Energy efficiency in cloud computing data center: a survey on hardware technologies

A Katal, S Dahiya, T Choudhury - Cluster Computing, 2022 - Springer
The internet is expanding its viewpoint into each conceivable part of the cutting-edge
economy. Unshackled from our web programs today, the internet is characterizing our way …

GPU power cap** for energy-performance trade-offs in training of deep convolutional neural networks for image recognition

A Krzywaniak, P Czarnul, J Proficz - International conference on …, 2022 - Springer
In the paper we present performance-energy trade-off investigation of training Deep
Convolutional Neural Networks for image recognition. Several representative and widely …

A survey of thermal management in cloud data centre: Techniques and open issues

R Rani, R Garg - Wireless Personal Communications, 2021 - Springer
In recent years, there has been a great increase in usage of cloud data centers which leads
the energy consumption growth by about 10% a year continuously. Further, due to the …

SDN-DVFS: an enhanced QoS-aware load-balancing method in software defined networks

M Mahmoudi, A Avokh, B Barekatain - Cluster computing, 2022 - Springer
Recently, software defined networks (SDN) has been considered as a promising technology
for improving the network performance. However, the load imbalance problem considerably …

GPU Shader Analysis and Power Optimization Model

G Konnurmath, S Chickerur - Engineering, Technology & Applied Science …, 2024 - etasr.com
With the rapid advancements in 3D game technology, workload characterization has
become crucial for each new generation of games. The increased complexity of scenes in …

Autotuning based on frequency scaling toward energy efficiency of blockchain algorithms on graphics processing units

M Stachowski, A Fiebig, T Rauber - The Journal of Supercomputing, 2021 - Springer
Energy-efficient computing is especially important in the field of high-performance
computing (HPC) on supercomputers. Therefore, automated optimization of energy …

Pm3: Power modeling and power management for processing-in-memory

C Zhang, T Meng, G Sun - 2018 IEEE International symposium …, 2018 - ieeexplore.ieee.org
Processing-in-Memory (PIM) has been proposed as a solution to accelerate data-intensive
applications, such as real-time Big Data processing and neural networks. The acceleration …

EPPMiner: An extended benchmark suite for energy, power and performance characterization of heterogeneous architecture

Q Wang, P Xu, Y Zhang, X Chu - Proceedings of the Eighth International …, 2017 - dl.acm.org
To address the ever-increasing demand for computing capacities, more and more
heterogeneous systems have been designed to use both general-purpose and special …

Power-Aware Characteristics of Matrix Operations on Multicores

G Konnurmath, S Chickerur - Applied Artificial Intelligence, 2021 - Taylor & Francis
ABSTRACT GPU accelerators are massively parallel in nature and tailored for processing
numerically intensive high-performance computing applications. But most of the applications …

Performance evaluation of parallel haemodynamic computations on heterogeneous clouds

O Bystrov, A Kačeniauskas, R Pacevič… - Computing and …, 2020 - cai.sk
The article presents performance evaluation of parallel haemodynamic flow computations
on heterogeneous resources of the OpenStack cloud infrastructure. The main focus is on the …