Deep learning at the speed of light. ... We compile these ops into complex GPU kernels, so even though our ops are simple, we get high performance through the power of compilers! ... All neural ...

In addition, deep learning is considered as black box and hard to interpret. These factors make deep learning not widely used in microbiome-wide association studies. In this work, we construct a ...

In this work, image-to-graph conversion via clustering has been proposed. Locally group homogeneous pixels have been grouped into a superpixel, which can be identified as node. Simple linear iterative ...

Distributed deep learning is becoming a necessity to cope with growing data and model sizes. Its computation is typically characterized by a simple tensor data abstraction to model multi-dimensional ...

For instance, the GPU may be utilized to train the machine-learning model or carry out inference while the CPU samples the graph and creates mini-batches of data. These straightforward adjustments ...