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Many emerging large-scale data science applications require searching large graphs distributed across multiple memories and processors. This paper presents a distributed breadth-first search (BFS) scheme that scales for random graphs with up to three billion vertices and 30 billion edges. Scalability was tested on IBM BlueGene/L with 32,768 nodes at the(More)
This paper presents a middleware framework for storing, accessing and analyzing massive-scale semantic graphs. The framework, MSSG, targets scale-free semantic graphs with O(10<sup>12</sup>) (trillion) vertices and edges. Here, we present the overall architectural design of the framework, as well as a prototype implementation for cluster architectures. The(More)
BlueGene/L (BG/L), developed through a partnership between IBM and Lawrence Livermore National Laboratory (LLNL), is currently the world's largest system both in terms of scale, with 131,072 processors, and absolute performance , with a peak rate of 367 Tflop/s. BG/L has led the last four Top500 lists with a Linpack rate of 280.6 Tflop/s for the full(More)