Abstract:
The objective of many ongoing research projects in high performance computing (HPC) areas, such as Graph500 and Green Graph500 benchmarks, is to develop an advanced computing and optimization infrastructure for extremely large-scale graphs on the peta-scale supercomputers. The extremely large-scale graphs that have recently emerged in various application fields, such as transportation, social networks, cyber-security, and bioinformatics, require fast and scalable analysis. The number of vertices in the graph networks has grown from billions to trillions and that of the edges from hundreds of billions to tens of trillions, and therefore, we propose a new framework of software stacks for extremely large-scale graph analysis systems, such as parallel graph analysis and optimization libraries on multiple CPUs and GPUs, hierarchal graph stores using non-volatile memory (NVM) devices, and graph processing and visualization systems.
Keywords:
Mathematical Optimization, High-performance computing, Graph analysis, Super computer
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