基于GPU的LABVIEW编程

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GPU Begins With G and Ends With ULabVIEW GPU Computing unleashes the computing power of NVIDIA GPUs via the CUDA interface from within a LabVIEW application. Code that calls the GPU for computation is integrated into the native parallel execution system of LabVIEW as if it were any other multi-threaded external library function call.


The BasicsLabVIEW GPU Computing includes:

• A collection of LabVIEW data types and VIs, called LVCUDA and LVCUBLAS, for interfacing with the CUDA runtime and CUBLAS Library functions.
• A framework, called NICompute, that establishes a compute context in which user-define GPU functions execute
  

Put together these items allow LabVIEW users to:

• Target multiple GPU devices  from the LabVIEW diagram
• Manage resources across all GPU devices
• Facilitate numeric array data transfers to and from the GPU
• Execute GPU process in parallel with CPU execution
• Provide shared resource protection when performing GPU processes from different user libraries
• Block invalid references when used on the wrong GPU device
• Establish clean-up callbacks that ensure resources are freed even when the application is aborted.