Add to ORKGThe objective of many ongoing research projects in high performance computing (HPC) areas is to develop an advanced computing and optimization infrastructure for extremely large-scale graphs on the peta-scale supercomputers. The extremel
In the first week of January 2014 Dagstuhl hosted a Perspectives Workshop on "Connecting Performance...
International audienceExtreme Data is an incarnation of Big Data concept distinguished by the massiv...
Existing distributed graph analytics systems are categorized into two main groups: those that focus ...
Current large-scale HPC systems consist of complex configurations with a huge number of potentially ...
In order to achieve significantly better graph computation performance, an advanced multiprocessor a...
At the International Research Workshop on Advanced High Performance Computing Systems held in Cetrar...
Graph processing is increasingly popular in a variety of scientific and engineering domains. Consequ...
The advent of extreme-scale computing systems, e.g., Petaflop supercomputers, High Per-formance Comp...
The NPS High Performance Computing Center supports investigators using scientific workstations, su...
The growing use of graph in many fields has sparked a broad interest in developing high-level graph ...
High performance computing (HPC) and Big Data are technologies vital for advancement in science, bus...
Abstract—Owing to the extreme parallelism and the high component failure rates of tomorrow’s exascal...
In the present work we apply High-Performance Computing techniques to two Big Data problems. The frs...
NPS' High Performance Computing (HPC) Center supports investigators using scientific workstations, s...
Iterative computation on large graphs has challenged system research from two aspects: (1) how to co...
In the first week of January 2014 Dagstuhl hosted a Perspectives Workshop on "Connecting Performance...
International audienceExtreme Data is an incarnation of Big Data concept distinguished by the massiv...
Existing distributed graph analytics systems are categorized into two main groups: those that focus ...
Current large-scale HPC systems consist of complex configurations with a huge number of potentially ...
In order to achieve significantly better graph computation performance, an advanced multiprocessor a...
At the International Research Workshop on Advanced High Performance Computing Systems held in Cetrar...
Graph processing is increasingly popular in a variety of scientific and engineering domains. Consequ...
The advent of extreme-scale computing systems, e.g., Petaflop supercomputers, High Per-formance Comp...
The NPS High Performance Computing Center supports investigators using scientific workstations, su...
The growing use of graph in many fields has sparked a broad interest in developing high-level graph ...
High performance computing (HPC) and Big Data are technologies vital for advancement in science, bus...
Abstract—Owing to the extreme parallelism and the high component failure rates of tomorrow’s exascal...
In the present work we apply High-Performance Computing techniques to two Big Data problems. The frs...
NPS' High Performance Computing (HPC) Center supports investigators using scientific workstations, s...
Iterative computation on large graphs has challenged system research from two aspects: (1) how to co...
In the first week of January 2014 Dagstuhl hosted a Perspectives Workshop on "Connecting Performance...
International audienceExtreme Data is an incarnation of Big Data concept distinguished by the massiv...
Existing distributed graph analytics systems are categorized into two main groups: those that focus ...