Distributed Accelerated Reinforcement Learning This is an implementation of distributed reinforcement learning, used in several published works including Divergence-Augmented Policy Optimization and Exponentiall
Deep learning has disrupted nearly every field of research, including those of direct importance to drug discovery, such as medicinal chemistry and pharmacology. This revolution has largely been attributed to the unprecedented advances in highly parallelizable graphics processing units (GPUs) and the deve...
[13]Xiao, Wencong, et al. "AntMan: Dynamic Scaling on {GPU} Clusters for Deep Learning." 14th {USENIX} Symposium on Operating Systems Design and Implementation ({OSDI} 20). 2020. [14]Bai, Zhihao, et al. "PipeSwitch: Fast Pipelined Context Switching for Deep Learning Applications." 14th ...
In contrast to servers, a mobile computing environmentimposes many domain-specific constraints that invite us to review the general computingapproach used in a deep learning framework implementation. In this paper, we propose adeep learning framework that has been specifically designed for mobile device...
在众多映射函数F的估计方法中,深度学习 (Deep Learning,DL)方法利用深度神经网络(Deep Neural Network,DNN) 的多层非线性变换能实现映射函数F的无限逼近、表征输入数据分布,具有强大的自动特征提取和复杂模型构建能力,在医学图像处理领域应用十分广泛。其中,GPU是深度学习模型训练的算力保障。而一旦模型训练完成,借助GPU的...
[13]Xiao, Wencong, et al. "AntMan: Dynamic Scaling on {GPU} Clusters for Deep Learning." 14th {USENIX} Symposium on Operating Systems Design and Implementation ({OSDI} 20). 2020. [14]Bai, Zhihao, et al. "PipeSwitch: Fast Pipelined Context Switch...
Distributed Accelerated Reinforcement Learning This is an implementation of distributed reinforcement learning, used in several published works including Divergence-Augmented Policy Optimization and Exponentially Weighted Imitation Learning for Batched Historical Data (also has a Ray RLlib Implementation). 目前最...
cuDNN is a neural network library that is GPU optimized and can take full advantage of Nvidia GPU. This library consists of the implementation of convolution, forward and backward propagation, activation functions, and pooling. It is a must library without which you cannot use GPU for training ...
We used a stacked hourglass network34implemented in Pytorch44(https://github.com/pytorch/pytorch). The network architecture code is from the implementation in ‘PyTorch-Pose’ (https://github.com/bearpaw/pytorch-pose). The full network architecture is shown in Supplementary Fig.1. The Image augm...
[13]Xiao, Wencong, et al. "AntMan: Dynamic Scaling on {GPU} Clusters for Deep Learning." 14th {USENIX} Symposium on Operating Systems Design and Implementation ({OSDI} 20). 2020. [14]Bai, Zhihao, et al. "PipeSwitch: Fast Pipelined Context Switching for Deep Learning Applications." 14th...