The CUDA Toolkit and SDK v2.3 are now released and available to all developers.
A brief overview of features--there are a lot:
* The CUFFT Library now supports double-precision transforms and includes significant performance improvements for single-precision transforms as well. See the CUDA Toolkit release notes for details.
* The CUDA-GDB hardware debugger and CUDA Visual Profiler are now included in the CUDA Toolkit installer, and the CUDA-GDB debugger is now available for all supported Linux distros. (see below)
* Each GPU in an SLI group is now enumerated individually, so compute applications can now take advantage of multi-GPU performance even when SLI is enabled for graphics.
* The 64-bit versions of the CUDA Toolkit now support compiling 32-bit applications. Please note that the installation location of the libraries has changed, so developers on 64-bit Linux must update their LD_LIBRARY_PATH to contain either /usr/local/cuda/lib or /usr/local/cuda/lib64.
* New support for fp16 <-> fp32 conversion intrinsics allows storage of data in fp16 format with computation in fp32. Use of fp16 format is ideal for applications that require higher numerical range than 16-bit integer but less precision than fp32 and reduces memory space and bandwidth consumption.
* The CUDA SDK has been updated to include:
o A new pitchLinearTexure code sample that shows how to efficiently texture from pitch linear memory.
o A new PTXJIT code sample illustrating how to use cuModuleLoadDataEx() to load PTX source from memory instead of loading a file.
o Two new code samples for Windows, showing how to use the NVCUVID library to decode MPEG-2, VC-1, and H.264 content and pass frames to OpenGL or Direct3D for display.
o Updated code samples showing how to properly align CUDA kernel function parameters so the same code works on both x32 and x64 systems.
* The Visual Profiler includes several enhancements:
o All memory transfer API calls are now reported
o Support for profiling multiple contexts per GPU
o Synchronized clocks for requested start time on the CPU and start/end times on the GPU for all kernel launches and memory transfers
o Global memory load and store efficiency metrics for GPUs with compute capability 1.2 and higher
* The CUDA Driver for MacOS is now packaged separately from the CUDA Toolkit.
* Support for major Linux distros, MacOS X, and Windows:
o MacOS X 10.5.6 and later (32-bit)
o Windows XP/Vista/7 with Visual Studio 8 (VC2005 SP1) and 9 (VC2008)
o Fedora 10, RHEL 4.7 & 5.3, SLED 10.2 & 11.0, OpenSUSE 11.1, and Ubuntu 8.10 & 9.04
the Mandelbrot sample now requires compute capabilities 1.1 (as opposed to CUDA 2.2 sample)