Add to ORKGIn the present work we apply High-Performance Computing techniques to two Big Data problems. The frst one deals with the analysis of large graphs by using a parallel distributed architecture, whereas the second one consists in the design and implementation of a scalable solution for fast indexing and searching of large datasets of heterogeneous documents
Abstract—Large science projects rely on complex workflows to analyze terabytes or petabytes of data....
Our society is generating an increasing amount of data at an unprecedented scale, variety, and speed...
The result set produced by a search engine in response to the user query is very large. It is typica...
High performance computing (HPC) and Big Data are technologies vital for advancement in science, bus...
Graphs are a common representation in many problem domains, including engineering, finance, medicine...
Recent advances in large-scale experimental facilities ushered in an era of data-driven science. The...
One of the main challenges in data analytics is that discovering structures and patterns in complex ...
Big data analytics is eventual discovery of knowledge from large set of data thus leading to busines...
At the International Research Workshop on Advanced High Performance Computing Systems held in Cetrar...
Irregular algorithms such as graph algorithms, sorting, and sparse matrix multiplication, present nu...
Analyzing massive-data sets and streams is computationally very challenging. Data sets in systems bi...
In this Big data era, the need for performing large-scale computations is evident. A better understa...
The parallel programming come a long way with the advances in the HPC. The high performance computin...
Analyzing large data has become very feasible with recent advances in modern technology. Data acquis...
BigData revolutionised the IT industry. It first interested the OLTP systems. Distributed Hash Table...
Abstract—Large science projects rely on complex workflows to analyze terabytes or petabytes of data....
Our society is generating an increasing amount of data at an unprecedented scale, variety, and speed...
The result set produced by a search engine in response to the user query is very large. It is typica...
High performance computing (HPC) and Big Data are technologies vital for advancement in science, bus...
Graphs are a common representation in many problem domains, including engineering, finance, medicine...
Recent advances in large-scale experimental facilities ushered in an era of data-driven science. The...
One of the main challenges in data analytics is that discovering structures and patterns in complex ...
Big data analytics is eventual discovery of knowledge from large set of data thus leading to busines...
At the International Research Workshop on Advanced High Performance Computing Systems held in Cetrar...
Irregular algorithms such as graph algorithms, sorting, and sparse matrix multiplication, present nu...
Analyzing massive-data sets and streams is computationally very challenging. Data sets in systems bi...
In this Big data era, the need for performing large-scale computations is evident. A better understa...
The parallel programming come a long way with the advances in the HPC. The high performance computin...
Analyzing large data has become very feasible with recent advances in modern technology. Data acquis...
BigData revolutionised the IT industry. It first interested the OLTP systems. Distributed Hash Table...
Abstract—Large science projects rely on complex workflows to analyze terabytes or petabytes of data....
Our society is generating an increasing amount of data at an unprecedented scale, variety, and speed...
The result set produced by a search engine in response to the user query is very large. It is typica...