We present a new lock-free parallel algorithm for computing betweenness centrality of
massive complex networks that achieves better spatial locality compared with previous …

The purpose of the GraphBLAS Forum is to standardize linear-algebraic building blocks for
graph computations. An important part of this standardization effort is to translate the …

The rise of graph analytic systems has created a need for ways to measure and compare the
capabilities of these systems. Graph analytics present unique scalability difficulties. The …

Large-scale computation on graphs and other discrete structures is becoming increasingly
important in many applications, including computational biology, web search, and …

A crucial element of large web companies is their ability to collect and analyze massive
amounts of data. Tuple store databases are a key enabling technology employed by many of …

The MIT/IEEE/Amazon GraphChallenge. org encourages community approaches to
developing new solutions for analyzing graphs and sparse data. Sparse AI analytics present …

Analytics tasks manipulate structured data with variants of relational algebra (RA) and
quantitative data with variants of linear algebra (LA). The two computational models have …

Combinatorial techniques have become essential tools across the landscape of
computational science, and some of the combinatorial ideas undergirding these tools are …

The Apache Accumulo database is an open source relaxed consistency database that is
widely used for government applications. Accumulo is designed to deliver high performance …

Graphics processing units (CPUs) have been accepted as a powerful and viable
coprocessor solution in high-performance computing domain. In order to maximize the …