NVIDIA Performance Primitives (NPP) libraryĬUDA Toolkit for RedHat Enterprise Linux 5.3ĬUDA Toolkit for RedHat Enterprise Linux 4. Support for the latest OpenCL spec revision 1.0.48 and latest official Khronos OpenCL headers as of.Byte Addressable Stores, for faster video/image processing and compression algorithms.32-bit global and local atomics for fast, convenient data manipulation. OpenCL Images support, for better/faster image filtering.Ability to control compiler optimization settings via support for pragma unroll in OpenCL kernels and an extension that allows programmers to set compiler flags.Query for Compute Capability, so you can target optimizations for GPU architectures (cl_nv_device_attribute_query).Graphics Interoperability with OpenCL, Direc3D9, Direct3D10, and Direct3D11 for high performance visualization.Support for all the OpenCL features in the latest R195 production driver package:.On Linux, use cuda-gdb and cuda-memcheck, and check out the solutions from Allinea and TotalView that will be available soon.On Windows, use the new Parallel Nsight development environment for Visual Studio, with integrated GPU debugging and profiling tools (was code-named 'Nexus').In the window that pops up, click on More Info. Right-click on the image file and click on Get Info. 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 your Mac To find the dimensions of an image you have stored on a Mac (running macOS Mojave), follow these steps: Open the Finder application and locate your image. Support for device emulation mode has been packaged in a separate version of the CUDA C Runtime (CUDART), and is deprecated in this release.CUDA C/C++ kernels are now compiled to standard ELF format.CUDA Toolkit libraries are now versioned, enabling applications to require a specific version, support multiple versions explicitly, etc.New CUDA Memory Checker reports misalignment and out of bounds errors, available as a stand-alone utility and debugging mode within cuda-gdb.cuda-gdb support for JIT-compiled kernels.cuda-gdb hardware debugging support for applications that use the CUDA Driver API.Up to 100x performance improvement while debugging applications with cuda-gdb.CUBLAS now supports all BLAS1, 2, and 3 routines including those for single and double precision complex numbers.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.A new unified interoperability API for Direct3D and OpenGL, with support for:.C++ Class Inheritance and Template Inheritance support for increased programmer productivity.Fermi HW profiling support for CUDA C and OpenCL in Visual Profiler.Innovative grouping features allow for easy structuring of larger projects. Non-destructive Boolean operations: Create detailed, editable vector graphics by combining simple shapes. Support for the new Fermi architecture, with: Combine vector and bitmap graphics for stunning effects such as glossy surfaces, depth-of-field, and bokeh effects.
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