A curated list of research in System for Edge Intelligence and Computing(Edge MLSys), including Frameworks, Tools, Repository, etc. Paper notes are also provided.
Overview of edge computing in LinkedIn. [LinkedIn]
IoT (Internet of Things) Wireless & Cloud Computing Emerging Technologies. [Coursera]
Udemy Introduction to Edge Computing. [Udemy]
IOT Edge Computing | IoT Examples | Use Cases | HackerEarth Webinar.[Youtube]
Intel® Edge AI for IoT Developers [Udacity]
Stanford Seminar - The Future of Edge Computing from an International Perspective. [Youtube]
deepC is a vendor independent deep learning library, compiler and inference framework designed for small form-factor devices including μControllers, IoT and Edge devices[GitHub]
Tengine, developed by OPEN AI LAB, is an AI application development platform for AIoT scenarios launched by OPEN AI LAB, which is dedicated to solving the fragmentation problem of aiot industrial chain and accelerating the landing of AI industrialization. [GitHub]
Mobile Computer Vision @ Facebook [GitHub]
alibaba/MNN: MNN is a lightweight deep neural network inference engine. It loads models and do inference on devices. [GitHub]
XiaoMi/mobile-ai-bench: Benchmarking Neural Network Inference on Mobile Devices [GitHub]
XiaoMi/mace-models: Mobile AI Compute Engine Model Zoo [GitHub]
Tencent/nccn: ncnn is a high-performance neural network inference computing framework optimized for mobile platforms. [Github]
Tencent/TNN: [Github]
SqueezeWave: Extremely Lightweight Vocoders for On-device Speech Synthesis [GitHub][Paper]
Kubeedge: A Kubernetes Native Edge Computing Framework [GitHub]
Convergence of edge computing and deep learning: A comprehensive survey. [Paper]
Deep learning with edge computing: A review. [Paper]
Edge Intelligence: Paving the Last Mile of Artificial Intelligence with Edge Computing. [Paper]
Machine Learning at Facebook: Understanding Inference at the Edge. [Paper]
Mobile Edge Computing: A Survey on Architecture and Computation Offloading. [Paper]
边缘智能综述(edge intelligence)[Zhihu]
AI edge engineer [Blog]
Advance your edge computing skills with three new AWS Snowcone courses[Blog]
How fast is my model? [Blog]
Modeling of Deep Neural Network (DNN) Placement and Inference in Edge Computing. [Paper]
Characterizing the Deep Neural Networks Inference Performance of Mobile Applications. [Paper]
Neurosurgeon: Collaborative intelligence between the cloud and mobile edge. [Paper]
26ms Inference Time for ResNet-50: Towards Real-Time Execution of all DNNs on Smartphone [Paper]
Big/little deep neural network for ultra low power inference.[Paper]
JointDNN: an efficient training and inference engine for intelligent mobile cloud computing services. [Paper]
TeamNet: A Collaborative Inference Framework on the Edge.
Bottlenet++: An end-to-end approach for feature compression in device-edge co-inference systems. [Paper]
Distributing deep neural networks with containerized partitions at the edge. [Paper]
Collaborative execution of deep neural networks on internet of things devices. [Paper]
DeepThings: Distributed Adaptive Deep Learning Inference on Resource-Constrained IoT Edge Clusters. [Paper]
Scaling for edge inference of deep neural networks. [Paper]
Swing: Swarm Computing for Mobile Sensing.[Paper]
A Locally Distributed Mobile Computing Framework for DNN based Android Applications.[Paper]
Auto-tuning Neural Network Quantization Framework for Collaborative Inference Between the Cloud and Edge.[Paper]
DeepX: a software accelerator for low-power deep learning inference on mobile devices.[Paper]
ECRT: An Edge Computing System for Real-Time Image-based Object Tracking. [Paper]
Learning IoT in Edge: Deep Learning for the Internet of Things with Edge Computing[Paper]
Hierarchical Edge Caching in Device-to-Device Aided Mobile Networks: Modeling, Optimization, and Design. [Paper]
DeepCachNet: A Proactive Caching Framework Based on Deep Learning in Cellular Networks[Paper]
Deep learning-based edge caching for multi-cluster heterogeneous networks[[Paper]](Deep learning-based edge caching for multi-cluster heterogeneous networks)
Learn to Cache: Machine Learning for Network Edge Caching in the Big Data Era[Paper]
Deep Learning Based Caching for Self-Driving Car in Multi-access Edge Computing[Paper]
A smart caching mechanism for mobile multimedia in information centric networking with edge computing[Paper]
Context-Aware Convolutional Neural Network over Distributed System in Collaborative Computing. [Paper]
OpenEI: An Open Framework for Edge Intelligence. [Paper]
Latency and Throughput Characterization of Convolutional Neural Networks for Mobile Computer Vision [Paper]
NestDNN: Resource-Aware Multi-Tenant On-Device Deep Learning for Continuous Mobile Vision [Paper]
Lavea: Latency-aware video analytics on edge computing platform [Paper]
Scaling Video Analytics on Constrained Edge Nodes [Paper] [GitHub]
Fogflow: Easy programming of iot services over cloud and edges for smart cities. [Paper] [GitHub]