Wednesday | October 26, 2016
NVIDIA Dramatically Simplifies Parallel Programming With CUDA 6 Essay Writing Service Law Buy Descriptive Essay Essay On Energy Master Thesis On Branding

  • Unified Memory — Simplifies programming by enabling applications to access CPU and GPU memory without the need to manually copy data from one to the other, and makes it easier to add support for GPU acceleration in a wide range of programming languages.
  • Drop-in Libraries — Automatically accelerates applications’ BLAS and FFTW calculations by up to 8X by simply replacing the existing CPU libraries with the GPU-accelerated equivalents.
  • Multi-GPU Scaling — Re-designed BLAS and FFT GPU libraries automatically scale performance across up to eight GPUs in a single node, delivering over nine teraflops of double precision performance per node, and supporting larger workloads than ever before (up to 512 GB). Multi-GPU scaling can also be used with the new BLAS drop-in library.

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