It is our view that the state of the art in constructing a large collection of graph algorithms in terms of linear algebraic operations is mature enough to support the emergence of a standard set of primitive building blocks. This paper is a position paper defining the problem and announcing our intention to launch an open effort to define this standard
Abstract In this document we present a new approach to developing sequential and parallel dense line...
AbstractWe survey an algebra of formal languages suitable to deal with graph algorithms. As an examp...
The mixture of data in real-life exhibits structure or connection property in nature. Typical data i...
Abstract — It is our view that the state of the art in constructing a large collection of graph algo...
The challenges associated with graph algorithm scaling led multiple scientists to identify the need ...
Graph algorithms can be expressed in terms of linear algebra. GraphBLAS is a library of low-level bu...
The GraphBLAS standard (GraphBlas.org) is being developed to bring the potential of matrix based gra...
This dissertation advances the state of the art for scalable high-performance graph analytics and da...
Graph algorithms typically have very low computational intensities, hence their execution times are ...
The analysis of graphs has become increasingly important to a wide range of applications. Graph anal...
Optimizing linear algebra operations has been a research topic for decades. The compact languag...
This tutorial describes the theoretical background of GraphBLAS. First, we discuss the need for a st...
AbstractThe analysis of graphs has become increasingly important to a wide range of applications. Gr...
Algorithmic graph theory has been expanding at an extremely rapid rate since the middle of the twent...
A linear algebraic approach to graph algorithms that exploits the sparse adjacency matrix representa...
Abstract In this document we present a new approach to developing sequential and parallel dense line...
AbstractWe survey an algebra of formal languages suitable to deal with graph algorithms. As an examp...
The mixture of data in real-life exhibits structure or connection property in nature. Typical data i...
Abstract — It is our view that the state of the art in constructing a large collection of graph algo...
The challenges associated with graph algorithm scaling led multiple scientists to identify the need ...
Graph algorithms can be expressed in terms of linear algebra. GraphBLAS is a library of low-level bu...
The GraphBLAS standard (GraphBlas.org) is being developed to bring the potential of matrix based gra...
This dissertation advances the state of the art for scalable high-performance graph analytics and da...
Graph algorithms typically have very low computational intensities, hence their execution times are ...
The analysis of graphs has become increasingly important to a wide range of applications. Graph anal...
Optimizing linear algebra operations has been a research topic for decades. The compact languag...
This tutorial describes the theoretical background of GraphBLAS. First, we discuss the need for a st...
AbstractThe analysis of graphs has become increasingly important to a wide range of applications. Gr...
Algorithmic graph theory has been expanding at an extremely rapid rate since the middle of the twent...
A linear algebraic approach to graph algorithms that exploits the sparse adjacency matrix representa...
Abstract In this document we present a new approach to developing sequential and parallel dense line...
AbstractWe survey an algebra of formal languages suitable to deal with graph algorithms. As an examp...
The mixture of data in real-life exhibits structure or connection property in nature. Typical data i...