The NVIDIA CUDA Toolkit 4.1 RC2 is now available for anyone to download. The key features of this release are:

• A new LLVM based compiler
• Over 1000 additional image processing function in the NPP library
• A Visual profiler

There is also a new version of Parallel Nsight 2.1 RC2 with support for CUDA 4.1. To download and to find out more follow: http://bit.ly/sRpQvr

Libra SDK is a sophisticated runtime including API, sample programs and documentation for massively accelerating software computations. This introduction tutorial provides an overview and usage examples of the powerful Libra API & math libraries executing on x86/x64, OpenCL, OpenGL and CUDA technology. Libra API enables generic and portable CPU/GPU computing within software development without the need to create multiple, specific and optimized code paths to support x86, OpenCL, OpenGL or CUDA devices. Link to PDF: www.gpusystems.com/doc/LibraGenericComputing.pdf

KOAP, pronounced “cope,” is a tool for developing OpenCL applications. It’s purpose is to allow the programmer to aggregate and simplify calls to the OpenCL API. KOAP accepts as input a file containing (or including) both the OpenCL program and the host C program. KOAP understands several directives, each of which is prefixed with a $ character. When KOAP is run, these directives are replaced with the requisite OpenCL API calls. Programs preprocessed by KOAP can run on any target supported by OpenCL, including both NVIDIA and AMD GPUs.

KOAP is now freely available as a source code tar file from http://aggregate.org/KOAP/.

Support for several types of compression has been added to the GPU-based database engine ålenkå . Supported algorithms include FOR (frame of reference), FOR-DELTA and dictionary compression. All compression algorithms run on the GPU achieving gigabytes per second compression and decompression speed. The use of compression allows to significantly reduce or eliminate I/O bottlenecks in analytical queries as shown by ålenkå’s results in the Star Schema and TPC-H benchmarks.

ClusterChimps.org has released a step by step guide to integrating CUDA with GNU Autotools. The guide covers building stand alone CUDA binaries, static CUDA libraries, shared CUDA libraries and comes with an example tarball. For more information go to http://www.clusterchimps.org/autotools.php

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.

Exposure Render is a Direct Volume Rendering Application that applies progressive Monte Carlo raytracing, coupled with physically based light transport to heterogeneous volumetric data. Exposure Render enables the configuration of any number of arbitrarily shaped area lights, models a real-world camera, including its lens and aperture, and incorporates complex materials, whilst still maintaining interactive display updates. It features both surface and volumetric scattering, and applies noise reduction to remove the unwanted startup noise associated with progressive Monte Carlo rendering. The complete implementation is available in source and binary forms under a permissive free software license.

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.

OCLTools is a powerful, yet compact, suite of Open Source tools that provide OpenCL developers with more alternatives to kernel compilation. OCLTools enables developers to eliminate costly kernel compilation time from the runtime of your application. With OCLTools developers can embed the source code of their kernels (clear text or encrypted) directly into their program binaries, eliminating the need to distribute kernel source code in the open while still maintaining the flexibility of runtime compilation. Both source code and precompiled binaries can be embedded into OpenCL binaries, effectively eliminating the additional kernel compilation overhead from the run time of your application.

For more information go to http://www.clusterchimps.org

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.