Distributed machine learning (DML) techniques, such as federated learning, partitioned
learning, and distributed reinforcement learning, have been increasingly applied to wireless …

The staggering innovations and emergence of numerous deep learning (DL) applications
have forced researchers to reconsider hardware architecture to accommodate fast and …

One embodiment provides for a compute apparatus to per form machine learning
operations, the compute apparatus comprising a decode unit to decode a single instruction …

为了有效去除地震数据随机噪声, 提出了一种基于卷积神经网络(CNN) 的地震数据随机噪声去除
算法. 算法的关键在于构建一个适用于地震数据去噪的CNN, 包含输入层, 卷积层, 激活层 …

Deep learning frameworks have been widely deployed on GPU servers for deep learning
applications in both academia and industry. In training deep neural networks (DNNs), there …

Deep neural networks (DNNs) have made significant achievements in a wide variety of
domains. For the deep learning tasks, multiple excellent hardware platforms provide efficient …

Background In deep learning the most significant breakthrough in the field of image
recognition, object detection language processing was done by Convolutional Neural …

INTRODUCTION: In recent years, deep learning techniques have been made to outperform
the earlier state-of-the-art machine learning techniques in many areas, with one of the most …

One embodiment provides for a compute apparatus to perform machine learning operations,
the apparatus comprising a decode unit to decode a single instruction into a decoded …

With increasing number of open-source deep learning (DL) software tools made available,
benchmarking DL software frameworks and systems is in high demand. This paper presents …