Add to ORKGIn this thesis we proposed and implemented the MMR, a new and open-source MapRe- duce model with MPI for parallel and distributed programing. MMR combines Pthreads, MPI and the Google\u27s MapReduce processing model to support multi-threaded as well as dis- tributed parallelism. Experiments show that our model signi cantly outperforms the leading open-source solution, Hadoop. It demonstrates linear scaling for CPU-intensive processing and even super-linear scaling for indexing-related workloads. In addition, we designed a MMR live DVD which facilitates the automatic installation and con guration of a Linux cluster with integrated MMR library which enables the development and execution of MMR applications
We present GPMR, our MapReduce library that leverages the power of GPU clusters for large-scale comp...
The processing of massive amounts of data on clusters with finite amount of memory has become an imp...
Abstract—In an attempt to increase the performance/cost ratio, large compute clusters are becoming h...
In this thesis we proposed and implemented the MMR, a new and open-source MapRe- duce model with MP...
Web-scale digital assets comprise millions or billions of documents. Due to such increase, sequentia...
Abstract The timely processing of large-scale digital forensic targets demands the empoyment of larg...
MapReduce is an emerging programming paradigm for data parallel applications proposed by Google to s...
In an attempt to increase the performance/cost ratio, large compute clusters are becoming heterogene...
As the data growth rate outpace that of the processing capabilities of CPUs, reaching Petascale, tec...
MapReduce is a programming model and an associated implementation for processing and generating larg...
MapReduce is the preferred cloud computing framework used in large data analysis and application pro...
In the last two decades, the continuous increase of computational power has produced an overwhelming...
Abstract—MapReduce is arguably the most successful par-allelization framework especially for process...
Abstract—MapReduce is a powerful tool for processing large data sets used by many applications runni...
The computing power of modern high performance systems cannot be fully exploited using traditional p...
We present GPMR, our MapReduce library that leverages the power of GPU clusters for large-scale comp...
The processing of massive amounts of data on clusters with finite amount of memory has become an imp...
Abstract—In an attempt to increase the performance/cost ratio, large compute clusters are becoming h...
In this thesis we proposed and implemented the MMR, a new and open-source MapRe- duce model with MP...
Web-scale digital assets comprise millions or billions of documents. Due to such increase, sequentia...
Abstract The timely processing of large-scale digital forensic targets demands the empoyment of larg...
MapReduce is an emerging programming paradigm for data parallel applications proposed by Google to s...
In an attempt to increase the performance/cost ratio, large compute clusters are becoming heterogene...
As the data growth rate outpace that of the processing capabilities of CPUs, reaching Petascale, tec...
MapReduce is a programming model and an associated implementation for processing and generating larg...
MapReduce is the preferred cloud computing framework used in large data analysis and application pro...
In the last two decades, the continuous increase of computational power has produced an overwhelming...
Abstract—MapReduce is arguably the most successful par-allelization framework especially for process...
Abstract—MapReduce is a powerful tool for processing large data sets used by many applications runni...
The computing power of modern high performance systems cannot be fully exploited using traditional p...
We present GPMR, our MapReduce library that leverages the power of GPU clusters for large-scale comp...
The processing of massive amounts of data on clusters with finite amount of memory has become an imp...
Abstract—In an attempt to increase the performance/cost ratio, large compute clusters are becoming h...