Features:

  • C/C++ compiler
  • Visual Profiler
  • GPU-accelerated BLAS library
  • GPU-accelerated FFT library
  • GPU-accelerated Sparse Matrix library
  • GPU-accelerated RNG library
  • Additional tools and documentation

Highlights:

  • Easier Application Porting
    • Share GPUs across multiple threads
    • Use all GPUs in the system concurrently from a single host thread
    • No-copy pinning of system memory, a faster alternative to cudaMallocHost()
    • C++ new/delete and support for virtual functions
    • Support for inline PTX assembly
    • Thrust library of templated performance primitives such as sort, reduce, etc.
    • Nvidia Performance Primitives (NPP) library for image/video processing
    • Layered Textures for working with same size/format textures at larger sizes and higher performance
  • Faster Multi-GPU Programming
    • Unified Virtual Addressing
    • GPUDirect v2.0 support for Peer-to-Peer Communication
  • New & Improved Developer Tools
    • Automated Performance Analysis in Visual Profiler
    • C++ debugging in CUDA-GDB for Linux and MacOS
    • GPU binary disassembler for Fermi architecture (cuobjdump)
    • Parallel Nsight 2.0 now available for Windows developers with new debugging and profiling features.

What's New:

CUDA 9 is the most powerful software platform for GPU-accelerated applications. It has been built for Volta GPUs and includes faster GPU-accelerated libraries, a new programming model for flexible thread management, and improvements to the compiler and developer tools. With CUDA 9 you can speed up your applications while making them more scalable and robust.

Release Highlights

  • Up to 5X faster libraries with optimizations and heuristics
  • Powerful thread management with cooperative groups
  • Up to 1.5X faster HPC apps with Volta GPUs, NVLINK and HBM2

Libraries

  • Speed up high performance computing (HPC) and deep learning apps with new GEMM kernels in cuBLAS
  • Execute image and signal processing apps faster with performance optimizations across multiple GPU configurations in cuFFT and NVIDIA Performance Primitives
  • Solve linear and graph analytics problems common in HPC with new algorithms in cuSOLVER and nvGRAPH

Cooperative Groups

  • Express rich parallel algorithms with threads from sub-tiles to warps, blocks and grids
  • Manage and reuse threads efficiently within an application with new API and function primitives
  • Replace warp-synchronous programming with robust programming model on Kepler architecture and above

Volta Architecture

  • Execute AI applications faster with Tensor Cores performing 5X faster than Pascal GPUs
  • Scale multi-GPU applications with next generation NVLink delivering 2X throughput of prior generation
  • Increase GPU utilization with Volta Multi-Process Service (MPS)

Development Tools

  • Optimize and pre-fetch memory access by identifying source code causing page faults in unified memory
  • Profile NVLink efficiently by adding events to timeline and color coding connections
  • Inspect unified memory performance bottlenecks with new event filters based on virtual address, migration reason and page fault access type

Complete release notes can be found here.