 +0000

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

dom — Sun, 24 Jul 2011 22:11:29 +0000

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.

rCUDA 3.0a released

dom — Mon, 18 Jul 2011 00:02:13 +0000

A new alpha release of rCUDA 3.0 (Remote CUDA), the Open Source package that allows performing CUDA calls to remote GPUs, has been released. Major improvements included in this new version are:

Partially updated API to 4.0
Added compatibility support with CUDA 4.0 environment
Updated CUBLAS API to 4.0 for the most common CUBLAS routines
Fixed some bugs
General performance improvements

For further information, please visit the rCUDA webpage.