General Sparse Matrix-Matrix Multiplication (SpGEMM) has attracted much attention from
researchers in graph analyzing, scientific computing, and deep learning. Many optimization …

Protected database search systems cryptographically isolate the roles of reading from,
writing to, and administering the database. This separation limits unnecessary administrator …

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 …

Triangle counting serves as a key building block for a set of important graph algorithms in
network science. In this paper, we address the IEEE HPEC Static Graph Challenge problem …

The ability to collect and analyze large amounts of data is a growing problem within the
scientific community. The growing gap between data and users calls for innovative tools that …

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 …

In 2013, we released a position paper to launch a community effort to define a common set
of building blocks for constructing graph algorithms in the language of linear algebra. This …

Sparse matrices are often used to model the interactions among different objects and they
are prevalent in many areas including e-commerce, social network, and biology. As one of …

Triangle counting is a representative graph analysis algorithm with several applications. It is
also one of the three benchmarks used in the IEEE HPEC Graph Challenge. Triangle …