Improving mapreduce energy efficiency for computation intensive workloads
T Wirtz, R Ge - 2011 International Green Computing …, 2011 - ieeexplore.ieee.org
MapReduce is a programming model for data intensive computing on large-scale distributed
systems. With its wide acceptance and deployment, improving the energy efficiency of …
systems. With its wide acceptance and deployment, improving the energy efficiency of …
Energy-aware scheduling of mapreduce jobs
The majority of large-scale data intensive applications executed by data centers are based
on MapReduce or its open-source implementation, Hadoop. Such applications are executed …
on MapReduce or its open-source implementation, Hadoop. Such applications are executed …
On the performance and energy efficiency of Hadoop deployment models
E Feller, L Ramakrishnan… - 2013 IEEE International …, 2013 - ieeexplore.ieee.org
The exponential growth of scientific and business data has resulted in the evolution of the
cloud computing and the MapReduce parallel programming model. Cloud computing …
cloud computing and the MapReduce parallel programming model. Cloud computing …
Tapa: Temperature aware power allocation in data center with map-reduce
In this paper, we analytically derive, implement, and empirically evaluate a solution for
maximizing the execution rate of Map-Reduce jobs subject to power constraints in data …
maximizing the execution rate of Map-Reduce jobs subject to power constraints in data …
Governing energy consumption in Hadoop through CPU frequency scaling: An analysis
With increasingly inexpensive storage and growing processing power, the cloud has rapidly
become the environment of choice to store and analyze data for a variety of applications …
become the environment of choice to store and analyze data for a variety of applications …
[PDF][PDF] Energy efficiency for MapReduce workloads: An in-depth study
Energy efficiency has emerged as a crucial optimization goal in data centers. MapReduce
has become a popular and even fashionable distributed processing model for parallel …
has become a popular and even fashionable distributed processing model for parallel …
Hadoopcl: Mapreduce on distributed heterogeneous platforms through seamless integration of hadoop and opencl
M Grossman, M Breternitz… - 2013 IEEE International …, 2013 - ieeexplore.ieee.org
As the scale of high performance computing systems grows, three main challenges arise:
the programmability, reliability, and energy efficiency of those systems. Accomplishing all …
the programmability, reliability, and energy efficiency of those systems. Accomplishing all …
Energy efficiency dilemma: P2p-cloud vs. datacenter
Energy consumption is increasing in the IT sector and a remarkable part of this energy is
consumed in data centers. Numerous techniques have been proposed to solve the energy …
consumed in data centers. Numerous techniques have been proposed to solve the energy …
Performance management of accelerated mapreduce workloads in heterogeneous clusters
Next generation data centers will be composed of thousands of hybrid systems in an attempt
to increase overall cluster performance and to minimize energy consumption. New …
to increase overall cluster performance and to minimize energy consumption. New …
Energy-aware scheduling of mapreduce jobs for big data applications
The majority of large-scale data intensive applications executed by data centers are based
on MapReduce or its open-source implementation, Hadoop. Such applications are executed …
on MapReduce or its open-source implementation, Hadoop. Such applications are executed …