Big data analytics using cloud computing based frameworks for power management systems: Status, constraints, and future recommendations
Traditional parallel computing for power management systems has prime challenges such
as execution time, computational complexity, and efficiency like process time and delays in …
as execution time, computational complexity, and efficiency like process time and delays in …
Mapping techniques in multicore processors: current and future trends
Multicore systems are in demand due to their high performance thus making application
mapping an important research area in this field. Breaking an application into multiple …
mapping an important research area in this field. Breaking an application into multiple …
Asymo: scalable and efficient deep-learning inference on asymmetric mobile cpus
On-device deep learning (DL) inference has attracted vast interest. Mobile CPUs are the
most common hardware for on-device inference and many inference frameworks have been …
most common hardware for on-device inference and many inference frameworks have been …
Hybrid fuzzy-based deep remora reinforcement learning based task scheduling in heterogeneous multicore-processor
In recent times, heterogeneous multicore processors have played a critical role in many
applications because they provide better performance in adapting power constraints with …
applications because they provide better performance in adapting power constraints with …
An intelligent task scheduling mechanism for autonomous vehicles via deep learning
G Balasekaran, S Jayakumar, R Pérez de Prado - Energies, 2021 - mdpi.com
With the rapid development of the Internet of Things (IoT) and artificial intelligence,
autonomous vehicles have received much attention in recent years. Safe driving is one of …
autonomous vehicles have received much attention in recent years. Safe driving is one of …
Evaluation of the intel thread director technology on an alder lake processor
JC Saez, M Prieto-Matias - Proceedings of the 13th ACM SIGOPS Asia …, 2022 - dl.acm.org
Asymmetric multicore processors (AMPs) combine high-performance big cores with more
energy-efficient small cores, all exposing a shared instruction-set architecture but different …
energy-efficient small cores, all exposing a shared instruction-set architecture but different …
Prediction of job characteristics for intelligent resource allocation in HPC systems: a survey and future directions
Z Hou, H Shen, X Zhou, J Gu, Y Wang… - Frontiers of Computer …, 2022 - Springer
Nowadays, high-performance computing (HPC) clusters are increasingly popular. Large
volumes of job logs recording many years of operation traces have been accumulated. In the …
volumes of job logs recording many years of operation traces have been accumulated. In the …
[PDF][PDF] Hardware response and performance analysis of multicore computing systems for deep learning algorithms
With the advancement in technological world, the technologies like Artificial Intelligence (AI),
Machine Learning (ML), and Deep Learning (DL) are gaining more popularity in many …
Machine Learning (ML), and Deep Learning (DL) are gaining more popularity in many …
Low-complex resource mapping heuristics for mobile and iot workloads on NoC-HMPSoC architecture
Network-on-chip-based heterogeneous multiprocessor system-on-a chip (NoC-HMPSoC) a
single board computer is extensively utilized in many real-time applications such as mobile …
single board computer is extensively utilized in many real-time applications such as mobile …
A hybrid computational approach to process real-time streaming multi-sources data and improve classification for emergency patients triage services: moving forward …
Abstract In the Internet of Medical Things (IoMT)-based real-time telemedicine systems,
patients can utilize a wide range of medical devices and sensors, which leads to the …
patients can utilize a wide range of medical devices and sensors, which leads to the …