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The challenge is that many tasks are not well suited to parallel computing.
The technique is now called parallel computing.
Possible heavy parallel computing.
For parallel computing on mobile devices, we can apply the CPU based parallel computing with multi-thread approach and the CPU based parallel computing with OpenCL.
Authors exploit general purpose parallel computing on NVIDIA GPUs.
Compute unified device architecture is NVIDIA's parallel computing architecture.
CUDA is a parallel computing architecture developed by NVIDIA.
Finally we design parallel computing algorithm to compute these equations.
This specialization makes them ideal for machine learning, specifically parallel computing.
For improved speed, we use parallel computing (via MPI).
CUDA is a massive parallel computing architecture model.
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