Survey on prediction models of applications for resources provisioning in cloud

M Amiri, L Mohammad-Khanli - Journal of Network and Computer …, 2017 - Elsevier
According to the dynamic nature of cloud and the rapid growth of the resources demand in it,
the resource provisioning is one of the challenging problems in the cloud environment. The …

Biphase adaptive learning-based neural network model for cloud datacenter workload forecasting

J Kumar, D Saxena, AK Singh, A Mohan - Soft Computing, 2020 - Springer
Cloud computing promises elasticity, flexibility and cost-effectiveness to satisfy service level
agreement conditions. The cloud service providers should plan and provision the computing …

Runtime data management on non-volatile memory-based heterogeneous memory for task-parallel programs

K Wu, J Ren, D Li - SC18: International Conference for High …, 2018 - ieeexplore.ieee.org
Non-volatile memory (NVM) provides a scalable solution to replace DRAM as main memory.
Because of relatively high latency and low bandwidth of NVM (comparing with DRAM), NVM …

A comparison of GPU execution time prediction using machine learning and analytical modeling

M Amarís, RY de Camargo, M Dyab… - 2016 IEEE 15th …, 2016 - ieeexplore.ieee.org
Today, most high-performance computing (HPC) platforms have heterogeneous hardware
resources (CPUs, GPUs, storage, etc.) A Graphics Processing Unit (GPU) is a parallel …

Dynamic, behavioral-based estimation of resource provisioning based on high-level application terms in cloud platforms

G Kousiouris, A Menychtas, D Kyriazis… - Future Generation …, 2014 - Elsevier
Delivering Internet-scale services and IT-enabled capabilities as computing utilities has
been made feasible through the emergence of Cloud environments. While current …

Accelerating architectural simulation via statistical techniques: A survey

Q Guo, T Chen, Y Chen… - IEEE Transactions on …, 2015 - ieeexplore.ieee.org
In computer architecture research and development, simulation is a powerful way of
acquiring and predicting processor behaviors. While architectural simulation has been …

Machine learning-based runtime scheduler for mobile offloading framework

H Eom, PS Juste, R Figueiredo… - 2013 IEEE/ACM 6th …, 2013 - ieeexplore.ieee.org
Remote offloading techniques have been proposed to overcome the limited resources of
mobile platforms by leveraging external powerful resources such as personal work-stations …

A conceptual framework for HPC operational data analytics

A Netti, W Shin, M Ott, T Wilde… - 2021 IEEE International …, 2021 - ieeexplore.ieee.org
This paper provides a broad framework for understanding trends in Operational Data
Analytics (ODA) for High-Performance Computing (HPC) facilities. The goal of ODA is to …

The rise of the (modelling) bots: Towards assisted modelling via social networks

S Pérez-Soler, E Guerra, J De Lara… - 2017 32nd IEEE/ACM …, 2017 - ieeexplore.ieee.org
We are witnessing a rising role of mobile computing and social networks to perform all sorts
of tasks. This way, social networks like Twitter or Telegram are used for leisure, and they …

Machine learning based auto-tuning for enhanced opencl performance portability

TL Falch, AC Elster - 2015 IEEE International Parallel and …, 2015 - ieeexplore.ieee.org
Heterogeneous computing, which combines devices with different architectures, is rising in
popularity, and promises increased performance combined with reduced energy …