Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Graph-parallel computation has become a crucial component in emerging applications of b search, data analytics and machine learning. In practice, most graphs derived from real-world phenomena are very large and scale-free. Unfortunately, distributed graph-parallel computation of these  natural  graphs still suffers strong scalability issues on contemporary multicore clusters. To embrace the multicore architecture in distributed graph-parallel computation,  propose the framework Graphine, which features (i) A Scatter-Combine computation abstraction that is evolved from the traditional vertex-centric approach by fusing the paired scatter and gather operations, executed separately on two edge sides, into a one-sided scatter. Further coupled with active message mechanism, it potentially reduces intermediate message cost and enables fine-grained parallelism on multicore architecture. (ii) An Agent-Graph data model, which leverages an idea similar to vertex-cut but conceptually splits the remote replica into two agent types of scatter and combiner, resulting in less communication.  implement the Graphine framework and evaluate it using several representative algorithms on six large real-world graphs and a series of synthetic graphs with por-law degree distributions.  show that Graphine achieves sublinear scalability with the number of cores per node, number of nodes, and graph sizes (up to one billion vertices), and is 2   $\sim$      15 times faster than the state-of-the-art PorGraph on a cluster of 16 multicore nodes.
['Jie Yan', 'Guangming Tan', 'Zeyao Mo', 'Ninghui Sun']
I am writing a research paper on a idea Graphine: Programming Graph-Parallel Computation of Large Natural Graphs for Multicore Clusters
[{"from": "human", "value": "I am writing a research paper on a idea Graphine: Programming Graph-Parallel Computation of Large Natural Graphs for Multicore Clusters"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Graph-parallel computation has become a crucial component in emerging applications of b search, data analytics and machine learning. In practice, most graphs derived from real-world phenomena are very large and scale-free. Unfortunately, distributed graph-parallel computation of these  natural  graphs still suffers strong scalability issues on contemporary multicore clusters. To embrace the multicore architecture in distributed graph-parallel computation,  propose the framework Graphine, which features (i) A Scatter-Combine computation abstraction that is evolved from the traditional vertex-centric approach by fusing the paired scatter and gather operations, executed separately on two edge sides, into a one-sided scatter. Further coupled with active message mechanism, it potentially reduces intermediate message cost and enables fine-grained parallelism on multicore architecture. (ii) An Agent-Graph data model, which leverages an idea similar to vertex-cut but conceptually splits the remote replica into two agent types of scatter and combiner, resulting in less communication.  implement the Graphine framework and evaluate it using several representative algorithms on six large real-world graphs and a series of synthetic graphs with por-law degree distributions.  show that Graphine achieves sublinear scalability with the number of cores per node, number of nodes, and graph sizes (up to one billion vertices), and is 2   $\\sim$      15 times faster than the state-of-the-art PorGraph on a cluster of 16 multicore nodes."}]