Using the GPUs embedded in mobile devices allows for increasing the performance of the applications running on them while reducing the energy consumption of their execution. This article presents a task-based solution for adaptative, collaborative heterogeneous computing on mobile cloud environments. To implement our proposal, we extend the COMPSs-Mobile framework – an implementation of the COMPSs programming model for building mobile applications that offload part of the computation to the Cloud – to support offloading computation to GPUs through OpenCL. To evaluate our solution, we subject the prototype to three benchmark applications representing different application patterns.This work is partially supported by the Joint-Laboratory on E...
Nowadays, cloud and edge computing technologies has been adopted in different use cases, such as vi...
Map-Reduce is a framework for processing parallelizable problem across huge datasets using a large c...
In recent years, the employment of smart mobile phones has increased enormously and are concerned as...
Using the GPUs embedded in mobile devices allows for increasing the performance of the applications ...
This paper presents a framework to develop and execute applications in distributed and highly dynami...
The advent of the Cloud and the popularization of mobile devices have led us to a shift in computing...
GPUs traditionally offer high computational capabilities, frequently higher than their CPU counterpa...
In this article, we present COMPSs-Mobile: a framework that aims to ease the development of MCC appl...
Modern mobile devices are often required to process multiple computationally intensive applications ...
Nowadays, mobile devices are suffering from limited computational resource. To increase capabilities...
Porting a computationally demanding CUDA application to a GPU designed for mobile phones and tablets...
Mobile Cloud Computing (MCC) combines mobile computing and cloud computing aiming to aid performance...
Mobile processors continue to increase in performance while becoming more power efficient, providing...
For the past few years we have seen an exponential growth in the number of mobile devices and in th...
With heterogeneous computing becoming mainstream, researchers and software vendors have been trying ...
Nowadays, cloud and edge computing technologies has been adopted in different use cases, such as vi...
Map-Reduce is a framework for processing parallelizable problem across huge datasets using a large c...
In recent years, the employment of smart mobile phones has increased enormously and are concerned as...
Using the GPUs embedded in mobile devices allows for increasing the performance of the applications ...
This paper presents a framework to develop and execute applications in distributed and highly dynami...
The advent of the Cloud and the popularization of mobile devices have led us to a shift in computing...
GPUs traditionally offer high computational capabilities, frequently higher than their CPU counterpa...
In this article, we present COMPSs-Mobile: a framework that aims to ease the development of MCC appl...
Modern mobile devices are often required to process multiple computationally intensive applications ...
Nowadays, mobile devices are suffering from limited computational resource. To increase capabilities...
Porting a computationally demanding CUDA application to a GPU designed for mobile phones and tablets...
Mobile Cloud Computing (MCC) combines mobile computing and cloud computing aiming to aid performance...
Mobile processors continue to increase in performance while becoming more power efficient, providing...
For the past few years we have seen an exponential growth in the number of mobile devices and in th...
With heterogeneous computing becoming mainstream, researchers and software vendors have been trying ...
Nowadays, cloud and edge computing technologies has been adopted in different use cases, such as vi...
Map-Reduce is a framework for processing parallelizable problem across huge datasets using a large c...
In recent years, the employment of smart mobile phones has increased enormously and are concerned as...