Accelerating matrix multiplication is crucial to achieve high performance in many application domains, including neural networks, graph analytics, and scientific computing. These applications process ...

Coded computing has proved its efficiency in handling a straggler issue in distributed computing framework. However, in a coded distributed computing framework, there may exist Byzantine workers who ...

Suite of tools for deploying and training deep learning models using the JVM. Highlights include model import for keras, tensorflow, and onnx/pytorch, a modular and tiny c++ library for running math ...

As you can see, some very common (3D) operations like matrix multiplication and inversion can be almost 10 times faster than their corresponding RTL versions. In addition, FastMath includes a number ...