Scale-Train: A Scalable DNN Training Framework for a Heterogeneous GPU Cloud
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3184692
Abstract: In order to cope with the growing scale of deep neural network (DNN) models and training data, the use of cloud computing for distributed DNN training is becoming increasingly popular. The amount of available resources… read more here.
Keywords: scale; training; cloud; dnn training ... See more keywords
GANPU: An Energy-Efficient Multi-DNN Training Processor for GANs With Speculative Dual-Sparsity Exploitation
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Journal of Solid-State Circuits"
DOI: 10.1109/jssc.2021.3066572
Abstract: This article presents generative adversarial network processing unit (GANPU), an energy-efficient multiple deep neural network (DNN) training processor for GANs. It enables on-device training of GANs on performance- and battery-limited mobile devices, without sending user-specific… read more here.
Keywords: dnn training; ganpu energy; energy efficient; processor ... See more keywords
Enhancing DNN Training Efficiency Via Dynamic Asymmetric Architecture
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Computer Architecture Letters"
DOI: 10.1109/lca.2023.3275909
Abstract: Deep neural networks (DNNs) require abundant multiply-and-accumulate (MAC) operations. Thanks to DNNs’ ability to accommodate noise, some of the computational burden is commonly mitigated by quantization–that is, by using lower precision floating-point operations. Layer granularity… read more here.
Keywords: training efficiency; enhancing dnn; dynamic asymmetric; architecture ... See more keywords
A Mobile DNN Training Processor With Automatic Bit Precision Search and Fine-Grained Sparsity Exploitation
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Micro"
DOI: 10.1109/mm.2021.3135457
Abstract: In this article, an energy-efficient deep learning processor is proposed for deep neural network (DNN) training in mobile platforms. Conventional mobile DNN training processors suffer from high-bit precision requirement and high ReLU-dependencies. The proposed processor… read more here.
Keywords: training; dnn training; bit precision; processor ... See more keywords
A Guessing Entropy-Based Framework for Deep Learning-Assisted Side-Channel Analysis
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Information Forensics and Security"
DOI: 10.1109/tifs.2023.3273169
Abstract: Recently deep-learning (DL) techniques have been widely adopted in side-channel power analysis. A DL-assisted SCA generally consists of two phases: a deep neural network (DNN) training phase and a follow-on attack phase using the trained… read more here.
Keywords: guessing entropy; dnn; side channel; deep learning ... See more keywords