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:
16-bit floating point (FP16) data format
- Store up to 2x larger datasets in GPU memory
- Reduce memory bandwidth requirements by up to 2x
- New mixed precision cublasSgemmEX() routine supports 2x larger matrices
New cuSPARSE GEMVI routines
- Optimized dense matrix x sparse vector routines - ideal for Natural Language Processing
Instruction-level profiling helps pinpoint performance bottlenecks
- Quickly identify the specific lines of source code limiting the performance of GPU code
Apply advanced performance optimizations more easily
Previous version 6.5.14: