Maple can take advantage of CUDA-enabled graphics cards to leverage the tremendous computational power of those cards, dramatically speeding up key computations.

  • The CUDA package allows Maple to use the graphics processing unit (GPU) of your NVIDIA Compute Unified Device Architecture (CUDA)-enabled hardware to accelerate key linear algebra routines, when such a card is available on your computer.
  • Numeric computations done using CUDA acceleration can run an order of magnitude faster.
  • The key computations that take advantage of the CUDA technology are fundamental, often repeated steps in virtually all matrix computations, so substantial speedups are available for all your large-scale linear algebra problems.
  • Both single (float[4]) and double-precision (float[8]) operations are supported, depending on the capabilities of the GPU hardware in use.


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