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 ...

数学计算中的硬件加速是社区经常探讨的话题，如果能够利用一些库和硬件的优势，无疑能够帮助科研、生产等。近日，一个优化 AMD CPU 的帖子在 Matlab 社区引起讨论——通过几行代码，将 AMD CPU 加速 250%，进而帖子作者将方法推广到了其他社区，介绍了更普适性 ...

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 ...

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 ...

The most widely used matrix-matrix multiplication routine is GEMM (GEneral Matrix Multiplication) from the BLAS (Basic Linear Algebra Subroutines) library. And these days it can be found being used in ...

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 ...

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.