The Libra 1.2 compute platform and ecosystem now supports a broad range of AMD and NVIDIA CPU & GPU compute devices, providing users a complete and dynamic cross-processor, cross-platform heterogeneous developer SDK & run-time environment. A Windows version is available for download.

• Support for the new Fermi architecture, with:
  • Native 64-bit GPU support
  • Multiple Copy Engine support
  • ECC reporting
  • Concurrent Kernel Execution
  • Fermi HW debugging support in cuda-gdb
  • Fermi HW profiling support for CUDA C and OpenCL in Visual Profiler
• C++ Class Inheritance and Template Inheritance support for increased programmer productivity
• A new unified interoperability API for Direct3D and OpenGL, with support for:
  • OpenGL texture interop
  • Direct3D 11 interop support
  • CUDA Driver / Runtime Buffer Interoperability, which allows applications using the CUDA Driver API to also use libraries implemented using the CUDA C Runtime such as CUFFT and CUBLAS.
• CUBLAS now supports all BLAS1, 2, and 3 routines including those for single and double precision complex numbers
• Up to 100x performance improvement while debugging applications with cuda-gdb
• cuda-gdb hardware debugging support for applications that use the CUDA Driver API
• cuda-gdb support for JIT-compiled kernels
• New CUDA Memory Checker reports misalignment and out of bounds errors, available as a stand-alone utility and debugging mode within cuda-gdb
• CUDA Toolkit libraries are now versioned, enabling applications to require a specific version, support multiple versions explicitly, etc.
• CUDA C/C++ kernels are now compiled to standard ELF format
• Support for device emulation mode has been packaged in a separate version of the CUDA C Runtime (CUDART), and is deprecated in this release. Now that more sophisticated hardware debugging tools are available and more are on the way, NVIDIA will be focusing on supporting these tools instead of the legacy device emulation functionality.
  • On Windows, use the new Parallel Nsight development environment for Visual Studio, with integrated GPU debugging and profiling tools (was code-named “Nexus”). Please see www.nvidia.com/nsight for details.
  • On Linux, use cuda-gdb and cuda-memcheck, and check out the solutions from Allinea and TotalView that will be available soon.
• Support for all the OpenCL features in the latest R195 production driver package:
  • Double Precision
  • Graphics Interoperability with OpenCL, Direc3D9, Direct3D10, and Direct3D11 for high performance visualization
  • Query for Compute Capability, so you can target optimizations for GPU architectures (cl_nv_device_attribute_query)
  • Ability to control compiler optimization settings via support for pragma unroll in OpenCL kernels and an extension that allows programmers to set compiler flags. (cl_nv_compiler_options)
  • OpenCL Images support, for better/faster image filtering
  • 32-bit global and local atomics for fast, convenient data manipulation
  • Byte Addressable Stores, for faster video/image processing and compression algorithms
  • Support for the latest OpenCL spec revision 1.0.48 and latest official Khronos OpenCL headers as of 2010-02-17

The toolkit, drivers, tools and documentation are available from http://developer.nvidia.com/object/cuda_3_0_downloads.html.

This blog entry by James Reinders from Intel describes the acquisition and future plans in more detail.

• Automatic cross-segment load-balancing for multidisplay installations
• Dynamic Frame Resolution (DFR) for constant-framerate rendering
• Compression Plugin API for runtime-loadable image compression engines

See the 0.9 release notes on the Equalizer website for a comprehensive list of new features, enhancements, optimizations and bug. A paperback Equalizer Programming and User Guide is available from Lulu.com. Commercial support, custom software development and porting services are available from Eyescale Software GmbH.

Additional new features in CUDA Toolkit 2.3 include:

• 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. (See the release notes for details, including changes to LD_LIBRARY_PATH on Linux)
• 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:
  • A new pitchLinearTexure code sample that shows how to efficiently texture from pitch linear memory.
  • A new PTXJIT code sample illustrating how to use cuModuleLoadDataEx() to load PTX source from memory instead of loading a file.
  • 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.
  • 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:
  • All memory transfer API calls are now reported
  • Support for profiling multiple contexts per GPU
  • Synchronized clocks for requested start time on the CPU and start/end times on the GPU for all kernel launches and memory transfers
  • 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:
  • MacOS X 10.5.6 and later (32-bit)
  • Windows XP/Vista/7 with Visual Studio 8 (VC2005 SP1) and 9 (VC2008)
  • Fedora 10, RHEL 4.7 & 5.3, SLED 10.2 & 11.0, OpenSUSE 11.1, and Ubuntu 8.10 & 9.04

Developers can download the latest CUDA Toolkit, SDK, and drivers now.

This paper explores the challenges in implementing a message passing interface usable on systems with data-parallel processors. As a case study, we design and implement the “DCGN” API on NVIDIA GPUs that is similar to MPI and allows full access to the underlying architecture. We introduce the notion of data-parallel thread-groups as a way to map resources to MPI ranks. We use a method that also allows the data-parallel processors to run autonomously from user-written CPU code. In order to facilitate communication, we use a sleep-based polling system to store and retrieve messages. Unlike previous systems, our method provides both performance and flexibility. By running a test suite of applications with different communication requirements, we find that a tolerable amount of overhead is incurred, somewhere between one and five percent depending on the application, and indicate the locations where this overhead accumulates. We conclude that with innovations in chipsets and drivers, this overhead will be mitigated and provide similar performance to typical CPU based MPI implementations while providing fully-dynamic communication.

(Jeff A. Stuart and John D. Owens, Message Passing on Data-Parallel Architectures, Proceedings of the 23rd IEEE International Parallel and Distributed Processing Symposium)

The CUDA Toolkit and SDK 2.1 beta includes support for VisualStudio 2008 support on Windows XP and Vista and Just-In-Time (JIT) compilation for applications that dynamically generate CUDA kernels. Several new interoperability APIs have been added for Direct3D 9 and Direct3D 10 that accelerate communication to DirectX applications as well as a series of improvements to OpenGL interoperability.

CUDA Toolkit and SDK 2.1 beta also features support for using a GPU that is not driving a display on Vista, a beta of Linux Profiler 1.1 (separate download) as well as support for recent releases of Linux including Fedora9, OpenSUSE 11 and Ubuntu 8.04.

CUDA Toolkit and SDK 2.1 beta is available today for free download from www.nvidia.com/object/cuda_get.