Convergence of edge computing and deep learning: A comprehensive survey
Ubiquitous sensors and smart devices from factories and communities are generating
massive amounts of data, and ever-increasing computing power is driving the core of …
massive amounts of data, and ever-increasing computing power is driving the core of …
A systematic review of Green AI
With the ever‐growing adoption of artificial intelligence (AI)‐based systems, the carbon
footprint of AI is no longer negligible. AI researchers and practitioners are therefore urged to …
footprint of AI is no longer negligible. AI researchers and practitioners are therefore urged to …
Edge intelligence: Paving the last mile of artificial intelligence with edge computing
With the breakthroughs in deep learning, the recent years have witnessed a booming of
artificial intelligence (AI) applications and services, spanning from personal assistant to …
artificial intelligence (AI) applications and services, spanning from personal assistant to …
[HTML][HTML] All one needs to know about fog computing and related edge computing paradigms: A complete survey
Abstract With the Internet of Things (IoT) becoming part of our daily life and our environment,
we expect rapid growth in the number of connected devices. IoT is expected to connect …
we expect rapid growth in the number of connected devices. IoT is expected to connect …
Machine learning at the network edge: A survey
Resource-constrained IoT devices, such as sensors and actuators, have become ubiquitous
in recent years. This has led to the generation of large quantities of data in real-time, which …
in recent years. This has led to the generation of large quantities of data in real-time, which …
A survey on edge computing systems and tools
Driven by the visions of Internet of Things and 5G communications, the edge computing
systems integrate computing, storage, and network resources at the edge of the network to …
systems integrate computing, storage, and network resources at the edge of the network to …
A survey on optimized implementation of deep learning models on the nvidia jetson platform
S Mittal - Journal of Systems Architecture, 2019 - Elsevier
Abstract Design of hardware accelerators for neural network (NN) applications involves
walking a tight rope amidst the constraints of low-power, high accuracy and throughput …
walking a tight rope amidst the constraints of low-power, high accuracy and throughput …
Green ai: Do deep learning frameworks have different costs?
The use of Artificial Intelligence (ai), and more specifically of Deep Learning (dl), in modern
software systems, is nowadays widespread and continues to grow. At the same time, its …
software systems, is nowadays widespread and continues to grow. At the same time, its …
Bandwidth-efficient live video analytics for drones via edge computing
Real-time video analytics on small autonomous drones poses several difficult challenges at
the intersection of wireless bandwidth, processing capacity, energy consumption, result …
the intersection of wireless bandwidth, processing capacity, energy consumption, result …