While OpenCL sounds attractive because of its generality, it hasn’t performed as well as CUDA on NVIDIA GPUs, and many deep learning frameworks either don’t support OpenCL or only support it ...

CUDA is Nvidia’s API for its general purpose ... If the current progress is anything to go by, PyTorch should be as good as any deep learning framework by the time of the PyTorch 1.0 release ...

This week yielded a new benchmark effort comparing various deep learning frameworks on a short list of CPU and GPU ... CPU only versions because of high parallelization on lots of CUDA cores,” the ...

Nvidia runs the Deep Learning Institute (DLI), through which it helps developers learn to use frameworks to design, train, and deploy neural network-powered machine learning for a variety of ...

Of course, it also has to have the requisite software stack in place as well, which is an area that Nvidia has been ahead with its own CUDA libraries to hook into most well-known deep learning ...

TensorFlow works seamlessly on Linux, allowing developers to leverage NVIDIA CUDA and TensorRT for faster computations. PyTorch, developed by Facebook's AI Research Lab, is another popular deep ...

The NVIDIA ® DIGITS™ Deep Learning GPU Training System version 2 (DIGITS 2) and NVIDIA CUDA ® Deep Neural Network ... versions of the deep learning frameworks Caffe, Minerva, Theano and ...

Within the realm of data science, deep learning frameworks are predominantly delivered via software found in the Python ecosystem. When looking at the options in the space, it may appear to some as a ...