Though, such devices are equipped with low computing resources which represent the main challenges of Edge Computing(EC) [16]. As a way to overcome this challenge, transfer learning could be a possible way to consolidate the needed computational power and facilitate more efficient EC. Therefore, ...
VII Deep Learning Training at Edge VII-A Distributed Training at Edge VII-B Vanilla Federated Learning at Edge VII-C redCommunication-efficient FL VII-D Resource-optimized FL VII-E redSecurity-enhanced FL VIII Deep Learning for Optimizing Edge VIII-A redDL for Adaptive Edge Caching VIII-A1 Use...
Deep Learning on Mobile Devices Through Neural Processing Units and Edge Computing. In IEEE INFOCOM 2022-IEEE Conference on Computer Communications (pp. 1209-1218). IEEE. Q1 该paper解决了什么问题? 在训练DNN的过程中,NPU存在处理速度快但有精度损失。原因是:NPU只能支持FP16操作并使用FP16存储每个层的...
In the context of edge computing (EC) paradigm the new type of specific System on a Chip (SoC) devices with tensor processing architectures (TPAs) appeared for running deep learning (DL) models efficiently on edge computing accelerators (ECAs). Despite availability of numerous benchmarks of ECA...
After several years of development, edge computing for deep learning has shown incomparable practical value in the IoT environment. Pushing computing resources to the edge in closer proximity to devices enables low-latency service delivery for both safety and applications. This Special Issue, Deep ...
Learn how deep learning works and how to use deep learning to design smart systems in a variety of applications. Resources include videos, examples, and documentation.
Deep Learning is artificial intelligence (AI) that has networks capable of learning unsupervised from data that is unstructured or unlabeled.
This research presents a hybrid model using deep learning with Particle Swarm Intelligence and Genetic Algorithm (“DPSO-GA”) for dynamic workload provisioning in cloud computing. The proposed model works in two phases. The first phase utilizes a hybrid PSO-GA approach to address the prediction ...
Learn to build deep learning, accelerated computing, and accelerated data science applications for industries, such as healthcare, robotics, manufacturing, and more. Reduce Time to Production Build production-quality solutions with the same DLI base environment containers used in the courses, available ...
This research addresses these challenges by optimizing Edge Computing scenarios in two ways, two-phase immersion cooling systems and smart resource allocation via Deep Reinforcement Learning. To this end, several Edge Computing scenarios have been modeled, simulated, and optimized with energy-aware ...