I saw this from CNN: http://money.cnn.com/news/newsfeeds/articles/marketwire/0559840.htm
Rich Standards-Based Tools and Libraries Develop Around CUDA Architecture
…
CUDA Toolkit 3.0 Beta: With the CUDA Toolkit 3.0 Beta, developers can start developing applications today for the NVIDIA Fermi architecture. This beta release includes features such as ECC reporting, Dual DMA Engine, Concurrent Kernel Execution and NVIDIA Fermi HW debugging support in cuda-gdb. Performance profiling is included for both CUDA Visual Profiler and the OpenCL Visual Profiler. Also included is support for a new unified interoperability API for Direct3D and OpenGL including Direct3D 11.
OpenCL 1.0 Extensions: NVIDIA is the only vendor supporting OpenCL features beyond the minimum conformance level. New extensions released by NVIDIA include support for double precision, OpenGL interoperability and the new OpenCL Installable Client Device (ICD). These new features supplement existing NVIDIA-only support for 2D image, 32-bit atomics and byte addressable stores.
NVIDIA “Nexus,” the codename for the industry’s first development environment for massively parallel GPU applications, integrated into Microsoft Visual Studio IDE: Comprised of a Debugger, Performance Analyzer and Graphics Inspector, this beta release gives GPU Computing developers an immediate boost in productivity through common and easy to use tools.
The Portland Group (PGI) — CUDA Fortran: Production release of the world’s first Fortran compiler compatible with the NVIDIA CUDA-enabled GPUs. CUDA Fortran will accelerate the adoption of GPU Computing in areas where applications are written in Fortran, such as ocean modeling, weather forecasting, environmental modeling, seismic analysis, bioinformatics and other areas.
Professional HPC Debugging Solutions from Allinea and TotalView were also launched this week. These tools provide CUDA GPU features that complement existing capabilities for parallel debugging using MPI, OpenMP and pthreads on the Linux platform. It enables developers to debug applications that are running on hybrid clusters of x86-64 CPUs and Tesla GPU-based servers.
Numerical Analysis Packages: Significant advances in the use of CUDA-enabled GPUs have also been made in prominent numerical analysis and mathematical modeling packages such as MATLAB from Mathworks, Mathematica from Wolfram Research and LabVIEW from National Instruments.
CUDA Libraries: In addition, developers can take advantage of a rich set of CUDA-accelerated libraries available from NVIDIA and its partners including BLAS, FFT, LAPACK (EM Photonics CULA), MAGMA (ICL at the UTK), NVIDIA Performance Primitives (NPP), CUDA Vision Workbench (CVWB) and video and image processing libraries.
…