Future data center energy-conservation and emission-reduction technologies in the context of smart and low-carbon city construction
The energy consumption of data centers accounts for approximately 1% of that of the world,
the average power usage effectiveness is in the range of 1.4–1.6, and the associated carbon …
the average power usage effectiveness is in the range of 1.4–1.6, and the associated carbon …
MLCAD: A survey of research in machine learning for CAD keynote paper
Due to the increasing size of integrated circuits (ICs), their design and optimization phases
(ie, computer-aided design, CAD) grow increasingly complex. At design time, a large design …
(ie, computer-aided design, CAD) grow increasingly complex. At design time, a large design …
The path planning of mobile robot by neural networks and hierarchical reinforcement learning
J Yu, Y Su, Y Liao - Frontiers in Neurorobotics, 2020 - frontiersin.org
Existing mobile robots cannot complete some functions. To solve these problems, which
include autonomous learning in path planning, the slow convergence of path planning, and …
include autonomous learning in path planning, the slow convergence of path planning, and …
Saving time and cost on the scheduling of fog-based IoT applications using deep reinforcement learning approach
Due to the rapid growth of intelligent devices and the Internet of Things (IoT) applications in
recent years, the volume of data that is generated by these devices is increasing …
recent years, the volume of data that is generated by these devices is increasing …
A survey of domain-specific architectures for reinforcement learning
M Rothmann, M Porrmann - IEEE Access, 2022 - ieeexplore.ieee.org
Reinforcement learning algorithms have been very successful at solving sequential decision-
making problems in many different problem domains. However, their training is often time …
making problems in many different problem domains. However, their training is often time …
Deep reinforcement learning empowers automated inverse design and optimization of photonic crystals for nanoscale laser cavities
Photonics inverse design relies on human experts to search for a design topology that
satisfies certain optical specifications with their experience and intuitions, which is relatively …
satisfies certain optical specifications with their experience and intuitions, which is relatively …
A survey on energy management for mobile and IoT devices
S Pasricha, R Ayoub, M Kishinevsky… - IEEE Design & …, 2020 - ieeexplore.ieee.org
Mobile and IoT devices have proliferated our daily lives. However, these miniaturized
computing systems should be highly energy-efficient due to their ultrasmall form factor …
computing systems should be highly energy-efficient due to their ultrasmall form factor …
Dynamic resource management of heterogeneous mobile platforms via imitation learning
The complexity of heterogeneous mobile platforms is growing at a rate faster than our ability
to manage them optimally at runtime. For example, state-of-the-art systems-on-chip (SoCs) …
to manage them optimally at runtime. For example, state-of-the-art systems-on-chip (SoCs) …
Approximate policy-based accelerated deep reinforcement learning
X Wang, Y Gu, Y Cheng, A Liu… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
In recent years, the deep reinforcement learning (DRL) algorithms have been developed
rapidly and have achieved excellent performance in many challenging tasks. However, due …
rapidly and have achieved excellent performance in many challenging tasks. However, due …
An energy-aware online learning framework for resource management in heterogeneous platforms
Mobile platforms must satisfy the contradictory requirements of fast response time and
minimum energy consumption as a function of dynamically changing applications. To …
minimum energy consumption as a function of dynamically changing applications. To …