The aim of this master thesis is to both give the programmer some guidelines to achieve good scalabilities with tasked based programming models and to improve the COMPSs runtime scheduler the capabilities to reach this scaling objectives
Basic science is becoming ever more computationally intensive, increasing the need for large-scale c...
International audienceNowadays, when we face with numerous data, when data cannot be classified into...
At present, big data is very popular, because it has proved to be much successful in many fields suc...
The aim of this master thesis is to both give the programmer some guidelines to achieve good scalabi...
Many fields of modern science require huge amounts of computation, and workflows are a very popular ...
In both business and computing, complex projects are often defined as workflows, which describe the ...
MapReduce ecosystems are (still) widely popular for big data processing in data centers. To address ...
© 2018 Elsevier B.V. As distributed systems such as clouds get increasingly popular in the use for b...
In recent years there has been an extraordinary growth of large-scale data processing and related te...
This dissertation addresses three key challenges that are characteristic to the online scheduling of...
MapReduce ecosystems are (still) widely popular for big data processing in data centers. To address ...
Data intensive computing holds the promise of major scientific breakthroughs and discoveries from th...
Recent trends in big data have shown that the amount of data continues to increase at an exponential...
Many functions in today’s society are immensely dependent on data. Data drives everything from busin...
Runtime systems are critical in the support for big data applications. For example, task dependency ...
Basic science is becoming ever more computationally intensive, increasing the need for large-scale c...
International audienceNowadays, when we face with numerous data, when data cannot be classified into...
At present, big data is very popular, because it has proved to be much successful in many fields suc...
The aim of this master thesis is to both give the programmer some guidelines to achieve good scalabi...
Many fields of modern science require huge amounts of computation, and workflows are a very popular ...
In both business and computing, complex projects are often defined as workflows, which describe the ...
MapReduce ecosystems are (still) widely popular for big data processing in data centers. To address ...
© 2018 Elsevier B.V. As distributed systems such as clouds get increasingly popular in the use for b...
In recent years there has been an extraordinary growth of large-scale data processing and related te...
This dissertation addresses three key challenges that are characteristic to the online scheduling of...
MapReduce ecosystems are (still) widely popular for big data processing in data centers. To address ...
Data intensive computing holds the promise of major scientific breakthroughs and discoveries from th...
Recent trends in big data have shown that the amount of data continues to increase at an exponential...
Many functions in today’s society are immensely dependent on data. Data drives everything from busin...
Runtime systems are critical in the support for big data applications. For example, task dependency ...
Basic science is becoming ever more computationally intensive, increasing the need for large-scale c...
International audienceNowadays, when we face with numerous data, when data cannot be classified into...
At present, big data is very popular, because it has proved to be much successful in many fields suc...