The rapid explosion of online Cloud-based services has put more pressure on Cloud service providers for being in condition to satisfy the corresponding huge demand for computing power. While this challenge can be easily tackled by adding more resources, achieving high-power efficiency (i.e., the amount of data processed per watt) is far more complex. In recent years, to cope with the power-efficiency challenge, different hardware systems (e.g., GPUs, FPGAs, DSPs), each exposing different capabilities and programming models, became part of the standard data center hardware ecosystem. Besides their growing adoption on the core of the Cloud, also edge systems started to embrace heterogeneity to enable data processing closer to the data sources...
Computer science and engineering have evolved rapidly over the last decade offering innovative Machi...
In recent years, the need for the efficient deployment of Neural Networks (NN) on edge devices has b...
Tiny machine learning (TinyML) has become an emerging field according to the rapid growth in the are...
Computing has undergone a significant transformation over the past two decades, shifting from a mach...
Advanced computing systems have long been enablers for breakthroughs in Machine Learning (ML) algori...
The growing number of low-power smart devices in the Internet of Things is coupled with the concept ...
The recent progress in machine learning in computer vision guides to enormous hardware requirements....
Deploying convolutional neural networks (CNNs) in embedded devices that operate at the edges of Inte...
Although state-of-the-art in many typical machine-learning tasks, deep learning algorithms are very ...
Energy and power are the main design constraints for modern high-performance computing systems. Inde...
Modern machine learning (ML) applications are often deployed in the cloud environment to exploit the...
Nowadays, with the huge advance of sensor technology and the increase of the amount of data generate...
Machine learning (ML) has been extensively employed for strategy optimization, decision making, data...
The number of connected Internet of Things (IoT) devices are expected to reach over 20 billion by 20...
In Internet of Things (IoT) scenarios, it is challenging to deploy Machine Learning (ML) algorithms ...
Computer science and engineering have evolved rapidly over the last decade offering innovative Machi...
In recent years, the need for the efficient deployment of Neural Networks (NN) on edge devices has b...
Tiny machine learning (TinyML) has become an emerging field according to the rapid growth in the are...
Computing has undergone a significant transformation over the past two decades, shifting from a mach...
Advanced computing systems have long been enablers for breakthroughs in Machine Learning (ML) algori...
The growing number of low-power smart devices in the Internet of Things is coupled with the concept ...
The recent progress in machine learning in computer vision guides to enormous hardware requirements....
Deploying convolutional neural networks (CNNs) in embedded devices that operate at the edges of Inte...
Although state-of-the-art in many typical machine-learning tasks, deep learning algorithms are very ...
Energy and power are the main design constraints for modern high-performance computing systems. Inde...
Modern machine learning (ML) applications are often deployed in the cloud environment to exploit the...
Nowadays, with the huge advance of sensor technology and the increase of the amount of data generate...
Machine learning (ML) has been extensively employed for strategy optimization, decision making, data...
The number of connected Internet of Things (IoT) devices are expected to reach over 20 billion by 20...
In Internet of Things (IoT) scenarios, it is challenging to deploy Machine Learning (ML) algorithms ...
Computer science and engineering have evolved rapidly over the last decade offering innovative Machi...
In recent years, the need for the efficient deployment of Neural Networks (NN) on edge devices has b...
Tiny machine learning (TinyML) has become an emerging field according to the rapid growth in the are...