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

Simultaneous localization and mapping (SLAM) is a critical capability in autonomous
navigation, but in order to scale SLAM to the setting of “lifelong” SLAM, particularly under …

Many link prediction algorithms require the computation of a similarity metric on each vertex
pair, which is quadratic in the number of vertices and infeasible for large networks. We …

Simultaneous localization and mapping (SLAM) is a critical capability in autonomous
navigation, but memory and computational limits make long-term application of common …

Information of Connected Vehicles (CVs) could describe vehicular dynamics in much greater
detail, enhancing the effectiveness of traffic control systems. One important such system is …

We present PSPIKE+, as a family of parallel hybrid linear system solvers that are more
robust than other available preconditioned iterative methods, and more scalable than …

In this paper we consider the problem of estimating pair-wise signals׳ dissimilarities through
the comparison of the underlying local manifold structures. Aiming to confront with issues …

Many simulations in science and engineering give rise to sparse linear systems of
equations. It is a well known fact that the cost of the simulation process is almost always …

The Fiedler vector of a graph plays a vital role in many applications. But it is usually very
expensive in that it involves the solution of an eigenvalue problem. In this paper, we …

The availability of large-scale computing platforms comprising of tens of thousands of
multicore processors motivates the need for the next generation of highly scalable sparse …