Deep learning is one of the hottest subjects in the field of computer science these days, fueled by the convergence of massive datasets, highly parallel processing power, and the drive to build ...

The Intel® Math Kernel Library, Intel MKL, is a library of common numerical methods used in scientific and engineering applications. Highly optimized for Intel processors running Windows, MacOS, and ...

In Part 1 we introduced Intel® Math Kernel Library for Deep Neural Networks (Intel® MKL-DNN), an open source performance library for deep learning applications. Detailed steps were provided on how to ...

Nearly all big science, machine learning, neural network, and machine vision applications employ algorithms that involve large matrix-matrix multiplication. But multiplying large matrices pushes the ...

The MKL libraries for accelerating math operations debuted in Intel's own Python distribution, but now other Pythons are following suit Last year Intel became a Python distributor, offering its own ...

Data scientists and deep and machine learning researchers rely on frameworks and libraries such as Torch, Caffe, TensorFlow, and Theano. Studies by Colfax Research and Kyoto University have found that ...

What comes after “Big Data”? I’d say “Faster Big Data.” And it’s going to be a game changer well beyond what Big Data has done so far. Fast and efficient Big Data applications will change our lives.