Unused Kernel Optimization: In CUDA 11.5, unused kernel pruning was introduced with the potential benefits of reducing binary size and improving performance through more efficient optimizations.You can find documentation for these instructions in the PTX ISA guide: BMSK and SZEXT. New instructions in public PTX: New instructions for bit mask creation - BMSK and sign extension - SZEXT are added to the public PTX ISA.A future CUDA release will have the Nsight Visual Studio installer with VS2022 support integrated into it. A separate Nsight Visual Studio installer 2022.1.1 must be downloaded from here. VS2022 Support: CUDA 11.6 officially supports the latest VS2022 as host compiler.Large CPU page support for UVM managed memory.Added L2 cache control descriptors for atomics.Added new NVML public APIs for querying functionality under Wayland.Added ability to disable NULL kernel graph node launches.The host-side compiler must support the _int128 type to use this feature.
#NVIDIA CUDA TOOLKIT WINDOWS 10 FULL#
Full release of 128-bit integer (_int128) data type including compiler and developer tools support.A corresponding API, cudaGraphNodeGetEnabled(), allows querying the enabled state of a node. Support is limited to kernel nodes in this release. Added a new API, cudaGraphNodeSetEnabled(), to allow disabling nodes in an instantiated graph.Parallel Nsight 2.0 now available for Windows developers with new debugging and profiling features.GPU binary disassembler for Fermi architecture (cuobjdump).C++ debugging in CUDA-GDB for Linux and MacOS.Automated Performance Analysis in Visual Profiler.GPUDirect v2.0 support for Peer-to-Peer Communication.Layered Textures for working with same size/format textures at larger sizes and higher performance.Nvidia Performance Primitives (NPP) library for image/video processing.Thrust library of templated performance primitives such as sort, reduce, etc.C++ new/delete and support for virtual functions.No-copy pinning of system memory, a faster alternative to cudaMallocHost().Use all GPUs in the system concurrently from a single host thread.